Forget spreadsheets. Organizations that are winning in this down economy are using automated analytical tools to take a more scientific approach to decision making through observation, experimentation and measurement to improve their business processes.
This paper will outline the value and methods involved in data mining across both quantitative and qualitative data. In addition, it will describe the data transformations necessary before doing such work, and the tools that are particularly valuable for mining mixed data types.
Published By: Datawatch
Published Date: Mar 21, 2014
Big Data is not a new problem. Companies have always stored large amounts of data—structured like databases, unstructured like documents—in multiple repositories across the enterprise. The most important aspect of big data is not how big it is, or where it should be stored, or how it should be accessed. It’s the efficacy of business intelligence tools to plumb its depths for patterns and trends, to derive insight from it that will give companies competitive advantage in an increasingly challenging business climate. Visualization allows companies to analyze big data in real-time across a variety of sources in order to make better business decisions.