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.
Today, enterprises recognize the critical value of advanced analytics within the organization and they are implementing data democratization initiatives. As these initiatives evolve, new roles emerge in the organization. The newest of these analysis-related roles is the ‘analytics translator‘. As the enterprise considers the relevance of this new role within the business, it is important to understand the responsibilities of an Analytics Translator, and how this role might help the organization to achieve its goals.
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.
Self-Serve Data Preparation is the next generation of business analytics and business intelligence. Self-serve data preparation makes advanced data discovery accessible to team members and business users no matter their skills or technical knowledge.
The term ‘Advanced Analytics’ can seem daunting to the average business user and even to the average business enterprise but the process is not as complex as it may seem.
Advanced Analytics is comprised of numerous sophisticated analytical techniques, designed to parse, explore and analyze data and produce results to support business decisions. Fortunately, today’s new self-serve business intelligence solutions allow for ease-of-use, bringing together these varied techniques in a simple interface with tools that allow business users to utilize advanced analytics without the skill or knowledge of a data scientist, analyst or IT team member. Advanced Analytics provides a 360 degree view of data from data marts, data warehouses, best-of-breed, legacy systems and other data sources. The analytical techniques and algorithms are designed to identify patterns and trends, pinpoint issues and the root cause of these issues and allow the enterprise to capitalize on opportunities and accurately plan for the future.
There is too much to do in a day to wait for someone else to give you the data you need. But, when it comes to data preparation and data analytics, business users are usually not comfortable with complex solutions that are time consuming or that require professional analytical skills. You pay your team members to have a certain type of expertise and that doesn’t always include technology or analytical knowledge. So, if you want them to be a real asset to the organization, you have to give them easy-to-use self-serve data preparation tools. Self Serve data prep allows business users to quickly gather and prepare data for analysis and to answer questions and solve problems without delay.
ElegantJ BI, a leading vendor in Business Intelligence and Advanced Analytics solutions, is pleased to announce that it is listed for its suite in the Gartner ‘Other Vendors to Consider for Modern BI and Analytics’ report published August 4, 2017.
