The term “big data” has arisen in recent years to describe multi-terabyte datasets. Big data certainly has its challenges, relative to scalability and data management. But it’s also useful for business intelligence purposes. In particular, the massive datasets of big data provide substantial data samples for various forms of analytics, especially advanced forms that are discovery oriented.
In a related trend, many organizations are stepping up their use of analytics, as a way of understanding a relentlessly changing business and economic environment. Whether you’re trying to discover the root cause of the latest customer churn or the hidden costs that are eroding the bottom line, you need discovery oriented analytic tools and techniques that work well with big data. That’s why big data and analytics have come together in recent years, thereby causing substantial changes in tools and best practices for analytics.
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