Preparing data for analysis used to be a long, difficult process performed by IT or data scientists. Needless to say, that process meant that business users could not get the job done. They were forced to make a request, wait for the process to be completed and then, more than likely, for the same team to actually perform the analysis. If the data prep was not accurate or was incomplete, the process starts all over OR produces poor results and, in many cases, those poor results are not obvious to the business user. What does that mean? It means that the business is using information and results that they do not know are wrong!
SO…when Augmented Analytics evolved to include Self-Serve Data Preparation, businesses could provide better results AND access for business users without data science or analytical skills.
Self Service Data Prep allows a business user with average technology skills to gather and prepare data to explore, clean, shape, reduce, and combine data with tools that auto suggest relationships, JOINS and type casts, and allow users to connect, and mash up data, to sample outliers, to determine data lineage and collaborate with full insight into where the data came from and whether it is dependable. Users can search data, profile and catalogue, all without the assistance of IT or data scientists. So, those users can fulfill roles and responsibilities without delay and with confidence.
With Augmented Analytics and Self-Serve Data Preparation, businesses can improve productivity for business users and for the data scientists and IT teams that support them. By reducing user dependence on these specialists, the business can optimize the time of all team members, engender data popularity, improve data quality and dependability, and champion the use of data across the enterprise.
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