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Reducing Business Risk with Data Integration

A study by Bloor Research put the failure rate for data migration projects at 38%. When you consider that a failed data migration project can temporarily hold up vital business processes, this becomes even more bad news.  This affects customer service, internal business processes, productivity, etc., leading to an IT infrastructure that is just not meeting the expectations of the business.

If you own one of these dysfunctional IT infrastructures, you’re not alone.  Most enterprises struggle with the ability to manage the use of data within the business.  Data integration becomes an ad hoc concept that is solved when needed using whatever works at the time.  Moreover, the ability to manage migration and data quality becomes a lost art, and many users distrust the information coming from business systems they should rely upon.

The solution to this problem is complex.  There needs to be a systemic approach to data integration that is led by key stakeholders.  Several business objectives should be set prior to creating a strategy, approach, and purchasing key technologies.  This includes:

  • Define the cost of risk in having substandard data quality.
  • Define the cost of risk in not having data available to systems and humans in the business.
  • Define the cost of lost strategic opportunities, such as moving into a new product line or acquiring a company.

The idea is that, by leveraging data integration approaches and technology, we’ll reduce much of the risk, which actually has a cost.

The risk of data quality is obvious to those inside and out of IT, but the damage that could occur when not having a good data integration and data quality strategy and supporting technology is perhaps much farther reaching that many think.  The trick is to solve both problems at the same time, leveraging data integration technology that can deal with data quality issues as well.

Not having data available to both end users who need to see it to operate the business, as well as to machines that need to respond to changing data, adds to the risk and thus the cost.  In many enterprises, there is a culture of what I call “data starvation.”  This means it’s just accepted that you can’t track orders with accurate data, you can’t pull up current customer sales information, and this is just the way things are.  This is really an easy fix these days, and one dollar invested in creating a strategy or purchasing and implementing technology will come back to the business twenty fold, at least.

Finally, define the cost of lost strategic opportunities.  This is a risk that many companies pay for, but it’s complex and difficult to define.  This means that the inability to get the systems communicating and sharing data around a merger, for example, means that the enterprises can’t easily take advantage of market opportunities.

I don’t know how many times I’ve heard of enterprises failing at their attempts to merge two businesses because IT could not figure out how to the make the systems work and play well together.  As with the other two risks, a manageable investment of time and money will remove this risk and thus the cost of the risk.

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One Response to Reducing Business Risk with Data Integration

  1. Businesses today are set up to manage Risk. Data or poor quality data or lack of access drives up that Risk. Data Integration is a key component of your data analytics infrastructure that does not get as much attention as it should. It is not easy. At least, we can strive to make data integration flexible so that it can handle needs of today but also be able to handle unknown/unstructured data of tomorrow. This is where we need a “Hybrid Data Integration” model that combines the best of Hadoop and traditional BI.

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