Arun Gupta is a professional writer for an Offshore Software Development Indian IT company offering customized solutions including Application Testing, Business Integration & Data Warehousing (BI & DW) and Infrastructure Management Services for clients around the world.
Hundreds of major companies around the world use data warehousing solutions to get a single, integrated view of their business to enhance decision-making, customer relationships, and profitability. Given the prominent role it plays in its customers’ businesses, the reliability and security of its software is truly mission-critical. The need of the hour is a relational database management system that is linearly and predictably scalable in all dimensions of a database system workload (data volume, breadth, number of users, and complexity of queries), explaining its popularity for large enterprise data warehouse applications.
If there is a single pitfall that undermines any given data management initiative, it is most likely to be found in the realm of data quality, which is a requirement for sound decision-making. Whether in combination or by themselves, databases are almost certain to contain entry errors, multiple common entries and other redundancies that inevitably lead to incorrect or incomplete identifications of customers, products and locations. Thus, data quality is a critical prerequisite to any BI initiative that would otherwise skew or obfuscate meaning in the reporting and analytic outputs of databases, reporting tools, dashboards and scorecards. When people talk about an enterprise data warehousing, they certainly understand the concept of everyone in the enterprise should be able to access all the data in the enterprise.
When you work within the data warehousing arena, what most people start off with is trying to generate reports for their end-user community. This seems fairly easy if one can take the data, format it and push an answer set to the end-user, to an Excel sheet, or to a prepackaged paper packet or a computer. So, essentially the data is being pushed out to where it’s being used. What’s most effective is when people can take their questions and bring them to where the data is. So, rather than moving data, processes are being moved. Because moving data costs a lot of money, takes a lot of time, adds a level of security breach apart from creating confusion. Hence it’s always better to bring the data together once, and allow people to access that data with their processors.
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