Data Integration is old news!!


This may be controversial coming from someone that has worked with data his entire career, someone that has been involved with software vendors focused on data integration and access for the last 6 years, and someone that is responsible for product marketing for SAS data management capability, but I’ll say it anyway… “Data Integration is just not that interesting”.

While there have been many good developments relating to data integration…

  • Moving from silo’d data integration capabilities to a unified platform that includes data integration, data quality, MDM, data governance features, etc.
  • Introduction of ELT as a mechanism to better leverage the database capabilities.
  • Expansion of data integration methods to include virtualization, event processing, etc.
  • Products that integrate cloud and on-premise resources.
  • Etc….

I find it much more interesting to consider the strategic value of information while encouraging organizations to implement strategies, capabilities and processes necessary to manage information as a strategic asset. Just as organizations moved from a data integration to a data management mindset, it’s now important to consider a more strategic, information management approach.

While I plan to address information management as a critical topic over the next several months, I thought I’d start by identifying key information management considerations.

Data Challenges

  • It’s about pulling together fragmented data both inside and outside the enterprise, managing it properly and turning that data into valuable information that drives insightful decision making.
  • It’s about supporting data at rest and data in motion. This includes leveraging massively scalable capabilities that can process or analyze ALL available data to the nth degree of detail AND it’s about applying information and analytic services to data that is streaming through. This provides you the ability to derive value from the information earlier and it provides you the ability to determine how to best process or store information based on organizational relevance.

Leveraging Analytics

  • It’s about turning traditional data preparation for analytics on its head so that you not only leverage data management capabilities to prepare data for analytics, you apply analytics to the data management process itself. Just as you apply analytics to a business process like marketing campaign management, you should apply analytics to the data management process.
  • It’s about leveraging new sources of information or existing sources of information that have not been utilized due to complexity, cost, etc. It’s using these data sources to complement the traditional sources of transactional data to provide additional insight or context to produce rich information to drive effective decisions.
  • It’s about IT developing a basic understanding of analytics, starting with understanding the various data requirements that relate to the various analytic disciplines.
  • It’s about IT understanding the overall analytics lifecycle – from data preparation, to model development / testing to model deployment – and building the right infrastructure to operationalize this lifecycle with the same level of discipline that is applied to the operational application development lifecycle.
  • It’s about IT working in concert with the data scientist / statistician community so that they can offload as much of the data preparation work as possible from these scarce resources.

Collaboration & Governance

  • It’s about driving real collaboration between business and IT, and recognizing that collaboration is the key to unlocking business value from data. This collaboration comes in the form of information governance and in the form of managing the process steps involved in the entire information continuum.

Comprehensive Approach

  • It’s about taking a look at your information comprehensively, including the capabilities, strategies and processes involved not only in data management, but analytics and decisioning, something we refer to as analytic management and decision services respectively.
  • It’s about taking a holistic approach, one that is not just focused on product capabilities and tools but an approach that encompasses best practices in the form of information management strategy and implementation services.
  • It’s about taking an enterprise approach. Just as most organizations have moved to an enterprise architecture approach for developing applications, organizations need to consider information management from an enterprise perspective. This doesn’t imply that you have to take a big bang implementation approach, but your overall design approach should be comprehensive.
  • It’s about leveraging a comprehensive approach that includes business rule capabilities that can complement the logic that is inherent in an analytical model or embedded within rich information services.

Architecture Considerations

  • It’s about leveraging all of the available technologies at your disposal while ensuring the correct mix of said technologies. For example, on the data management side, it involves leveraging an infrastructure that provides flexible deployment capabilities that span all of your data management needs including, data integration, data quality, enterprise data access, MDM, etc. It’s about leveraging the correct mix of deployment options from on-premise to appliance to the Cloud.
  • It’s about leveraging a variety of technologies to manage data and information vs. a one size fits all approach. This is necessary to support the diversity of requirements that face organizations today from temporal requirements (real-time vs. batch), to multiple consumption approaches (mobile to web), to the diversity of data (social to transactional), etc. These various factors drive the need for a comprehensive information management approach that supports the right mix of technologies, including the proper mix of data storage approaches, analytic modeling types, data integration styles, etc.
  • It’s about treating the cloud comprehensively, it’s not just public cloud SaaS, it’s leveraging Cloud concepts to drive your internal architecture, it’s about determining the correct mix of on-premise and cloud capabilities, it’s about understanding the entire cloud infrastructure, from public cloud SaaS, public cloud PaaS, to public cloud IaaS, etc. And finally, it’s about leveraging an information management approach that supports private or hybrid cloud deployments.
  • It’s about complementing your existing capabilities and investments by augmenting your current infrastructure and processes with a design and capabilities that will help you transition to a more strategic information management approach.
  • It’s about designing an infrastructure that not only supports diverse and distributed internal constituents but provides support for your entire partner ecosystem.
  • It’s about supporting multiple forms of consumption vs. delivering reports to a user sitting at a PC. It’s about leveraging a rich analytic and information services infrastructure that supports all forms of devices (smart phones, tablets), it’s about embedding these services within devices (network and medical devices), and within applications such as call center applications, financial applications, etc.
  • It’s about driving the convergence of process and information. Business applications are increasingly being developed using a service oriented approach where the application is constructed using a set of composite services. In most cases the application consists of presentation logic and business logic that effectively provide a window into the data (and in most cases the ability to create, read, update and delete the data). To think of the process and data as separate camps creates a divide that complicates the IT development process and leads to business inefficiencies.

CIO/IT Strategy

  • It’s about IT over-delivering on their basic KLTO (Keep the Lights On) responsibilities in a cost and resource effective manner so that IT has the bandwidth to focus on initiatives that drive real business impact.
  • It’s about working with a trusted partner ecosystem that not only helps you design and implement a flexible information management strategy for your current requirements, but helps you stay on top of new technologies and strategies that are constantly emerging.

Business Value

  • And finally, it’s about driving game changing business value based on solid ROI. Treating information as a strategic asset that facilitates superior decisions that can be made within your competitor’s decision cycle, driving game changing business impact.



About Author

Mark Troester

IT / CIO Thought Leader & Strategist

Mark Troester is the IT / CIO Thought Leader & Strategist for SAS. He oversees the company’s market strategy efforts for information management and for the overall CIO and IT vision. He began his career in IT and has worked in product management and product marketing for a number of Silicon Valley start-ups and established software companies. Twitter @mtroester


  1. Felix Liao

    Couldn't agree with Mark more! Data Integration has never been all that exciting and interesting, I even wrote a post on the similarity between Data Integration/Data Management and plumbing!

    Whilst plumbing or data integration is not all that interesting or exciting (or visible for that matter!). In order to build a great house or undertake some of the strategic initiatives Mark mentioned above, it is absolutely critical to get the plumbing or data management foundation right!

  2. Pingback: “Outdated Data Management” & the 21st Century - Information Architect

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