
How does an organization help the self-serve advanced analytics model grow and thrive? Responsibility lies in a number of places within the enterprise.

How does an organization help the self-serve advanced analytics model grow and thrive? Responsibility lies in a number of places within the enterprise.

I hope you would agree that every team member in your business is an important and valuable resource. When we talk, in the tech world, about self-serve apps and the concept of cascading analytics to everyone in the organization, managers and team members start to get nervous.

If you read industry and technology journals, you have probably seen the term, ‘digital transformation’. So, what is digital transformation Gartner asked, and here is what the Gartner glossary of terms says about that: ‘Digital business transformation is the process of exploiting digital technologies and supporting capabilities to create a robust new digital business model.’ So, that is the digital technology business definition and that definition will translate differently for every organization in terms of where the enterprise will begin to focus the transformation process and how it will get to its goal.

As a business manager or a business team member, you probably make it your business to stay abreast of industry and market trends and to understand how best to use technology to refine business results and better understand your market, competition and customers. If you have been reading industry publications, you are probably familiar with the concept of augmented analytics and augmented analytics benefits.

A data discovery tool is a crucial tool for every business user in your organization. With so many sources of data, in so many locations with your enterprise, it is impossible for users to know whether they have access to complete, accurate data to make decisions.

Can Your Business Achieve Self-Serve Data Prep? Lots of my friends talk about the difficulty of preparing data for analysis and how long it takes to get IT or data scientists or analysts to take on the project, get the data prepared and run reports or perform analytics. Frankly, this problem is a puzzle to me!

Data prep can slow down analytics and cause delays. Self-service data preparation (when done right) can enable business users to leverage sophisticated, easy-to-use tools for self-serve ETL. Data extraction, transformation and loading (otherwise known as ETL) can be time-consuming and requires professional skills but self-service ETL will walk business users through an augmented data preparation process and take the complicated, confusing steps out of the process by helping the user make decisions on how to prepare, clean, reduce and use the data in the best way possible.

You have probably heard a lot about the benefits of transforming business users into Citizen Data Scientists by deploying an advanced analytics platform. Let’s say you did your homework and found just the right solution so that all your needs are met and your business users can happily embrace the solution and become empowered – and in so doing, add value and accountability to your organization.

The benefits of advanced analytics are many and the current support in the market for business user access and data insight provides expanded advantages of advanced analytics.

How does one measure the effectiveness of a new Augmented Data Discovery solution? Once the business has chosen data democratization and implemented a self-serve analytics solution, it must measure ROI & TCO and establish metrics that will compare business results achieved before and after the implementation.