Highly Competitive - software industry insights

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

 

Why Modern Data Integration? Core Drivers and Characteristics

 

Part 2 of a multi-part series on the essential interwoven nature of Business and Modern Data Integration

 

From the business perspective, modern data integration has become instrumental simply because a lot of data that can be useful to organizations has a very short shelf life. Business processes, initiatives and other activities must be able to tap into data as soon as possible. Companies need to develop data management strategies that focus on generating business-ready and business-usable data. To do this, organizations need a new mindset where silos of all kinds are broken down, and where business and IT teams continue to grow a collaborative partnership to improve any and all integration processes to more quickly meet dynamic business needs.

For relevance to business needs, modern data integration must ensure business user participation in innumerable data management activities. Line of business teams are the business experts who are vital for revealing key information about data usage, the importance of data to specific business processes, as well as guidelines and thresholds for data quality and remediation. Business users can help to determine the value of source data in context, and to understand how it contributes to intelligence being gathered for the organization.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Drivers of Modern Data Integration

Complex problems confront organizations of all sizes; to solve them, the right technologies must come into play. However, when making technology purchase decisions, more companies now consider the impact on business results. Very few organizations can indulge in "tech for tech's sake".

Until recently, data integration solutions were tools only for tech-savvy teams. With modern data integration, business roles in organizations are taking more proactive participation in making sure that the right technologies are implemented. Vital data and the processes that produce it can better connect to business requirements and objectives. Organizations that recognize - and act on - the strategic value of data, also understand and embrace the need for technologies that get the most out of information and data, with continuous improvement and change.

Another key driver for the emergence of modern data integration is simply the imperative of keeping up with everything data, every day. Data, information and intelligence are the fuel for effective business processes throughout the organization – more of which must be handled in real-time. By considering business processes and business information in alignment to strategies and initiatives, business outcomes are likely to improve.

The need for context also drives modern data integration. The most up-to-date and useful data now comes from many sources, some internal to the enterprise and others from sites all over the digital landscape. For data external to the organization to convey meaning, additional qualification and context must come through connections to data such as master data. Context leads to determining the relevance of data from any source.

 

Core Characteristics

Technology capabilities are part of what defines modern data integration, so it's important to understand key characteristics of a comprehensive platform. Modern data integration characteristics and capabilities should align with both technical and business needs.

• Mandate to keep up with everything data. In this sense, modern data integration technologies, processes and users must be well armed to continuously handle data twists and turns over time. A comprehensive platform is needed to address every business and technical use case related to data assets – and it must be a platform that will continue to evolve and add capabilities.

• A hybrid solution to address any data integration flows. First and foremost the hybrid solution reflects the hybrid infrastructures of most organizations (on-premises and cloud). It also follows both the convergence of data and application integration, and of traditional and cloud-based solutions. This is a further step to eliminate silos for data, business processes and users of data integration.
• A ubiquitous platform: agile, flexible, adaptable, responsive, elastic with universal interoperability, orchestration and connectivity to support any kind of data integration process - anytime, anywhere. Reusability through pre-built components, with categories appropriate for business or technical users.

• Access and support for both business and technical users. Efforts for creating business user access can be applied to simplifying capabilities for technical users. The modern data integration platform should also provide the basis for business-IT collaboration in every sense, to gain expertise from both constituencies for optimal integration processes.
• Services-orientation for reusability. For technical teams, reusable services speed up the creation of more complex data integration processes, and help IT more quickly keep up with business demands. For business users, simpler integrations can quickly be pulled together through wizards.
• Evolved API management. Modern data integration solutions should provide simplified approaches to working with APIs. APIs permeate the digital world (cloud, mobile, web) and the enterprise application world. They drive new ways to access data, to develop apps, and innovate the use of data, including access for third party developer ecosystems, to extend the value of data beyond the organization itself.

• Centralized management for all things data, including data quality, data governance, and master data as critical pieces for modern data integration. These functions also strongly connect to business users, to ensure that the right data in context flows into processes and programs.

 

Modern Data Integration: Differentiating for Business Value

Sophisticated, wide-reaching technologies matter greatly as the basis of a modern data integration platform. But the technology alone does not engender modern data integration. Further definition comes from a solution base that equips organizations to handle any integration scenario and support any business case, where access and capabilities provided to both business and technical constituents take on innumerable data-related tasks. It's a mindset of business and technology teams working together to use data to improve business results and competitive edge.

Ultimately true differentiation centers on the value and benefits delivered to businesses and all users, by taking advantage of modern data integration. Metrics can be put into play to connect modern data integration capabilities and processes to business outcomes; from such metrics certain kinds of business value can be determined. Keep in mind that business value is subjective and different for every organization - and will change over time.

Business should be the heart of modern data integration.

 

 

 

Image source: information-age.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