Can Your Business Achieve Self-Serve Data Prep? Lots of my friends talk about the difficulty of preparing data for analysis and how long it takes to get IT or data scientists or analysts to take on the project, get the data prepared and run reports or perform analytics. Frankly, this problem is a puzzle to me!
In years past, data preparation was the domain of IT professionals and data scientists. In order to prepare data for analysis, one had to find, gather, and prepare the data and that preparation included cleaning, combining, reduction and shaping of the data.
Self-serve data preparation allows business users with average technical skills to gather and prepare data for analysis without the help of an IT professional or a data scientist. So, why is that important? Data prep is often the forgotten step in advanced analytics but, without a self-service data preparation tool, the process can take a long time and it can result in incomplete data, data that is hard to analyze and, sometimes, a total work stoppage while IT or a data scientist attempts to sort through the issues and untangle the mess.
Extract, Transform and Load (ETL) refers to a process of connecting to data sources, integrating data from various data sources, improving data quality, aggregating it and then storing it in staging data source or data marts or data warehouses for consumption of various business applications including BI, Analytics and Reporting. It offers high quality data, which otherwise resides in poorly structured heterogeneous, complicated data sources.
