Three Ways to Connect Data Integration to Business Strategy

Loraine Lawson

In this week's ebizQ column, David Linthicum makes a strong case for why data integration should be a top priority for businesses. After all, he explains, those who neglect data and integration with other systems "are going to find the bitter truth at some point," and that bitter truth is bad data, expensive repairs, and lost faith in IT.


Then he asked a question that's been bugging me all week: How do you make data integration a priority?


For those of you unfamiliar with Linthicum, he's the CTO of Bick Group, but he's also a well-known SOA writer and speaker who's branching into cloud issues. Before SOA, his focus was (and arguably still is) distributed computing and application integration; he often tackles data issues as well.


Those of you who are familiar with Linthicum will know he doesn't ask a question like that without answering it.


"It's really a matter of just looking at the business benefits, and thus the business case for data integration," he writes. "Without a sound data integration strategy you're simply not going to be able to meet the requirements of the business, and can't get more clear than that. Moreover, you need to consider data integration as something that's systemic to your architecture, and not just an afterthought."


To me, that actually answers the why more than the how. How do you go about finding the business case for data integration? And how do you ensure data integration becomes and remains a priority?


So, I did a bit of digging and I've found a few items that might help you identify the business case and institutionalize data integration as a strategic discipline.


As luck would have it, John Schmidt of Informatica recently launched a blog series on data as an asset. In his first post, he writes about the pros and cons of viewing data as an asset. I particularly appreciated his point that if it's not an asset, it's measured as a cost-and you know what happens to cost centers in tough times.


But for my money, the really good stuff is in the next three posts, starting with the second post, in which he explains accounting methods for determining an asset's value and applies those concepts to data. In the third post, he outlines how to calculate the EVA (Economic Value Add) for data. If that doesn't work out for you, in the most recent post, he explores a market-based approach to valuing data.


Schmidt's series will go a long way toward helping you attach value and thus build a business case for data initiatives.


Now-how to institutionalize data integration as a strategic process?


There are several good answers to this question. First, as I've shared many times, there's the old standby, the Integration Competency Center. If your problem is more about overcoming corporate politics and rallying support than organizing change, then I recommend you check out Rick Sherman's suggestions on creating support for holistic data integration.


But I'm actually most excited about a third possible answer that's just emerging on the horizon: the technology solution. I know, I know - tools are never a replacement for strategy. But hear me out. There's already a trend for business analysts to handle more integration. Not surprisingly, data management vendors have noticed this trend - in fact, I've talked with several vendors who say they now have to talk to the business and IT if they want to sell a solution.


Their products are starting to reflect and support this shift, and I think it's a promising development in terms of making data integration a strategic priority. For instance, Informatica recently rolled out Informatica 9, and one of the key selling points is that it's designed for both business analysts and IT.


And just this afternoon, I learned that DataFlux plans to unveil next week a new data management platform, with support for data governance, integration, data services and master data management-and it's designed to be used by business analysts and IT.


Increasingly, data management tools are marrying all the elements of data-integration, governance and quality-into one, business-friendly package. Perhaps in this case, the tools will soon help solve the challenge of data integration by strategy, rather than happenstance.

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Feb 18, 2010 2:24 PM Francis Carden Francis Carden  says:

For the sake of it, I'm going to take a different slant here.

Why has no one asked - WHY? Why do we STILL have this problem in 2010. It's not like it's a new problem and despite all we write, people still don't seem to be able to come up with a real solution to make the problem go away. Sure, they are great tools out there that HELP a lot but why are we even here? Why do we keep recreating the problem?

I am going to have a very small attempt to explain just a small bit of the why, from my "integration" and "application" development world. To me, it boils down to the business logic. ALways has and always will be until we invent a new paradigm. Business Logic is the achilles heel for data resulting in next gen legacy systems (LOL). Since I've been in IT, we write an application, apply business logic and store the resultant data. The data without the business logic is often useless. Would you risk reading a value from a database and assume it's the correct "Balance". Maybe someone has added a new field linked to a piece of data somewhere else and now that data  must be added (or subtracted or some other complex mathematical formula) before being presented to a user, used in a report or whatever.

You see, we can throw all of the tools and all of the new technology at the problem but until we start treating data again as business logic and treat business logic as the fundamental part of the integration process, we will go around and around in circles. Some of the early 4GL's attempted to solve this but thanks to the viral spread of data this faded away. I am not sure the problem will ever go away until we invent some new way for data to be...... say.... intelligent.

In the mean time, I will continue to help my customers, with their 5, 20, 50 or 500 desktop applications get joined at the hip. This is where the "real" data is "viewed" post business logic and can be "integrated" with little to no risk of missing a vital piece of the Business logic.

Feb 22, 2010 1:06 PM Dave Schiller Dave Schiller  says:

Thanks, Loraine, for addressing one of the pillars of data management that doesn't always get the attention it deserves.  At Teradata, we've seen firsthand how the continued exponential growth of data within companies provides new and exciting opportunities, but only if companies have the right tools and processes in place to make sense of the information.  Data is certainly a unique corporate asset and should be managed as such, so integration needs to be a top priority in terms of your overall business strategy. 

For the IT staff, integration decreases data redundancy and data movement, promotes higher reusability of application code and toolsets, and enables faster time-to-development when new user requests come into the queue.  For executives and managers, integration means stronger accountability and trust in the information that drives both strategy and tactics.  But, most importantly, knowledge workers can make business decisions, knowing that the data on which these decisions hinge is trusted and integrated.  Simply stated, better data integration provides better business analytics and efficiency.

To get the most bang for your buck, it's crucial to choose a solution that can avoid data duplication and redundancy costs while allowing users to make faster, smarter business decisions.  Our active business intelligence allows companies to make sense of these massive quantities of both unstructured and structured data, finding non-relational insights that would otherwise be missed.  This can only be done with proper data integration and data management processes.

Dave Schiller

Teradata Corporation

Services Marketing Program Manager

Feb 25, 2010 3:08 PM Frank Millar Frank Millar  says:

To those who've seen my previous posts, this'll not be surprising:

The top-down perspective provided by the enterprise architecture dictates that data integration must be done.


No special rationalizing needed.

Frank Millar

Executive Director

Millar Consultants, LLC

Feb 26, 2010 9:37 AM Ekta Ekta  says: in response to Dave Schiller

It seems that more and more enterprises nowadays are relying on real-time operational data found in systems. Data is simply data, and its everywhere, but on its own it is no more than just information waiting to be used. Much has been written about the need for better quality data, less redundant data, disparate data and more easily accessible data.

Having said that, there is another fact that trumps them all-how is the data being is used. It behooves us to make the best use of the data we work so hard to collect and protect.


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