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Is Time Running Out for the Traditional Analytics Power User?

Posted by Mark Fry and Daryl Baker on Jan 28, 2021 7:00:00 AM

Historically, the complexities of analytics tools have given rise to a Power User / Casual User split. Power Users consider themselves analytics gurus and commonly author content for others as well as themselves. They have made a niche by being highly skilled at creating beautiful visualizations in dashboards and presenting data visually. Frequently, within a department you might find a handful of Power Users creating and delivering content to a wider audience of Casual Users. Casual Users are generally less savvy and often left in awe when presented with these dashboards. They look amazing, and on the surface, they appear to deliver truthful answers. But are these Casual Users being sold short?

Out with the old and in with the new.

Power Users can be seen to lack governance. Power Users often use desktop tools with local data sets and end up with isolated siloes of data that are non-standardized, stale, often calculated incorrectly and difficult to manage. This results in sub-optimal decisions being made in a non-collaborative way and in people losing trust in the data. There is also the risk of confirmation bias, where the Power Users visualize only what they assume is relevant but might overlook factors critical to answering the business question at hand.

The fight of the business, what do they really want?

Is an IT-led analytics solution the answer? IT users care about things like governance, making sure that data is accurate, secure and accessible. Their main goal is delivering the ability to handle large volumes of trusted data with performance and disseminate it to large volumes of users. While this addresses the lack of governance, it often introduces critical bottlenecks as the IT department gets inundated with requests from multiple departments. Focusing on IT priorities by pursuing governance at the expense of agility leads to lost opportunities. Not being able to get fast answers to questions means either you can’t take advantage of opportunities in a timely manner, or the users are making fewer data-driven decisions. It doesn’t address the confirmation bias issue either. Do recent advances in AI present a possible alternative?

Does AI spell the end for the traditional Power User?

We have seen the introduction of “smarts” and AI into analytics tools to help answer more ambiguous questions and empower Casual Users in diagnostic analytics. Tech Data sells AI-infused analytics tools and data platforms that are designed to take the complexity out of building analytics. They use statistical models and machine learning under the covers to help answer those “why” questions accurately. There is no longer a worry about confirmation bias, as the AI examines the data and trains itself on what is statistically significant. Beyond this, AI can act as a “co-pilot” to help Casual Users build their analytics without those users needing ninja-like skills in using the tool. Natural language conversational capabilities allow Casual Users to ask simple questions of their data. The AI then determines the intent of the question, finds which data set best fits in answering the question, and presents the answer in a visually appealing way that is easy to consume. What does this mean for the Power Users? Now Casual Users can interact with an AI assistant to build visually appealing dashboards and ask questions about their data in natural language, and as AI becomes more prevalent in our analytics solutions, will the role of the Power User fade into obscurity?

What is the Future of the analytics Power User?

Power Users need to evolve to survive. By their very nature they are highly skilled and receptive to new innovations. As organizations adopt more mature Analytics strategies, the market is seeing an increasing appetite for Data Scientists to build and maintain predictive models, and this seems like a natural progression for the Analytics Power User to step into. Rather than being replaced by AI, Power Users can continue to be highly important by becoming the very people who build and train AI. Don’t write them off just yet.

About the Authors

Mark Fry is an experienced Analytics solutions specialist with over 33 years of technical expertise in the IT industry. Currently, Mark serves as a Technical Consultant in Tech Data's IoT and Data Solutions Practice, acting as a trusted advisor to Tech Data's US Business Partner community. Originally from the UK, Mark is based in Ramsey, New Jersey.

Daryl Baker is a leader in the analytics space with over a decade of knowledge in running a niche global analytics software organization.   Daryl runs the BSP Software group within Tech Data that develops, supports, and sells administrative tools for IBM Cognos Analytics world-wide.

Tags: Analytics, Big Data and Analytics, Power User, Does AI Spell the End for Traditional Power Users, Analytics Power Users, The Future of Big Data Analytics Power Users