This post is a collaboration between Novetta and O’Reilly. It was originally published by Andy Oram, Editor at O’Reilly Radar. We often talk in business and computing about moving from “raw data” to “knowledge,” hoping to take useful actions based on the data our organization has collected over time. Before one can view trends in your data or do other analytics, you need tools for data cleaning and for combining multiple data sources into meaningful collections of information, known as entities. An entity may be a customer, a product, a point of sale, an incident being investigated by the police, or anything else around which you want to build meaningful context. In this post, we’ll explore some of the complexities in real-life data that create headaches — and how analytical software can help users prepare data for sophisticated queries and visualizations.
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