Is Self-Serve Data Preparation Really Possible?
Your business users are ready to do the job! They have a lot of data spread across the enterprise in various data repositories and forms and they want to pull it all together and analyze the data to get the answers to the questions you ask them every day. But, preparing that data is not easy.
In the old days, team members would reach into a file cabinet and pull out folders with the right information. They would pour over the numbers and the data and draw conclusions and then make a plan or provide a report. Sometimes the data was old and sometimes the conclusions they drew were incorrect or based on biased opinion.
Today, Self-Serve Data Preparation can provide business users with the tools they need to find and prepare the data they will need to answer those crucial questions and to do all of that without the assistance of an already overburdened IT staff. Data preparation does not have to be difficult.
Now your users can get what they want, when they want it with complete control over data elements, as well as the volume and the timing. Self Service Business Intelligence provide easy to use tools so that business users can prepare their data on their own without the assistance of IT staff. They can use simple extraction, transformation and loading features – ETL for business users – to extract the data they want and perform analysis and reporting quickly and easily.
Self-Serve Data Preparation allows business users to perform data preparation and Augmented Data Preparation features allow business users to test theories and hypotheses by prototyping on their own. Users have access to simple, easy-to-use interfaces, and drag and drop functionality, without the need for complex tools.
When data preparation for analytics is married with self-serve data prep, users can bypass the process of preparing data at the central meta data layer and access, and prepare data to create and share reports and create custom alerts. Using Smarten suggestions and auto-suggested relationship, they can discover answers and leverage JOINS, hierarchies and type casts without the skill and knowledge of a data scientist.