It’s becoming increasingly clear that possessing big data and extracting value from it are two entirely different things. In discussion with Dataconomy earlier this week, Alpine Data Labs’ CMO Bruno Aziza remarked: “It’s really hard to extract value out of big data today. I think if you look at market research, only 4% of companies get value out of their big data investments.”
There are several speed bumps on the roadmap to becoming a data-driven enterprise; unstructured data, ill-suited data architecture and cost of hiring the right people and owning the right hardware can all inhibit the success of big data initiatives. But which of these factors is the biggest pain point when trying to launch a big data initiative? Let us know what you think below.
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(Image Credit: Quinn Dombrowski)
Furhaad, those are very interesting concerns with big data. With the explosion of big data, companies are faced with data challenges in three different areas. First, you know the type of results you want from your data but it’s computationally difficult to obtain. Second, you know the questions to ask but struggle with the answers and need to do data mining to help find those answers. And third is in the area of data exploration where you need to reveal the unknowns and look through the data for patterns and hidden relationships. The open source HPCC Systems big data processing platform can help companies with these challenges by deriving insights from massive data sets quick and simple. Designed by data scientists, it is a complete integrated solution from data ingestion and data processing to data delivery. Their built-in Machine Learning Library and Matrix processing algorithms can assist with business intelligence and predictive analytics. More athttp://hpccsystems.com