5 tips for enabling citizen data scientists

Self-service analytics tools are enabling citizen data scientists to dig deeper into BI than ever before. Experts offer insights into how to empower data democratization.

As enterprises increasingly strive to become data-driven operations that depend more on empirical evidence than on intuition to influence business decisions, they’re going to need more people to be able to effectively crunch the numbers. Long gone are the days where the typical user is content waiting for a new report to be churned out by overworked BI analysts.
Analysis and presentation of numbers are expanding outside the reach of BI, as more organizations democratize the process. But in order to get the most out of what citizen data scientists can do across the enterprise, organizations must find ways to enable them to get the job done. Citizen data scientists need better access to not only the data that’s relevant to them, but also user-friendly tools to analyze and present it in an understandable format.

Even though the business user is in charge of slicing and dicing, there’s a lot of work on the back end to make that process as seamless and effective as possible. In particular, organizations seeking to enable citizen data scientists need to keep data visualization top of mind, as that’s what will make or break the data-driven decision-making process.

“You need visualization to get the most out of big data,” said Cody Swann, CEO of Gunner Technology, a development firm that aims to enable its users with visualization tools. “First, because visualization makes spotting potential trends and correlation much easier and, second, because seeing is believing, and execs need a visual representation to easily consume.”

It takes a three-pronged partnership to enable a culture of self-service analytics so users can consistently, quickly and effectively build the right data visualizations when they need them. Users need not only support from IT to procure and run the infrastructure behind all the data, but also support from the BI analysts for whom data crunching is second nature, to help put the analysis and visualization process on rails for them. That way, users can then run individual reports on their own, but they’re backstopped with the assurance that data handling is secure, runs consistently and is based on sound mathematical principles.

We asked experts for some tips to get organizations empowering their citizen data scientists. Here’s what they suggested:

1. Pair citizen data scientists with business analysts

Self-service analytics served up to citizen data journalists shouldn’t consist of just letting users figure it all out on their own. Ideally, organizations should pair the users with BI professionals to come up with different classes of analysis and visualization that work for everyone.

“Having a business power user paired up with a seasoned BI professional can often lead to better results faster than putting the responsibility into the hands of either group exclusively,” said Michael Golub, senior vice president of analytics and machine learning at Anexinet. “Visualization is creative work just as much as it is technical. Taking an agile business/tech-working-together approach is one way to get the most out of the time spent designing and developing critical visualizations that will eventually help shape the direction of your organization or enterprise.”

Read the full article at searchbusinessanalytics.techtarget.com

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