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April 24, 2009

Cutting Costs through Data Integaration Tools Rationalization

Filed under: Data Integration, Data Quality — Tags: , — Olga Belokurskaya @ 4:29 am

Gartner on cost-cutting bent again! According their latest press-release, rationalizing data integration tools can save companies more than $500,000 annually. Moreover, they suggest adopting a shared-services model in the longer term.

It’s a fact that most companies often purchase and implement new data integration tools in a fragmented way without considering extending investments already made in other parts of the business.  This results in multiple tools from different vendors and consequently – loads of money on licensing and maintenance.

Taking into account today’s organizations’ and industries’ focus on cost optimization (cost cutting, to be exact), fragmented approach to data integration should be reviewed in order to increase efficiency and reduce expenses.

Here what Ted Friedman, Gartner distinguished expert says:

The first step is for IT teams focused on data integration to save money by rationalizing tools. Further, there is a greater longer-term opportunity to substantially reduce costs and increase efficiency and quality by moving to a shared-services model for the associated skills and computing infrastructure.

Gartner recommends three elements executed to realize this first step:

  • Planners should rationalize across the three main categories of data integration tools: extraction, transformation and loading (ETL); data replication; and data federation, ideally arriving at a standard tool for each of these styles of data delivery. They should decide which tools to keep and which to discontinue based on the business context and requirements, rather than blindly rationalizing wherever possible based purely on cost.
  • Centralize Data Integration Computing Infrastructure to avoid redundant servers and storage caused by deployment of each tool on dedicated hardware. Many organizations can make substantial savings on computing capacity by implementing shared computing infrastructure for data integration workload.
  • Gartner recommends that organizations centralize data integration roles and skills into a shared services team model to reduce staffing costs directly by 50 per cent or more each year.

In conclusion, Ted Friedman stresses that rationalization should not be limited to one business unit, and that CIOs and data integration teams should work together to lead the rationalization and shared-services program.

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