The Rise of the Data Analyst

Data Analysts Are How Modern Businesses Turn Data into Real-time Results

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Everything today moves at the speed of bits. But rewind twenty years — laptops were just taking off, AOL reigned, and CD burners were cutting-edge. To see how much things have changed, just check out the rise of the term “data driven”.

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It makes sense. For a while, most business data was small, a bit stale and lived in a sea of spreadsheets. Now, everything is in the cloud, it's immediate and the volumes are staggering.

Data Stacks – the Good, the Bad and the Ugly

As businesses frantically digitized, they discovered they could stitch their new data together to create business opportunities and reduce operations risk. So next they started hiring engineers to build and operate data stacks.

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Data stacks proved to be powerful, especially for enterprises, but expensive and technical. Even with big investments, businesses can still feel limited by hard-to-get engineering time. Many leaders report missing business opportunities and having higher operating costs due to data bottlenecks.

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This is because companies of all sizes still have three issues:

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1. Engineers are very expensive and there aren’t enough of them
2. Business teams need rapid response analytics and engineers are very busy
3. Engineers can't always have the full business context and it takes time to tune new insights

Invest in Data Analysts

In response, savvy businesses are accelerating their hiring of analysts. In fact, data analysts are now the largest data role in the US.

Investing in data analysts creates big wins. Done correctly, businesses can create new opportunities faster and lower operating costs.

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To achieve this, data analysts are typically part of business teams and collaborate with any specialized data teams (often found in enterprises). This structure allows for business teams to drive priorities, data teams to collaborate and data analysts to have the full context for fast tuning.

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Analysts also need tools – ideally one tool – to conduct thorough data investigations, create insightful reports and build high-impact analytics. This platform should also enable them to leverage standardized data assets, and transfer important projects to specialized data teams.

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Analysts Need Modern Tools

Data analysts struggle when they're under-tooled. Pre-cloud solutions like Excel/spreadsheets, siloed databases and BI dashboarding are too limited for the work analysts need to do.

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With modern tools, data analysts can rapidly create insights and automate solutions. New Analytics Automation Platforms (AAP) do for data analysts what CRM and marketing automation did for sellers and marketers. With AAP, data analysts have a single platform for both one-off analysis and automated analytics, and can collaborate with data teams.

Key features include easy data access, data cleaning, data stitching, data analytics, analytic modeling, data delivery and automation. Combined with a data stack, analysts can even leverage data modeling done by other teams. And after they build high-ROI insights, analysts can automate their delivery back to almost any business app, tool or platform.

It’s a Bright, New World

Now business leaders can get automatic, opportunity-creating insights in hours, not months thanks to data analysts. Using new analytics automation platforms, data analysts can deliver important answers 5x faster when and where business teams need them.

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Have you tried analytics automation? Check out Savant to learn more about how to create more business opportunities from your data and lower operations costs.