Big data analytics is the process of examining various legacy data to identify common or discrete patterns, data correlations and other useful information that can be used to make a better decisions. With big data analytics, data scientists and business analyst can analyze huge volumes of data from various database or data systems that conventional analytics and business intelligence solutions cannot produce. Various Consider that your organization could accumulate (if it hasn’t already) billions of rows of data with hundreds of millions of data combinations in multiple data stores and abundant formats. High-performance analytics is necessary to process that much data in order to figure out what’s important and what isn’t.
Historically Business houses collected and stored terabytes of data but never been able to analyze and make meaningful use of the data for decision making preocess in full context. Else they have to wait hours or days to get some metrics ?
With new advances in computing technology, there’s no need to avoid tackling even the most challenging business problems. For simpler and faster processing of only relevant data, you can use high-performance analytics. Using high-performance data mining, predictive analytics, text mining, forecasting and optimization on big data enables you to continuously drive innovation and make the best possible decisions. In addition, organizations are discovering that the unique properties of machine learning are ideally suited to addressing their fast-paced big data needs in new ways.