Highly Competitive - software industry insights

MDM – Speaking the “Language” of Business

 

Part 5 of a six part series on the "New Age of Master Data Management"

 

Data management continues to take on an ever-growing range of activities as the role of data has evolved and expanded for many organizations. Business agility and real-time insight are inherent requirements for many organizations. To meet such requirements organizations need right-time data on a continuous basis, where master data management initiatives are integral to processing business-ready data.

MDM software solutions are evolving as well, to better meet business needs. The new directions of MDM software obviously carry a heavy package of sophisticated technology. Analytics processes now utilize numerous disparate data sources that need context and relationship information that comes from trustworthy and relevant master data. Some MDM solutions are utilizing technologies like graph databases to take advantage of multi-dimensional capabilities to more expansively and agilely handle relationships across all data types. More analytics processes are now providing information and insight primarily for business users who aren't necessarily highly adept at hands-on technology or data management, which opens up new challenges and opportunities for MDM vendors.

The value of these solutions is heavily tied to business needs and objectives. And this value must be clearly and honestly communicated to a growing array of business roles -- in the language of those business users.

In the 'New Age of MDM', with greater business participation, should IT and data management team members utilize more of the language of less technical business roles when in discussions related to MDM purchases, implementations and usages?

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

The "Languages" of MDM

Often conversations regarding master data management have been among IT and data management professionals, including more tech-savvy business roles involved in data management. The "language" of MDM started off primarily related to the worlds of IT and data management teams – in other words "techy talk".

But it's likely that this original "language" of MDM is now insufficient for meeting current business objectives and requirements, with the increased (and necessary) involvement of business roles, and the importance of selling the value of MDM to business managers and non-IT decision-makers. A growing lineup of business roles are increasingly involved in data governance discussions regarding practices, policies, cultural changes, and processes, as well as how to develop cross-functional teams and remediate silos for systems and data. Discussions with business roles also focus on the many ways that MDM can underpin important business initiatives and desired outcomes for objectives.

Conversations about the purchase of MDM software solutions can involve less technical roles. High level managers and C-level roles may be part of the decision-making processes: deciding if master data management itself should be adopted; understanding how MDM supports business requirements and goals; choosing which MDM software technologies to utilize; determining metrics and assessing outcomes related to MDM initiatives. Obviously these conversations also involve IT and data management teams, who now must be prepared to communicate well with different business roles.

 

Communicating in Customer Business Language

Those of us who work with software vendors (no matter which "side") are clearly aware that marketing and sales efforts for software solutions can deviate linguistically from technical terminology when communicating with less technical business users. But with the recent evolutionary changes for MDM software offerings, there is an increasing need for software vendors and practitioners of MDM to speak the language of the business.

When marketing and selling their MDM software to business roles, some vendors are dropping the use of the term "master data management" in order to bypass the "negative baggage" of traditional MDM solutions. Software vendors with new approaches to MDM are utilizing 'new language' to better describe what these new approaches really do, and how they better align the value with Business. Beyond simply being marketing efforts, most changes in 'language' are fairly honest attempts to more clearly connect MDM practices and solutions to real business needs, desired outcomes and advantage – in terminology that conveys realistic meaning to business users and decision-makers.

Business roles involved in buying decisions may not know what MDM is, can get confused or lost in the terminology and technology, can see it as too complicated – all of which can interfere with the prospective customer's understanding of why MDM is important for making competitive use of data. It's legitimate for vendors to focus on the high level of what MDM contributes to improve data and business processes, and what the business benefits are for each organization. Focus should also cover how the MDM solution handles business needs relative to existing organizational infrastructure, along with business practices and processes – and ultimately business objectives and desired outcomes.

If MDM software vendors demonstrate clearly how the technologies connect to achieving business objectives and outcomes, it better enlightens prospective customers on the benefits and essential nature of master data management – both in terms of the MDM practice and the supporting technologies. And very importantly, business language is essential to uncover business problems to be solved and how data management fits into overall business strategies.

Obviously there is a danger of over-simplification. MDM implementations can take time, both for setting up the technologies, and to institute cultural changes, data governance practices and new cross-functional processes. These aspects of MDM practices and solutions must be honestly communicated. Fortunately we are seeing great advances by different vendors to more quickly get MDM implementations up-and-running, and to take new approaches to how MDM programs are run in order to more clearly show the benefits of MDM and to produce them in a timely manner.

 

How MDM Software Vendors Speak the Language of Business

Often the "buyers" of enterprise software consist of multiple roles in an organization. No longer is software purchasing solely the domain of IT or other technical teams. There is frequently a composite "buyer" that draws on both influencers and decision-makers. Obviously technical teams perform a very important role in the purchase of software, more often as influencers rather than the final decision-makers. Business roles involved in enterprise software purchases can include: mid-level managers and business unit managers whose teams will be impacted by the use of the software; VPs who approve purchases; CEOs and CFOs who influence or dictate purchase decisions; and even staff in accounts payable who enact purchase transactions.

There are numerous software vendors with various flavors of MDM solutions who are leaning further into the language of business to conduct marketing and sales activities, and discussions about implementations and usage. Here are a couple of examples:

Enabling Content Management and Digital Interactions

Data and analytics have become essential components of the marketing efforts of most organizations. As a natural evolution, certain marketing technologies have embedded master data management capabilities to provide a more seamless application for business users. Some vendors of such marketing technologies don't call out MDM per se as a component of the solution.

A company that started as a traditional PIM vendor evolved its software into a solution for managing complex product information and multichannel content, for multiple roles in the information supply chain. For the user, the MDM / PIM part is "invisible". Prospective customers see this solution as an application that supports multichannel interactions, sophisticated content management and digital communications / marketing. The vendor places a strong emphasis on business user access to solution capabilities which further encompasses the business user perspective and language.

The solution provides a means to help resolve the "information fragmentation" that plagues organizational efforts to address the complexities of content management and usage, including highly variable sources (user-generated content, outside experts, brand) and diverse distribution channels (corporate website, mobile, social). The solution supports efforts to reconcile brand consistency and customer experience requirements that are necessary for successful digital marketing.

These are all very much business problems that are being addressed by business teams: digital marketing, ecommerce, content management, product strategy, and so on. The vendor reveals the value of the solution in the language of both business buyers and users. In marketing the solution, the software vendor focus isn't on data / information per se, but on what business users need to do with information and content, and how solution capabilities help them manage these activities in support of digital business needs.

 

Breaking Free from Traditional MDM through Data-Driven Business Applications

A vendor has introduced a relatively new "master data management" platform that is designed to break away from the traditional aspects of MDM software solutions. Instead of basing MDM and other data-related capabilities on relational databases, which has been a common choice until recently, this vendor loads combined and curated data into a NoSQL graph database. This allows the vendor to provide a scalable multi-tenant platform-as-a-service to innovate the creation of 'data applications' that are frequently closely tied to business functions and initiatives.  

On the technical side, this approach supports oversized datasets and accommodates rapidly evolving schema, something most relational databases find difficult. Graph databases provide a greatly improved method to delineate relationships between people, data, and things.  

For business users, this data management solution provides the means to build data-driven business applications that align with the goals and functions of the business. Business users can construct applications that are industry-specific to perform exactly the processes that are needed.

Business users don't need to know that the platform is based on an MDM infrastructure. This vendor wants to give business users the equivalent of "consumer apps" that produce information and analytics results quickly and easily. The vendor frequently speaks "business language" to help business users grasp these concepts.

For business users to successfully take advantage of this platform, the software capabilities and processes will have to be couched in the language of the business. The platform will have to carefully manage business user access based on guidelines and activities that make sense to less-technical business roles. As with any data management software solution that strives to support usage by business roles, IT and data management teams must be partners with the business to ensure successful outcomes. Collaborative capabilities enable such partnerships. So it will be interesting to see how successfully this vendor empowers and protects business usage of its MDM-based platform.

 

Going Beyond the "Traditional Language" of MDM

In the 'New Age of MDM', we are seeing great diversity as to how vendors, practitioners and organizations talk about MDM. Changes in language are essential to better connect MDM practices and solutions to real business needs, desired outcomes and value – in terminology that conveys real meaning to business management and decision-makers.

We'll continue to see a broadening variety of solutions that build on MDM, while deviating from traditional MDM implementations, in order to offer more business-relevant capabilities. Realistically, even the term "master data management" can be confusing for business roles in many organizations that could benefit from implementing MDM practices and technologies. It can be advantageous and helpful when vendors use new but honest terminology to better demonstrate business value and help prospective customers understand the 'why' and 'how' of implementing master data management initiatives.

It seems that the more innovative the MDM-related software solution, the greater the need for new ways to work directly with business roles and to communicate in the language of business. One of the stumbling blocks for such innovation of software and language comes from analyst firms that cover MDM software solutions. Increasingly certain analyst firms have become trapped by their inexact definitions of what kind of solution constitutes an "MDM offering", when evaluating MDM vendors for benchmark reports. Many vendors with MDM-related offerings are trailblazing new directions for MDM, but are excluded from certain industry benchmarks because of the narrow definition held by these firms. Analyst firms following such a path are performing a disservice to buyers who are interested in the right approach to MDM for their organizations, or who are in need of an MDM-based offering that provides business applications tailored for immediate needs.

 

Image source: hastac.org

 

About the author: Julie is an independent consultant and industry analyst for B2B software solutions, providing services to vendors to improve strategies for customers and target markets, products and solutions, and future direction. Julie has expertise in several solution spaces including: data integration and data quality; analytics and BI; business process, workflow and collaboration; digital marketing, WCM and social media; and the pivotal importance of user and customer experiences. Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt For more information: Julie Hunt Consulting – Strategies for B2B Software Solutions: Working from the Customer Perspective

 

Master Data Management Rebooted

 

Part 1 of a multi-part series on the "New Age of Master Data Management"

 

The 'New Age' of Master Data Management

It's about time that master data management (MDM) enjoyed a 'new age'. The creation and use of master data for business purposes has always been a good idea. The goal has been to make sense of all data that touches the organization: clean it up, add context, enrich it, and put it to work strategically as well as operationally.

Unfortunately, MDM has been plagued with certain problems from the very start. This stems mostly from the fact that MDM lands hard on some of the messiest aspects of an organization: data silos, unconnected systems and processes, management turf wars, and organizational roadblocks to disparate people working effectively together for common purpose.

 

Why Does Master Data Matter?

As the importance, value and sheer volume of data assets grow, so does the critical need for trustworthy, up-to-date information that is ready-to-go for any purpose. MDM processes consolidate data from numerous sources in meaningful ways. Master data also provides context and reveals data relationships for sources like big data that often exist as fragments without useful referential connections.

Master data has a large and growing role in areas that matter to organizations: strong brand presence, multichannel customer interactions, right-fit content and information, and highly variable buying journeys.

Analytics, particularly of the real-time variety, produce more realistic and trustworthy results when utilizing master data. Master data is often a key part of predictive analytics in support of: supply chain processes; personalization for improved customer experiences; logistics; operational optimization; and safety and preventive procedures.

A core element of MDM is data quality. Improved data quality impacts endless aspects of the business for reasons that should be obvious. But all too often, business management fails to comprehend how much poor data quality impacts profitability, productivity and even perception of the brand. Real world incidents that have been repeated at far too many organizations include:

• Inconsistent data of poor quality has led to extensive quantities of items in warehouses to "disappear" from systems records, never to be sold or consumed by the business. This can amount to millions of dollars of losses.
• Contradictory and confusing product lists and catalogs that deter purchases by customers and make sales staff look stupid – again with no purchases resulting.
• Costly pricing errors that persist undetected over time can have breath-taking negative impact on the bottom line.

 

Roadblocks, Detours, Dead Ends

Over time traditional approaches for MDM implementations have faltered for several reasons, many of which echo the failures of traditional ERP installations:

• Implementations take too long and cost too much.
• Project scope is often much too large.
• Business and IT teams are poorly coordinated for achieving the desired end state.
• Results fail to meet important business needs and / or show value in an obvious and timely fashion.
• Traditional approaches lag in keeping up with new technologies.
• Solutions have delayed including new data sources like the many varieties of big data.

A continuing obstacle is the lack of involvement of upper management with such important activities. If organizations want to tap into more data that is trustworthy and business-ready, it requires buy-in from upper management on down. Such buy-in is shown through clear commitments, upper management champions, and real data strategies – basically understanding the high value of data and what it takes to achieve it.

 

The Reality of MDM: People and Politics

What many people get wrong about MDM is thinking that it's all about the technology. In reality, it's much more about people, processes, and (unfortunately) politics. The people and politics of the organization can throw up significant obstacles to successful MDM programs. This is more likely to happen in organizations where upper level management has failed to provide its leadership and involvement in MDM implementations.

Silos permeate organizations from top to bottom, and not just in terms of software systems or digital assets. Collaboration between people is often limited. Internal politics can bring on secrecy or "turf wars" when it comes to the ownership of data and business processes. Resistance to change, lack of trust, desires to "hoard" data and information all come into play. Orchestration and collaboration of business and technical teams have always been critical to MDM success, but can be derailed by internal silos and politics.

Of course, technology provides an important means to achieve MDM implementations. But many vital activities aren't technical. For MDM and data governance to be successful, distinct changes must take place in organizations to eliminate the many silos that prevent the generation of reliable and up-to-date master data.

Not surprisingly, when things go wrong, organizations want to blame MDM technologies for the failures, instead of facing up to what really ails the organization. However, traditional MDM solutions have had significant limitations and often don't do much to help with the "people problem".

 

Wanted: Improved Approaches

A classic approach to MDM, the "bottom up" method, has not worked well simply because unsynchronized teams are trudging separate long roads to achieve the "desired end state" and often don't ever get there. It's easy to imagine the many ways that this method can be derailed. Instead, businesses benefit most from MDM approaches that work the way the business and its employees need to function to achieve real goals and objectives.

One of the most important changes to MDM approaches has organically grown out of the fact that much of MDM and data governance revolves around business use cases and business users. So it's gratifying to see more overtly business-defined approaches that not only delineate the approach but are enabling changes to the technologies that support them. These business-defined approaches reflect the complex, sophisticated needs of many organizations:

• Working from the desired end state and / or from the requirements of complex business problems to create master data management processes.
• Choosing contextual and analytic MDM solutions over traditional MDM tools that can handle new approaches for multi-dimensional and complex hierarchical data, including social and commercial graphs that underlie business use cases such as customer-responsive interactions across digital channels.
• Utilizing new MDM platforms that simplify the development of industry-focused business applications that take advantage of master data to solve business problems.
• Transforming model-driven approaches to be more flexible and agile in order to work with existing business processes as the starting point (instead of creating new processes), to deliver business value more quickly. IT and business teams can then transition to optimizing various processes for additional value.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

In a real world example, a pharmaceuticals company has utilized a new MDM solution to uncover significant information that improves the success of promoting drugs to individual healthcare organizations. Such information includes:

• Which insurance companies or payers accepted by the healthcare organization actually cover the drugs
• And for those payers, which insurance plans provide coverage
• What contracts for the pharmaceuticals company are already in place
• What other sales teams in the same company are already promoting to the healthcare organization
• Other important influence and decision-making factors that derive from complex hierarchies and networks of relationships

Running through such an analysis based on master data before approaching a healthcare organization helps the sales team determine if any business opportunities exist, and reveals better ways to approach contacts in the organization.

 

Master Data Management Rebooted

In the next five posts, I'll present and analyze what is changing for master data management approaches and solutions, including new technologies, and the evolutionary involvement of business roles in MDM and data governance.

One of the final aspects that I'll explore is this: is it time to quit calling it "master data management" and devise a name that better fits MDM Rebooted?

 

Image Source: hbr.org

 

About the author: Julie is an independent consultant and industry analyst for B2B software solutions, providing services to vendors to improve strategies for customers and target markets, products and solutions, and future direction. Julie has expertise in several solution spaces including: data integration and data quality; analytics and BI; business process, workflow and collaboration; digital marketing, WCM and social media; and the pivotal importance of user and customer experiences. Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt For more information: Julie Hunt Consulting – Strategies for B2B Software Solutions: Working from the Customer Perspective

 

Cloud Integration: One Platform, Diverse Users

 

Final article of a six-part series on the essential interwoven nature of Business and Modern Data Integration

 

When we're talking about diverse categories of users for data management software solutions such as data and application integration, it's essential to understand the perspective of each group of users and their needs and abilities, in order to develop the most suitable user interface and the right capabilities for each category.

The future of cloud integration platforms may belong to vendors that step up to truly understand diverse users and then deliver what they require to be successful.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Today cloud-based integration platforms are opening access to different categories of users including less-technical business users. Business users have begun to assume more hands-on use of integration capabilities to run pre-built integrations, profile datasets, perform data prep functions, and even create basic integrations through wizards and pre-configured components. This is a very important means to an equally important end: taking advantage of the availability of more data to help these users do their jobs better, to benefit the organization.

Vendors for cloud integration platforms are also beginning to recognize and support diverse technical users. There can be quite a bit of difference between a technically-adept line-of-business developer who lacks deep experience for creating integration processes, and a developer who is a data integration expert and likely tackling complex integration scenarios. Each category of developer requires the right user interface and capabilities to create, run and manage integrations, in order to accomplish work requirements and support business objectives.

I recently talked with a vendor that is focused on providing a single cloud integration platform for diverse user categories. The vendor is building out a framework of ten different categories of technical and business roles with a clear view to how the platform would be used by each category. This exploration of how different users make use of integration capabilities should help this vendor streamline and perfect what it takes for different users to work well not only on their own but with other user categories when needed. This requires the platform to guide each user category to the appropriate capabilities, including a role-responsive or adaptive UI.

Another cloud integration vendor is developing a vision for multiple categories of users with schematics for how they may continuously interact during several aspects of typical integration phases. For each category of user, the appropriate platform capabilities are pinpointed along the integration phase continuum. The vendor wants to expand the solution platform to shepherd and enable this symbiotic approach to business and IT working together for more effective integration processes.

When we're talking about different categories of users for data management functions, it's essential to understand the perspective of each group of users and their needs and abilities, in order to develop the most suitable user interface and the right capabilities for each category. In that sense, it takes an outside-in perspective, working from what different users need from data management functions like data integration, and how they are comfortable working. This is a very different approach for most integration vendors – the focus has long been solely on the technology (which obviously is still important). However usability from the user perspective has been a critical topic for software vendors for quite a while.

 

The Technologies Behind "Simple" User Interfaces

A cloud integration platform that is designed to support a variety of user access options clearly requires the development of sophisticated technologies that essentially make the complex seem simple to the user. Different categories of users often require variable versions of the same user interface that are streamlined for ease of use, and that provide access to role-appropriate capabilities.

As such, the integration solution can be distinctly shaped by the variety of user roles that are provided access to the platform.

Often the work done to enable less-technical users can also benefit UIs and capabilities for more technically-adept users, providing faster paths to creating integrations. More technical users can take advantage of pre-built integrations, shared services and components that require little or no coding, just as less technical users can. For those who need it, most cloud integration platforms include the ability to customize and extend pre-built integrations through coding and other methods.

Obviously to keep less technical users on the straight-and-narrow, monitoring and management by centralized IT teams behind the scenes are essential elements. Setting up the right balance of management and freedom for business users will take some hard work, but will pay off as certain integration activities can be handed off to business users. This is another area of business-IT collaboration that requires IT to enable business users to work with integration processes, not to prohibit them.

Cloud integration platforms provide other technologies to guide all categories of users to more quickly and confidently build, test and run integration processes. Such technologies include role-aware, interactive "tooltip" constructs that pop up in the UI in response to an action or choice. The influence of mobile apps and digital games can be seen in the better "tip systems".

UI-based guidance techniques include "crowd-sourced" recommendations that are derived from the analysis of all integrations in multi-tenant platforms. Analysis processes look at how similar integrations have handled certain steps or are constructed overall, elucidated by the context of what the user is trying to accomplish. Equally helpful, interactive assistance tools focus on quickly resolving errors by showing the most likely solutions in order of relevance.

The UI has become an essential element for usability in cloud integration platforms and obviously has inspired a great deal of innovation to benefit all users.

 

The User Experience of Data

In a sense, diverse business roles and different kinds of developers have both been "underserved" by integration solutions. All too often non-IT users are lumped into the single blob of "business users" which is pretty useless for understanding much about who those business users are or how they want to – or even should – use integration solutions. And developers are usually seen primarily as data integration experts, rather than acknowledging the diversity of developer categories that need to create integrations regardless of the extent of their knowledge about integrations.

Diversity of users for cloud integration solutions isn't going away. More roles in organizations want and need to work hands on with data management functions to help generate the datasets that they need for their jobs and their business objectives. So the vendors that step up and deliver what different users require will take cloud integration platforms into the future.

Just like any user experience challenge, the gateways to integration solutions - user interfaces – have to work well for each category of user. So vendors have to understand a lot more about the different kinds of users who want access to integration solutions and about the user experience they should have, to ensure the success of all users. For cloud integration platform vendors, providing outstanding user experiences – for diverse users – is an invaluable differentiator

 

Image source: http://synergy.kuniv.edu/

 

About the author: Julie is an independent consultant and industry analyst for B2B software solutions, providing services to vendors to improve strategies for customers and target markets, products and solutions, and future direction. Julie has expertise in several solution spaces including: data integration and data quality; analytics and BI; business process, workflow and collaboration; digital marketing, WCM and social media; and the pivotal importance of user and customer experiences. Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt For more information: Julie Hunt Consulting – Strategies for B2B Software Solutions: Working from the Customer Perspective

 

Data for Everyone? Self-service Data Integration

Part 4 of a multi-part series on the essential interwoven nature of Business and Modern Data Integration

 

                                                   

 

The notion of self-service data integration has been around for a while, somewhat hand-in-hand with self-service BI – both primarily coming from the perspective of power business users like data and business analysts. But a door also opened for less-technical LOB business users to participate in data integration activities. SaaS and cloud services introduced self-service data integration where SaaS providers or third-party vendors supply wizard-like UIs for basic pre-defined integrations or data synchs between specific applications. This version of self-service DI gained impetus from the Salesforce ecosystem of data integration services, many of which targeted "everyday" business users.

Data Integration as a Service seemed to be a new force for the democratization of data. However, when looking at current modern data integration solutions, it appears that tech-savvy business users are the main focus of self-service DI capabilities. So what has happened to data integration for everyday business users?

 

 

 

 

 

 

 

 

 

 

 

 

 

Data for Everyone?

The democratization of data has a place in Modern Data Integration, as both conceptual and actual future directions for solutions. Such democratization is meant in the context of sharing data more widely throughout the organization, connecting many more people to the data they need (not just upper level executives). Organizations thrive and sustain success with better and faster availability of the right data at the right time.

Democratization of data includes self-service data integration and other data services, such as data preparation, that can give business users more hands-on access to data, frequently without the direct intervention of IT. But it would seem that there is quite a ways to go to actually connect different kinds of business roles to the appropriate self-service data integration tools. There has been way more talk than actual availability of such solutions.

Of course, it will take very sophisticated technology behind the scenes to keep it simple in the UIs that give everyday business users access to data integration capabilities. A lot of work must be done, especially to build in the safeguards to keep less technical business users out of trouble. To ensure that everyday business users do the work correctly and avoid serious missteps, self-service data integration has to be narrowly defined, with guidance at every step.

Cloud data integration and data prep solutions support dynamic data catalogs or libraries that provide "certified" data sets that can work well for self-service DI. The resulting data sets are available to the appropriate user roles, including the less technical. Governance of which roles access what data furthers the democratization of data in a risk-controlled environment. It's important that business and IT teams continuously validate the contents of such data libraries, as many data sources come with a short shelf life of relevance.

 

 

 

 

 

 

 

 

Data Governance for Everyone

Self-service data integration is clearly moving forward, and it must go hand-in-hand with self-service governance. There is real risk associated with self-service DI that must be addressed through centralized IT management and governance, which need to be in place to prevent piecemeal and poorly managed efforts scattered throughout an organization. Cloud-based self-service data integration solutions are well-positioned for governance that maps into overall organizational data governance practices and policies.

But remember: data governance is more business than tech: business people are essential for implementing successful data governance. Once again, the crucial partnership between business and IT is a core piece of data governance to make sure that it will work well and make sense both for business needs and objectives, and IT management of self-service DI activities.

 

Data Prep Solutions – Blazing a Trail for Self-Service DI for 'Everyone'?

Data preparation vendors have very effectively shared studies that highlight the costly nature of getting data ready for use by organizations: identifying the right sources; cleansing and validating data; testing for context and relevance; creating the appropriate integrations. Business and technology teams alike are better understanding why data integration and data preparation matter, and why they must be done well. These are not trivial undertakings, and require sophisticated technologies to produce the usable data sets greatly needed for many business activities.

An extensive array of data preparation technologies have emerged to help connect more business people to the data they require for analytics and BI, seeking to greatly reduce onerous preparation time to generate that data. Data integration and data prep do have intertwined destinies, since the goal of either should be reliable, business-ready data. Data prep draws on data quality processes that are have been very much part of data integration for quite some time, as has data lineage.

It looks like data prep solutions are creating the next level of tools that more quickly achieve reliable data, by utilizing applications of newer technologies like machine learning. Data prep offerings incorporate focused machine learning / algorithmic capabilities to automate more of data testing and quality as well as approaches to data integration.

Obviously a core aspect of data preparation is self-service through SaaS / cloud platforms. The vendors behind these self-service offerings are clearly interested in extending the variety of roles, both business and technical, that can take advantage of data prep platforms. Right now the primary users are very technical DI experts and tech-savvy business analysts. But various vendors are working to include less-technical LOB business roles, as well as LOB developers. And these vendors do seem to understand that different user roles require different UIs, capabilities, guidance and governance, and access to data.

 

Self-Service Options and Modern Data Integration

We are seeing significant changes in integration processes, where data flows from and to anywhere: on-premises, cloud, partner systems, third-party enrichment, and so on. With Modern Data Integration, application and data integration are converging to provide everything organizations need in a comprehensive platform. Ultimately for business needs it's still all about the data.

And it's about more people in the organization gaining faster access to data to help them do their jobs better, with improved effectiveness and innovation for the business. Through cloud-based platforms, self-service options can be available to all kinds of roles in an organization.

Self-service data integration is an important goal or Modern Data Integration. But self-service data integration - and preparation - still has a long road to travel before data can be accessed by "everyone".

 

Image source: linkedin.com

 

About the author: Julie is an independent consultant and industry analyst for B2B software solutions, providing services to vendors to improve strategies for customers and target markets, products and solutions, and future direction. Julie has expertise in several solution spaces including: data integration and data quality; analytics and BI; business process, workflow and collaboration; digital marketing, WCM and social media; and the pivotal importance of user and customer experiences. Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt For more information: Julie Hunt Consulting – Strategies for B2B Software Solutions: Working from the Customer Perspective

The Much-Needed Business Facet for Modern Data Integration

 

Part 3 of a multi-part series on the essential interwoven nature of Business and Modern Data Integration

 

Data integration has always faced complex technical issues. Obviously the technically savvy will always be needed for many aspects of data integration, and require solutions that can handle complex problems. But this approach isn't enough for what businesses need and want today from Modern Data Integration. Making room for business ubiquity – business user participation and input – continues to be a challenge.

SaaS and cloud services are important technologies for modern data integration. SaaS in particular has brought into play ease-of-use and focused workflows to help non-technical users move through pre-built integrations. More vendor solutions are improving user experiences and solution efficiency, for both technical and less-technical users. There is increasing development of streamlined UIs, powered by sophisticated technologies behind the scenes, thus speeding data integration tasks.

There seem to be more discussions addressing business data needs, connecting data integration more directly to desired business outcomes via business processes. Including business users in more areas of data management has seen growth both in "lip service" and actual implementations. For the majority of vendors, a business user remains a tech-savvy power user. So we still have miles to go before business ubiquity in data integration includes more types of business roles.

 

 

The Much-Needed Business Facet of Modern Data Integration

Business ubiquity is not limited to direct participation by business users, but includes the overarching notion of Business informing all activities around data integration functions. This means empowering all sorts of business roles to work in partnership with IT, to inform, validate, and provide context to data integration processes. Business roles can help determine if data integration functions will deliver the right data, and will know where problems are likely to occur.

The Modern Data Integration technology platform should provide access points for business users, as well as templates for practices and processes that help organizations engender useful, dynamic and continuous collaborations between business and IT – and the growing involvement of business roles at many levels. Collaborative approaches are usually iterative and involve processes that are both human-based and technology-based. Modern data integration solutions should include all appropriate collaborative aspects.

 

Modern Data Preparation

We're seeing growing attention on tools that more quickly connect business users to the data they need, without much intervention from IT. Data integration is not an easy-peasy undertaking for anyone. But we can break out components that are more amenable to business user access and participation, such as data preparation. There is real value in moving these tasks from IT to business users who can connect data to business processes, usage realities, professional knowledge, and pertinent requirements.

Self-service data preparation solutions include the integration of disparate data sources. These solutions address all of the functions that make the data business-usable and reliable: profiling or exploring, cleansing (which should follow organizational data quality guidelines), enrichment, and so on.

Business users working with data preparation solutions can achieve greater agility to respond to new data sources, new business initiatives, narrow windows of opportunity, impending competitive threats, and unexpected market changes – all of the realities of fast-changing and highly digital business worlds.

 

Business Use of Data Profiling

Data profiling started off as a technology and methodology for IT use. But data profiling can be an important tool for business users to gain full value from data assets. When given the right tools and practices for data profiling, business users should quickly identify inconsistencies and problems for data, before it is used for reporting and intelligence purposes. It's also a sensible way for business users to understand more about the data they utilize in applications, processes and analytics.

From such "data intelligence", business users can have a greater understanding different data sources to be able to ask the right questions for BI and analytics projects. They'll also know if they have the right data and all of the data that they need to answer their questions.

 

Business Data Libraries for Ready-to-go Data

Data libraries are another aspect of improving business-IT collaboration. Modern data integration solutions are doing a better job of attaining the holy grail of business-ready data: directories or libraries of available data views, particularly the data that results from a variety of integrations. This data could be accessed by IT or business users, with the safety net of role-based constraints built in. Such business data libraries greatly aid reusability, as well as allow business users to utilize the data sets that they need, but may not know how to generate.

 

Modern Data Governance for Data and Application Integration

Today's myriad of data sources, data integration tools and approaches, means that data governance is mission critical to ensuring trustworthy and business-usable data. As data and application integration processes overlap more and more in modern data integration, data governance now must oversee all integration approaches, as a centralized function.

Because of the new world of modern data integration, there is more pressure on data governance functions to accept new realities involving business users and self-serve data solutions. Organizations must establish guidelines and processes to directly manage when it's beneficial for business users to perform data prep or integration – or when then work is best done by technical teams due to complex technical requirements.

 

Modern Data Quality

For modern data integration evolution to work well for business user participation, data quality is paramount. More and more organizations understand that data can be a valuable asset, that intelligence can be derived from a variety of data sources, and that analytics of many kinds can greatly benefit decision making, future direction, competitiveness, and innovation. But many organizations aren't well-prepared to tackle the work that must be done to ensure that data is reliable, timely and relevant.

One reason data management and data quality are so important is that a lot of data that can be useful to the enterprise has a very short shelf life. So business processes and activities must be able to tap into data as soon as possible. But that data is only useful if it has high quality. All of the amazing new technologies of modern data integration solutions will mean nothing if the data is unreliable, and therefore unusable.

 

Business Ubiquity – Organizational Symbiosis

Business users increasingly have the potential to utilize powerful capabilities to explore, manipulate and merge new data sources without IT support. There is obvious advantage to organizations to fully support and empower business users to work more directly in many aspects of data management.

Modern data integration solutions should not only support business ubiquity, but can also benefit from it. Vendors can achieve this by making sure that these solutions:

• Provide natural access points for business users backed by built-in guidance to make sure these users don't misstep
• Document and support collaborative processes between IT and business roles in ways that improve data integrations
• Participate in building a comprehensive plan for business user participation and help execute it
• Trace and monitor metrics that are established to connect data integration processes to business outcomes and impact
• "Know" that technology is only part of what is needed to create, implement and reap value from data integration processes
• Support agile change involving both IT and business roles

 

Image source: theyellowsparrow.com

 

About the author: Julie is an independent consultant and industry analyst for B2B software solutions, providing services to vendors to improve strategies for customers and target markets, products and solutions, and future direction. Julie has expertise in several solution spaces including: data integration and data quality; analytics and BI; business process, workflow and collaboration; digital marketing, WCM and social media; and the pivotal importance of user and customer experiences. Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt For more information: Julie Hunt Consulting – Strategies for B2B Software Solutions: Working from the Customer Perspective

 

Knocking Down Silos: Connecting Technology to Business

 

"Knocking down silos" to ensure the critical role of data strategies and solutions -- from the perspectives of business needs, buyers and users, and software vendors.

 

 

A Passion for Software Technology

I have two great passions when it comes to software technology. My tech career and first source of passion for software began many years ago as a developer in the IT group of Texas Instruments, working on systems that supported the semiconductor division. From the very beginning, end users (or customers) were always in the back of my mind, both for the work I did in software development and for the system user guides that I wrote.

When I did analysis for a new software project, my frame of reference included: is this something that the people who do the work really need? Does it help them in the ways that they want to be helped? Will this improve the overall quality and productivity of work done? And, unlike many at the time, my user manuals were created from the user perspective, in a flow that followed how they would use the application for actual work. It seemed natural to me to connect technology to real business needs, and to people. Still does.

Unfortunately to this day, software vendors and in-house developers often put too much focus on technologies and features, and fail to connect with the right potential customers or users to create solutions that help customers solve their business problems. Software vendors and buyers alike need strategies and expert guidance to optimize today's integrated enterprises: how different software applications fit together, how to evolve practices and processes for users to best take advantage of new technologies – even cultural changes for the internal enterprise.

 

An Equal Passion for Data Applications

My second long-time passion comes from working with a data management software vendor for several years. Obviously data impacts most companies and their systems; functions like data integration and data quality matter a lot for successful outcomes. I'm concerned that many businesses and IT teams still come up short on understanding the importance of connecting data management processes to business needs.

I've worked with other software vendors with offerings for web content management, marketing automation and eLearning, to name a few. These solutions almost always include an increasing number of data-oriented capabilities, including analytics, and metrics.

Data runs through an entire organization and beyond -- connecting employees, customers, partners, systems, processes, actions, and outcomes. Unfortunately silos of all sorts also run through organizations, with horrific consequences for important business initiatives. For business software to work well, it's rarely only about the technology.

 

A Data Story for Digital Marketing: Silos and Integration

Successful digital marketing initiatives with an authentic customer focus are only possible with the substantial aid of sophisticated technologies. But the right technology isn't enough. All sorts of silos and stumbling blocks can plague marketers working with digital marketing. These hurdles mirror company-wide challenges to becoming customer-focused, business-agile and market-savvy. Integrated data management and analytics are crucial but so is the integration of many kinds of silos.

• Silos of information and content, business processes, and corporate functions continue to debilitate many organizations. Digital marketing will not happen if Marketing is a silo. The essentials of digital marketing are cross-team collaboration, bi-directional sharing of data and analytics results, cross-functional customer focus and support, relevant quality content. All of these pieces are needed to continuously update a strong understanding of customers and their journeys – across the organization.  
• Data and analytics are mission critical to everything in digital marketing, for successful outcomes. Data from many sources, inside and outside the firewall, is requisite to create and continuously update a multi-dimensional customer view – as well as analytics for buying trends, future customer behavior, understanding which products and which target markets, and better tracking of different customer journeys.

Data analytics initiatives are no small undertaking, especially since many of the sources and analytics processes don't originate in the Marketing 'silo'. As part of the effort to integrate silos, centralizing analytics can eliminate redundant effort to pull together intelligence to benefit all functions in the company. Centralized customer-focused analytics also contribute greatly to nurturing relevant customer experiences across channels by sharing the right insight with all customer-related functions in the business.

• It's very tempting to focus too much on technology and tactics. While technology is essential to make a lot of digital marketing happen, many marketers find themselves too enamored of the tools, thinking that's all it takes. Outcomes: no strategies, no customer focus, the wrong goals, and the wrong metrics. Often the mechanics of working with the technology pull marketers away from the actual customer experience and how to improve it – which are pivotal elements of digital marketing.

    

The Biggest Silo of Them All

If top management doesn't yet understand who their customers are and why they do or don't buy from the company, then it's crazy to expect marketing to conjure miracles and save the business. Company leaders must build corporate strategies that revolve around customers, delivering what they need and want – and they must pursue marketing as a strategic function. For most businesses, customers drive the sales process -- meaning that an organization will only succeed when marketing is empowered to provide the highly personalized and relevant interactions that help customers want to buy products.

 

Image Source: netsrv-consulting.com

 

About the author: Julie is an independent consultant and industry analyst for B2B software solutions, providing services to vendors to improve strategies for customers and target markets, products and solutions, and future direction. Julie has expertise in several solution spaces including: data integration and data quality; analytics and BI; business process, workflow and collaboration; digital marketing, WCM and social media; and the pivotal importance of user and customer experiences. Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt For more information: Julie Hunt Consulting – Strategies for B2B Software Solutions: Working from the Customer Perspective

 

 

 

Data Connectivity in the Web-Enabled World

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As the use of SaaS and cloud services has grown, the API (Application Programming Interface) has come to the forefront as an important technology component in this web-enabled world. APIs are points of entry or connectivity methods, for integrations between different services, systems or applications. Extensive documentation is made available to assist developers, to quickly and effectively work with an API.

Actually APIs have been around a long time, and have been used in data integration processes when other connectivity was unavailable. Both APIs and data integration have come a long way since then. Pre-built connectors for innumerable data sources and formats comprise 'table stakes' for today's data integration requirements. As such, developers and users can quickly set up API connectivity to simplify the sharing of data between: cloud services and mobile apps, data integration processes and data repositories – and enterprise applications residing anywhere.

 

The Web API Economy

A detrimental side effect of the fast growth of SaaS applications and cloud services has been the propagation of endless data silos in the cloud. Vendors for cloud applications provide APIs to enable users to access that data, which unfortunately results in the propagation of endless proprietary APIs. Mobile apps have added another front for the non-stop creation of APIs. While many APIs are available to third party developers as "open" or public APIs, underneath they are frequently proprietary to each vendor and not necessarily "open source".

Vendors for SaaS and cloud services have been able to find advantage in their APIs, both for their own purposes and to benefit their users, beyond accessing their data. APIs have become an economic factor that is opening the door to third-party innovation and developer communities. When vendors provide APIs, technology partners and other developers can create new applications (data mashups, for example) that extend the value of vendor services. Mobile apps in particular need such mashups to quickly and seamlessly pull in information that often comes from multiple sources.

Vendor companies are taking advantage of the APIs they have created to build their own digital sites, mobile apps and even internal business processes and applications. Slowly tools are appearing that enable business users (with good tech savvy) to work with APIs -- following the lead of emerging self-service options for business users in data integration and analytics. So the API Economy is evolving to help different roles get a lot more from web-enabled applications and services.

 

Web API Management

Numerous software vendors have found opportunities in providing API Management platforms or solutions. At the high level, these solutions support:

• Development, publishing and documentation phases
• Creation of integrations through pre-built connectors
• Various deployment and customer usage activities
• Overall management and monitoring of API events and services
• API life cycle management

The primary customers have been companies that create web APIs, but third-party users and partners also interact through API management platforms. These platforms make APIs available to third parties, through a regulated and secure interface.

 

API Management for All APIs

For all the buzz about the API Economy and extending services, ultimately a lot of the value of APIs is in connecting to, aggregating and integrating data for more innovative business use. What's exciting about the API Economy is that it's making it easier to use APIs, even for less tech-savvy business users. When offerings begin to include access for business users, it means that the tools are more streamlined for in-house developers and third party solution providers – translating into faster time to implementation and more time for innovation.

Somewhat ironically, the developers and third-party users of web APIs are now folding in connectivity to data sources and applications in the "traditional" enterprise tech world as new ways to leverage APIs. The current notion of what's called API Management will likely evolve beyond the initial focus on web APIs and APIs created and maintained by a particular company, to the broader enterprise world of systems.

 

Image source: cedefop

 

This post was brought to you by IBM for MSPs and opinions are my own. To read more on this topic, visit IBM's PivotPoint. Dedicated to providing valuable insight from industry thought leaders, PivotPoint offers expertise to help you develop, differentiate and scale your business.

 

About the author: Julie Hunt understands the overlap and convergence of many business processes and software solutions that once were thought of as "separate" – and how this impacts software Vendors and Buyers, as well as the strategies that enterprises implement for how technology supports the business and its customers. Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt For more information: Julie Hunt Consulting

 

 

 

Interoperating Services are the Heart of Cloud Data Integration

 

Most SaaS offerings started with a business user focus, providing applications that zero in on solving specific business problems. It's become an everyday occurrence for businesses of all sizes to migrate many of their needs to SaaS.

There are also SaaS applications that serve as components of a comprehensive IT landscape. But when we look at creating and maintaining the overall technology infrastructure in an organization, a single SaaS application really isn't able to provide full-on IT services. So IT has been finding more usefulness in the world of cloud services that have their roots in supporting IT and developers. IT is able to take advantage of cloud-based platforms, such Infrastructure as a Service, for core technology tools.

Obviously, in terms of data and technology interoperability, SaaS and cloud services must integrate with the entire IT world, much of which is still on-premises. Business processes and data-flows now run from cloud to on premises and back. Businesses need agile technology tools to handle the increasing hybrid infrastructures of many organizations.

The overlapping of data and application integration has been accelerating, particularly with the growth of cloud-based integration solutions. Out of this convergence has emerged the cloud integration platform iPaaS (Integration Platform as a Service). iPaaS is evolving into a new class of technology that supports hybrid infrastructures, and both business and IT users.

IPaaS has its origins in Data Integration as a Service targeting business users, and in data integration solutions for the proliferating silos of data in the cloud. It has been growing into a platform that also offers services for IT and developers, to more deftly handle multiple integration scenarios. iPaaS often functions as an orchestration hub for complex integration processes. And it is increasingly taking on more "traditional" data integration scenarios.

With iPaaS, business users can handle more of the basic integration tasks through self-service data integration, taking the load from IT and data management teams. And IT is becoming more in tune with the self-service economy, by taking advantage of pre-built, reusable services that speed up the creation of more complex data integration processes. Through a services approach to data and application integration, IT can more quickly keep up with business demands.

For the service economy, iPaaS has to be more than just another development platform for the tech savvy. The ultimate outcome of iPaaS should always be the creation of services – iPaaS itself is a means to an end. The services created contribute to iPaaS serving as an orchestration platform that can accomplish a great deal for organizations:

• Continue to grow the IT-Business partnership by using iPaaS as the means for business users to plan, design and execute integration processes; and by using iPaaS as a collaboration platform for IT and Business to improve any and all integration processes to more quickly meet dynamic business needs
• Utilize iPaaS services to streamline management of integrations and API environments from beginning to end
• Create a single environment where numerous technologies converge and interoperate with centralized management
• Engender the growth of transparency and insight for improved operational intelligence

While iPaaS solutions have evolved tremendously over the past few years, there are still miles to go. Several vendors have realized that with the disparate variety of data and business usage for integrations, critical functions like data quality, data governance and master data management must be added as core services for iPaaS. API management is another critical component, particularly since cloud services have a tight relationship to the development and usage of mobile apps that create and consume large volumes of data.

 

Image source: http://www.wunderground.com/wximage/canon30dguy/19

 

This post was brought to you by IBM for MSPs and opinions are my own. To read more on this topic, visit IBM's PivotPoint. Dedicated to providing valuable insight from industry thought leaders, PivotPoint offers expertise to help you develop, differentiate and scale your business.

 

About the author: Julie Hunt understands the overlap and convergence of many business processes and software solutions that once were thought of as "separate" – and how this impacts software Vendors and Buyers, as well as the strategies that enterprises implement for how technology supports the business and its customers. Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt For more information: Julie Hunt Consulting

 

Developing Mobile Business Apps – Navigating Data and APIs

 

Most organizations are well aware that mobile devices and applications are changing how they do business with customers and partners, and how their employees accomplish their work. Mobile business apps are developed to provide useful services that are designed specifically for mobile devices, focusing only on the most relevant streamlined capabilities. Well-designed apps also reflect an in-depth understanding of how different people use mobile devices.

The effectiveness of business mobile apps is ultimately about connecting users to the information and data that they need anywhere, anytime. Business data is frequently stored on multiple platforms, inside and outside the firewall, with varying levels of security and portability. End-to-end task workflows may even take place on multiple platforms. Savvy organizations are catching on that the mobile revolution cannot be stopped. It's best to proactively work out how to govern the mobile tools of the workforce.

Data management and governance, as well as flexible data integration processes, are key components of acquiring and integrating cloud and mobile data with on-premises data repositories. Data in the cloud has been a significant challenge for a while, with each cloud service providing proprietary APIs as the main means for connecting to data. But data residing on mobile devices introduces a whole new world of challenges, including serious security concerns.

As the use of mobile devices and apps for business activities continues to proliferate and fragment data, the standing of data integration as a mission critical technology escalates. What has changed for data integration solutions is the demand for more ways to create and use integration processes. To meet such demand, data integration platforms not only need to be high performance, they must continue to innovate ways to connect to data where it lives and then perform any number of actions to take data where it is needed.

 

Speeding Mobile App Development: API Management Platforms

Agility, flexibility and rapid development are key attributes for the mobile app creation process. Developers of mobile apps have an increasing number of cloud services and platforms that provide reusable components, including numerous JSON and REST APIs that enable data access, as well as the means for navigating security and authentication policies.

Mobile apps both generate and use APIs. On the generation side, APIs that are not well designed or properly built come with a high cost over long-term usage. On the API usage side, in the past, mobile app developers had to embed numerous SDKs directly into the app, which would require constant care and management. API management and integration platforms have been created specifically for mobile app development to orchestrate and enable data integration needs, so that mobile developers don't have to keep re-inventing the wheel when it comes to API creation and usage. These cloud-based integration management platforms cover many of the services that are needed for well-performing mobile apps. Indeed agile API management has become essential for smoothly-running mobile apps.

 

Governance and Security

As with any data-related functions, working with mobile / cloud data integration and APIs requires comprehensive governance and management, to ensure streamlined usability in mobile apps (or cloud services) while adhering to the overall data governance practices for the organization. If an organization doesn't address API management as a critical component of managing mobile app development and usage, many problems can and will result. Security guidelines are also critical for mobile practices.

Ultimately all data usage must in some way align to centralized management to ensure integrated policies, practices and processes across the organization. While the mobile device may be the activity point, the data used and created is still part of a bigger picture. On the other hand, data management practices and policies have to be balanced with enabling the workforce to make good use of cloud and mobile technologies, to more effectively perform work on behalf of the organization.

 

Image source: thisismoney.co.uk

 

This post was brought to you by IBM for MSPs and opinions are my own. To read more on this topic, visit IBM's PivotPoint. Dedicated to providing valuable insight from industry thought leaders, PivotPoint offers expertise to help you develop, differentiate and scale your business.

 

About the author: Julie Hunt understands the overlap and convergence of many business processes and software solutions that once were thought of as "separate" – and how this impacts software Vendors and Buyers, as well as the strategies that enterprises implement for how technology supports the business and its customers. Julie shares her takes on the software industry via her blog Highly Competitive and on Twitter: @juliebhunt For more information: Julie Hunt Consulting

Data Profiling Services: Putting Business Data to Work

 

 

Image source: itbusiness.ca

 

Within each business there are many people who possess the knowledge of how data needs to be used for business processes and particularly for how the right data can improve business agility, revenue growth and help meet customer expectations. Such employees are invaluable for examining business data: first, to determine its value in context, and second, to understand how it contributes to intelligence being gathered for the organization. The need to analyze data is at the foundation of every effective data management strategy, whether the analysis is handled from the business perspective or the technology side of the equation.

To connect savvy business people to the data they need requires the right technology tools. One tool that is still not easily made available to business users is data profiling. Data profiling is the process of analyzing data to determine things like its structure and meaning. Users set up a variety of methods and processes to reveal patterns of data usage, metadata matches, value completeness, degree of data quality, and so on.

Unfortunately data profiling has primarily been a tool for IT and data management teams working with data repositories and the systems that produce and consume data. But data profiling should be an important tool for business users to gain full value from data assets. Aided by data profiling, business users can quickly identify inconsistencies and problems in the data, before it is used for intelligence and decision-making purposes. They can also continuously learn more about different data sets to understand how such data fits business needs. Until data is understood in relation to various systems and processes, it's not possible to fully and reliably use the right data for the business.

Here's where managed technology services can put an interesting spin on connecting business users to tools like data profiling that have mostly been the domain of IT teams. Providers can package business user access into managed services for data management, to open up easy usage of data profiling for business purposes. In addition, providers that bring a specific industry focus for such managed services create even greater value for the business.

For example, there are services firms that consult with corporate legal departments and offer managed services packages that blend data management expertise with legal and regulatory expertise. Such managed services include pre-built data profiling services for areas such as risk management and eDiscovery for litigation and compliance. Many organizations are overwhelmed by the complexity and volumes of data that must be monitored and assessed, particularly in light of the challenges of meeting compliance and eDiscovery deadlines. Managed services, backed by industry expertise, can provide a sustainable and scalable solution while reducing the demand on internal resources.

But these firms usually provide these services only for IT and data management teams. Such managed services could and should include expanded data profiling packages tailored for business users who are less technical but are business data savvy. Data profiling processes are almost always recurring, to support continuous efforts to gain more value from data and to ensure that data quality is reliable; as such, managed services have a 'natural' fit with the creation of tailored data management services for business users.

 

 

This post was brought to you by IBM for Midsize Business and opinions are my own. To read more on this topic visit IBM's Midsize Insider. Dedicated to providing businesses with expertise, solutions and tools that are specific to small and midsized companies, the Midsize Business program provides businesses with the materials and knowledge they need to become engines of a smarter planet.

 

About the author: Julie Hunt understands the overlap and convergence of many business processes and software solutions that once were thought of as "separate" – and how this impacts software Vendors and Buyers, as well as the strategies that enterprises implement for how technology supports the business and its customers. Julie shares her takes on the software industry via her blog Highly Competitiveand on Twitter: @juliebhunt For more information: Julie Hunt Consulting – Strategies for B2B Software Solutions: Working from the Customer Perspective