Tag Archives: Ovum

Ballooning Data Sets Cause Application Performance Problems

According to a 2011 Ovum survey, 85% of respondents cited ballooning data sets as the cause of application performance problems. Many IT organizations fell short in 2012 letting unmanaged data growth impact the business. This year, Informatica is witnessing a surge of interest in Enterprise Data Archive solutions. This interest is being created because executives want to invest in innovative technologies for real-time and operational analytics. Yet, with little to no IT budget increase, IT leaders are getting creative.

Businesses are moving from on premises applications to Software as a Service (SaaS) freeing up time and resources – yet the legacy application being replaced all too often stays in the data center consuming costly resources. IT leaders are recognizing the quick win of retiring legacy applications. An application retirement strategy supports data center consolidation and application modernization initiatives – while ensuring data is retained to meet regulatory compliance and business needs. Significant cost savings are realized because mainframe systems can be turned off, maintenance costs go away. With this new source of revenue, executives can fund their analytics projects and drive competitive operations. (more…)

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Posted in Application ILM, Application Retirement, Data Archiving, SaaS | Tagged , , | Leave a comment

Data is the Answer, Now What’s the Question? Hint: It’s The Key to Optimizing Enterprise Applications

Data quality improvement isn’t really anything new; it’s been around for some time now.  Fundamentally the goal of cleansing, standardizing and enriching enterprise data through data quality processes remains the same.  What’s different now, however, is that in an increasingly competitive marketplace and in difficult economic times, a complete enterprise data quality management approach can separate the leaders from the laggards.  With a sound approach to enterprise data quality management, organizations reap the benefits of turning enterprise data into a key strategic asset. This helps to increase revenue, eliminate costs and reduce risks.  Using the right solution, organizations can leverage data in a way never possible before, holistically and proactively, by addressing data quality issues when and where they arise.  Doing so ensures key IT initiatives, like business intelligence, master data management, and enterprise applications, deliver on their promises of better business results. (more…)

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Posted in Data Quality, Master Data Management, Profiling | Tagged , , , , | Leave a comment

In Turbulent Times, It Pays to See Information as It Happens

Real-time and near real-time capabilities have been the watchwords of the industry for about a decade now, but only recently have we seen a convergence of the technology and methodologies – such as data warehousing and data integration platforms – that make it an affordable reality for most companies.

The drive to real-time was highlighted in a recent InformationWeek report, which says that manufacturers and retailers lead the way in using up-to-the-minute point-of-sale data to avoid stock-outs and overproduction.

The InformationWeek article points to the challenges manufacturers and retailers face in demand forecasting, in which manufacturers analyze weekly and even daily point-of-sale data from retailers so that they can better see what’s selling and where. Retailers have had a tough time predicting demand in today’s turbulent economy. (more…)

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Posted in Business Impact / Benefits, Data Integration, Data Warehousing, Enterprise Data Management, Operational Efficiency, Real-Time | Tagged , , , , | Leave a comment

How About a ‘Service Oriented Architecture’ for Data?

The principles of service oriented architecture (SOA) show a lot of promise for building greater agility and integration into applications. So why not extend these capabilities to the data integration world as well? With initiatives such as data warehousing and master data management (MDM) coming to the fore, data integration needs to be addressed on an enterprise scale.

Madan Sheina, principal analyst within Ovum’s Software Applications group, proposes that a data architecture be designed along the same lines as SOA for applications – in what he calls process-driven data integration. (more…)

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Posted in Data Integration, Data Services, Data Warehousing, Enterprise Data Management | Tagged , | 1 Comment