Is Self-Serve Data Prep the Same as Augmented Data Prep?

Self-Serve Data Preparation and Augmented Data Prep Go Hand in Hand!

I was talking to a friend the other day and she shared with me her experience at a recent business intelligence conference. She was a bit confused by some of the terminology and we spent a few minutes parsing the terms and talking about the concept of self-serve data preparation. She was confused by the fact that self-serve data prep and augmented data preparation are often mentioned in the same discussion.

“If something is self-serve,” she said. “How can it be augmented? Self-serve seems to me to mean that a person can do it alone without assistance.” She considers ‘augmenting’ to be assisting. Well, in some ways she is correct. But, let me tell you what I told her.

Augmented Data Preparation is designed to provide guidance, recommendations and auto-suggestions so that a user can work alone to get sophisticated results in a simple, intuitive, self-serve environment.

Self-Serve Data Preparation allows business users to perform data preparation and test theories and hypotheses by prototyping on their own. Users are not restricted to complex tools or forced to wait for programmers or data scientists, so in that respect, using the system is truly a self-serve experience!

Transform business users into Citizen Data Scientists with Self-Serve Data Preparation Tools that allow users to compile and analyze data and test theories and prototypes to support dynamic decisions and planning on their own. Augmented data prep allows for advanced data discovery with auto-suggested relationships, JOINs, type casts, hierarchies, etc. and it reduces and clarifies data so that it is easier to use and interpret the data for analysis. There is no need for advanced skills or technical knowledge to gather, compile and prepare the data. Users can leverage integrated statistical algorithms like binning, clustering, and regression for noise reduction, and trend and pattern identification.

While my friend didn’t really know about binning, clustering or regression, she did grasp the significance of having a tool to guide her through the process of preparing data and help her see the results and the relationships with more clarity. Yes, the system does ‘augment’ and support the user but the user is able to do the work on their own and that is great! It means users don’t have to wait for IT staff or analysts to help them. It means, the business intelligence solution is self-serve!

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