A decade ago, Google Chief Economist and Founding Dean of the UC Berkeley School of Information Hal Varian predicted that the next big job would be statistician. He wasn’t wrong; there is a massive demand for data scientists and business analysts, who can in turn name their price.

How Data Science Has Democratized: The Rise of the Citizen Data Scientist

Unfortunately for many companies, this high demand and high price put these specialists out of reach for the average midmarket organization. Not often can a midsized organization justify the creation of a new department, much less one that costs hundreds of thousands per year.

Luckily, technology has made analytics more user friendly and accessible, leading to a new era of analytics, one where a broader group of individuals can analyze and make decisions on information. While not as well-versed in data science, they are also much more affordable and are able to use knowledge from their role to apply data.

These “citizen data scientists” have more access to data than ever and deliver subject matter expertise in their fields. Empowered by business intelligence tools, these individuals can design and run the reports they need in a timely fashion and make decisions based on data that is as close to real time as possible.

As this takes place, users are able to make more complex queries and do more with the software, getting more value from the data and positioning the company for long-term success.

Challenges in Empowering Citizen Data Scientists

However, getting them set up and running is a challenge. Powerful and affordable tools like Power BI deliver functionality unmatched for the price, but for many people, the setup process can be overwhelming.

Getting Started

With hundreds of integrations available and thousands of reports you could generate and tweak, where do you start? Yes, there are templates available; yes, adding data sources is relatively easy; and yes, you could play around until things work.

However, think of it like this: You’re trying to cook a copycat recipe from a restaurant. You know what you’re trying to achieve, you have access to the right ingredients, but getting from concept to end product correctly isn’t exactly as easy as you’d think.

Say you’re a manufacturing firm and want to track YoY variance by expense category, headcount, and division in Power BI (one of the key metrics we mentioned in our blog on use cases). Where do you start? This is often one of the top concerns for organizations. Just as the wrong Excel formula and data source will yield the wrong results, the same goes for your BI setup.

Permissions Management

A trend noted by TechTarget, controlling who has access to raw data and who has the opportunity to make changes is a necessary part of empowering citizen data scientists. If the wrong person makes changes to a report, you may have to backtrack to find out what went wrong to fix it, possibly even losing reports.

Understanding How to Use BI

Before citizen data scientists can be expected to incorporate curated data sets, however, they must be trained properly. It’s important to remember that even when they’re eager to learn, they often don’t have the analytical educational foundation that a typical BI analyst has. This means you’re looking at steeper learning curves for tooling and processes.

While Power BI is easier to learn than many BI platforms, training on the customization and use of the product can set you up for success in the long term.

Setting Your Citizen Data Scientists up for Success: MIBAR and Power BI

At MIBAR, we have worked with Microsoft for decades, and are proud to recommend their products for companies looking to improve their results, gain more insight into data, and make smarter decisions.  If you’re looking to provide your non-analyst users with the tools they need to succeed, we recommend Power BI, an affordable and easy to use business intelligence product that can connect hundreds of potential applications.

We’ve helped companies like yours to set up Power BI, integrate it with the applications they currently use, and make decisions with better data. See a couple of our success stories including Wildlife Trading Company, AP&G, and Kayco, read our guide to business intelligence, and contact us for more information.