5 Requirements for Effective Self-Service Data Preparation

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Multi-Structured and Streaming Data

Anyone can easily connect to relational data, CSV and other standard-structured data. But often the data that provides the most analytical value is locked away in multi-structured or unstructured documents, and it seems impossible to use this information without rekeying the data.

Analysts must be able to quickly and easily acquire any data at any speed, including information from multi-structured sources, such as PDFs, text reports and web pages, as well as real-time streaming data. Self-service data prep technology can play a pivotal role in this endeavor by extracting, cleansing, preparing and blending this otherwise unworkable data into high-value information for solving business problems. And, as a result, data experts can spend the majority of their time on analysis – not data prep.

Business Intelligence (BI) and Big Data analytics tools have fundamentally transformed the way organizations operate. Business leaders across industries now use Big Data analytics technology for a wide range of processes, objectives and management needs. And the potential applications of modern BI tools are practically endless, as virtually every aspect of operational management and strategic oversight can benefit from more powerful and rapid insights.

But while the technology is there, studies have shown that return on investment (ROI) has been elusive at best for the vast majority of adopters. In fact, business analysts claim that 80 percent of their time is spent preparing data for analysis, and they still never seem to have the information they need.

Self-service data preparation (prep) is a critical, yet often overlooked, factor in the analytics process. In this slideshow, Datawatch Corp, has identified five essential self-service data prep capabilities every analyst must be able to access to derive maximum value from analytics solutions and help their organizations make more meaningful and timely decisions.


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