What is Self-Service Data Preparation & Can it Provide Actual Business Results?
Let’s cut to the chase! Results are everything and when you think of a task like preparing data for analytics, that task does not seem to have a direct connection to results. Or does it? Renowned technology research and analysis organization, Gartner, predicts that data and analytics organizations that provide agile, curated internal and external datasets for a range of content authors will realize twice the business benefits as those that do not.
If you choose and provide the right Self-Service Data Prep tools that are easy enough for business users to adopt, you can take the complex task of extracting, transforming and loading data (ETL) out of a restricted, limited environment and enable team members with average technical skills to prepare data for analytics and perform data analysis without waiting for IT or data scientists to intervene. Self-Service Data ETL should simplify the tasks of preparing data so users WANT to adopt the tools and use them for data prep and Data Analytics.
These easy-to-use tools allow business users to transform, shape, reduce, combine, explore, clean, sample and aggregate data, without the need for SQL skills, ETL or other programming language and the good news is that business users do not need to understand the complexities of any of these processes in order to use these tools. Augmented Data Preparation provides support and information so users get help at every step along the road and can compile and prepare data for use in analytics to test hypotheses, visualize data and create and share reports with other users. Machine learning capability provides guidance to determine the best techniques and the best fit transformations for the data business users want to analyze, allowing for better understanding of data.