What does the future hold ?
A data virtualisation solution requires frequent reads of source system data to combine data sets and deliver insights , so it is advisable to get such data in a physical space before applying virtualisation .
The accuracy of data is of paramount importance for any analytical system . Poor quality source data if fed directly into reporting would deliver incorrect results so it is imperative that data undergoes a rigorous data quality check before it is made available for consumption through virtualisation .
Complex merging of incremental data is necessary to create a version of facts that delivers insight from old facts in order to derive new facts . Such operations require enormous processing power and memory and these activities are best accomplished by an ETL solution , rather than data virtualisation .
What does the future hold ?
As data virtualisation comes of age , it is going a long way to solving the problem of today ’ s proliferation of data . By providing organisations with the ability to combine data from a variety of disparate data sources into a common format , it not only addresses problems of data compatibility and volume but also eliminates issues relating to expertise in specific programming languages .
Data virtualisation is a formidable ally and will deliver faster ROI and agility in decision-making based on actionable insights . As an alternative to big bang Data Warehouse solutions , data virtualisation offers a lightweight , cost-effective solution in a rapidly changing market place that enables businesses to remain competitive in their sector .
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