As business organizations fight for competitive advantage, funding for projects and large expenditures can fall by the wayside. In today’s competitive business market, every senior executive looks at risk, value and calculations like return on investment (ROI) and total cost of ownership (TCO) before approving a budget.
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.
Many organizations have grown comfortable with their business intelligence solution, and find it difficult to justify the need for advanced analytics. The advantages of advanced analytics are numerous and those advantages are based on the ability to further improve the business, increase user adoption (and therefore user empowerment and accountability) and, best of all, improve the bottom line and the accuracy of predictions and forecasts that will dictate the success of the business in the future.
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.
If your enterprise is entangled in complex data preparation and manipulation, and you want to simplify and expand the use of data preparation to leverage data integration and self-service data prep, you need to explore the potential of augmented data preparation. Data extraction, transformation and loading (ETL) can be a complex, time-consuming process, but self-serve data prep is ETL for business users.
Self-Serve Data Preparation is a critical component of augmented analytics. If these terms seem foreign to you, just know that they represent the future of business analysis. As organizations adopt self-serve business analysis, the business user with average technology skills must be able to leverage tools that are sophisticated, yet easy to use.
Self-serve has many meanings. You can pump your own gas, you can serve yourself at a buffet, and sometimes you can even do your own data preparation. You will notice that I said ‘sometimes’. That is because you have to choose the right tool if you want to really participate in self-serve data preparation.
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.
Self-Serve Data Preparation (aka augmented data preparation) is all about efficiency and the presentation of sophisticated data preparation tools in an easy-to-use environment. The idea behind self-service data preparation is to give the average business user the ability to prepare, use, report on and share data without the assistance of IT staff or analysts, thereby making their jobs easier and making every team member more of an asset to the organization.
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.
