Today’s business environment is defined by agility. The company that can innovate faster, react more quickly to changing end-customer preferences, and identify and pursue new revenue opportunities ahead of its peers, has a distinct competitive advantage.
In order to achieve that agility, businesses require a real-time stream of high-quality data analytics. The reality – and the problem – however is that data-driven business intelligence initiatives very often take weeks or months of data preparation before a question can be asked. Lines of businesses today do not have the luxury of that time. They need answers yesterday.
The fundamental reason why business intelligence (BI) queries take so long to complete is the process of data qualification. Data is no longer being generated by a small number of sources or being stored in a single location. The roster of database and data warehousing tools being used by lines of business is larger than ever before, and it is frequently changing. At the same time, data is being stored across a wide variety of storage infrastructure resources, on-premises and in the cloud.
Against this backdrop, obtaining visibility into data context – what data is available to address the query, and how that data needs to be prepped and assembled to meet that query – is a very lengthy and cumbersome process. This fact not only vastly extends the time it takes to process the BI query, but it also adds risk. Relevant data may be left out, and the business may be missing opportunities because it does not have full visibility into all of the questions that its data can answer.
Making the best data-driven business decisions possible clearly requires a new approach. It requires holistic visibility across all data sources, as well as the ability to map that data to the BI query at hand. Once that data has been identified, a streamlined path to assembling that data across the team of data scientists and other individuals that are working on the query, is also needed.
Watch our on demand webinar “The Top Four Challenges of Data Analytics and How to Solve Them”. Subject matter experts from Storage Switzerland and Promethium will discuss these challenges and how new methods and technologies can dramatically reduce the pain and cost of your analytics querying time.
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