Newsletters




Winning the Big Data Game


Bookmark and Share

As big data continues to explode, companies are exploring how they can leverage it for competitive advantage - to help them prepare for emerging trends within their industries, perform advanced analytics of data to help increase revenue and optimize processes or avoid potential pitfalls. As they do so, it is important to understand how analytics solutions can help.

A recent DBTA webcast highlighted the key considerations for selecting analytics tools and explored examples of how analytics are used in different industries. The webcast was presented by Dr. Thomas Hill, executive director for analytics at Dell's Information Management Group; and Marcia A. Kaufman, principal analyst and COO, Hurwitz & Associates.

An index provided by Hurwitz & Associates aims to assess the performance of big data analytics vendors across four dimensions – vision, visibility, validity, and value. According to a report issued by Hurwitz that looked at 10 vendors, organizations are analyzing larger and more diverse sources of data, and they are using advanced analytics to adjust business strategies and reduce risks. “Overall, customers really like the statistical vendor that they are working with,” stated Marcia A. Kaufman, principal analyst and COO of Hurwitz.

Given the speed and velocity at which big data moves, customers are concerned with their platforms’ ability to incorporate the data in real time and the amounts of data that can be analyzed. Only 45% of the organizations in the report rated their analytics platforms as excellent for business users, while 60% rate it excellent for data scientists. Customers are placing more weight on new algorithm development and new analytic techniques.

A key concern was the ability to find tools that work for business users. Data scientists are in short supply so organizations want software that is simple enough to enable business users to benefit from it. In addition, visualization capabilities are important to businesses they provide a bridge by which data scientists can connect with business users and explain the data. “At the end of the day, you need to have an interface for the business user that quickly translates the information from the data into something actionable,” said Hill. 

To view the webcast, go here


Sponsors