7 Steps to Virtualized Data Preparation
Bereich: Whitepaper
Today, enterprises are constantly challenged by inconsistent, incomplete and inaccurate data from myriad data sources. Data preparation is the process by which data analysts transform and organize that data into new data sets suitable for exploration and analysis. Data preparation is also a highly interactive experience, which needs to enable data analysts to quickly, accurately and independently prepare data for trusted reporting and analytics. Data is exposed to analysts in a spreadsheet-like interface, where they can then easily improve its quality, as well as enrich and shape it, to meet their analytical needs.
One of the key challenges with traditional data preparation is that it is a disjointed process. Typically, data preparation and analytics processes are conducted in separate software applications, making it slow, hard and expensive to prepare and then integrate data into a second tool for reporting and analysis. Data analysts use those dedicated data preparation tools to work with relatively small data sets, which limits the flexibilty and speed of data provisioning that organizations require to feed their Business Intelligence (BI) and analytics initiatives.
Please find more information in this white paper.
Bereitgestellt von:
Yellowfin
