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.
Data preparation tools come in many shapes and sizes and not all are equal. If your business is interested in implementing a self-serve environment where its business users can become a greater asset to the organization, and use data preparation for analytics, you definitely need to consider ease-of-use for your users and flexibility, sophisticated functionality and mobile accessibility for the good of the organization.
Extract, Transform and Load (ETL) refers to a process of connecting to data sources, integrating data from various data sources, improving data quality, aggregating it and then storing it in staging data source or data marts or data warehouses for consumption of various business applications including BI, Analytics and Reporting. It offers high quality data, which otherwise resides in poorly structured heterogeneous, complicated data sources.
The world of business analytics has changed dramatically in the past few years. If your business is looking to upgrade BI tools or to begin implementing an analytics solution, the solution must be user friendly for business users. The tools exist today for augmented analytics, augmented data discovery, self-serve data preparation and other features and modules that provide sophisticated functionality and algorithms in an easy-to-use dashboard and environment that is designed to support business users, as well as data scientists and IT staff.
ElegantJ BI, an innovative vendor in Business Intelligence and Augmented Analytics, is pleased to announce that ElegantJ BI is named as Representative Vendors in the Gartner ‘Market Guide for Traditional Enterprise Reporting Platforms‘ report published September 28, 2017.
What is self-serve data preparation? It isn’t a method of making up data. It is a method of preparing data that allows the average business user to compile and analyze data without the assistance of a data scientist or an IT professional.
By providing sophisticated analytical features and algorithms in an easy-to-use self-serve environment, the enterprise enables business users to perform data preparation and test theories and hypotheses and prototype on their own. Rather than preparing data at the central meta-data layer, and restricting what business users can do and see, IT enabled (rather than IT controlled), self-serve data preparation allows users to compile and prepare data and use that data in analytics to test hypotheses, perform visualization and create and share reports, and create custom alerts and other information. Business users can control the data elements, the volume and the timing.
This might be a strange comparison but let me make it anyway! Think of data agility and data quality like a tight rope act. The tightrope walker is thinking about getting to the other side without falling. The audience wants to see grace and beauty during the process. They want to see a QUALITY act. In the case of the tightrope walker and the audience, they sometimes have very different goals.
