The phrase “With Big Data, comes Big Responsibility” is not uncommon to many professionals. But what happens when we add Simple, Diversified, and Complex data to that mix?
BrightTALK Community Manager Ina Yulo interviews Jeremy Sokolic from business analytics company Sisense to get his thoughts on the challenges commonly faced by data professionals and some tips to overcome them.
Could you explain what the data complexity matrix is and what some of its key advantages are?
The Data Complexity Matrix is a framework that helps business and IT professionals better understand there data sets and determine the optimal tools that could be used in a business analytics program.
Has Big Data become a Big problem? Could you share some of your top tips for dealing with these challenges?
Turning big data into something actionable has become a challenge. ?My biggest tip would be to aim for consolidation of the tools and systems used to analyze and manage large data sets.
Today, many businesses are forced to combine multiple tools together to analyze big data. The problem is using too many tools creates an enormous overhead to implement, maintain and integrate. The best solution is to use the least possible number of tools, or ideally a single end to end solution which often is the fastest path to take big data to insights.
What are the common mistakes professionals make regarding Big Data?
At times, professionals focus just on a specific large data set, without thinking through all the additional data sources that may be necessary to derive answers to specific business questions. Realizing that the real value, often comes in combining different data sets and types of data, professionals should aim to create an analytic environment that is not solely about big data, but one that enables business users to work with varied data sources as a coherent whole so that they can answer business questions.
When it comes to data management, how do challenges faced by IT users differ from the obstacles regular business users face?
?The biggest challenge for business users is their inability to analyze all the data they want, in the way they want without having to turn to IT. For IT the biggest struggle is data preparation and dealing with the challenges of continually keeping big data sets tuned for fast analysis.
Could you give a brief summary of your upcoming webinar and what the audience can expect to learn from it?
We will explore the characteristics of four different types of data: Simple, Diversified, Big, and Complex; We will also help end users understand what kind of data they have and what the implications are when choosing a data appropriate business analytics tool.
Jeremy’s webinar is live on November 4th at 3 p.m. GMT/ 4 p.m. CET and available after on-demand. Register here.