2021 Analytics Trends You Need to Know

Tom O’Neill, Chief Cloud Officer

Increasingly complex datasets (data lakes, etc.) will be prepared and analyzed with code written in Python, R, and SQL. Companies will face challenges hiring and retaining the right people with skill sets appropriate for companies’ data needs. 

What it means for business leaders

While AI will be crucial for helping nontechnical workers make sense of the biggest and most complex datasets, only advanced coding languages can perform next-level procedures like forecasting future scenarios or building world-changing technology like autonomous vehicles. You need a skilled data team with engineers knowledgeable in Python and R (and your competitors already have them).

32%

The percentage of respondents to the aforementioned IDC report who prefer to interact with data via code. This percentage will skyrocket as companies ask more and more questions of their datasets, which can only be answered with advanced analytics — 81% of respondents currently use a cloud data warehouse or lake, and code is a powerful way to pull vital insights from the kinds of massive datasets stored in these systems.

“Cloud storage becoming so cheap has massively changed analytics,” says Tom O’Neill, Sisense Chief Cloud Officer. “Instead of organizing everything neatly and querying it, companies often just dump it into data lakes and other large cloud storage systems. Advanced coding languages like Python and R are the only ways to pull insights out of it. Those insights are massive game-changers!”

Charles Holive, Managing Director of Strategy Consulting

Customer-facing apps depend on customizability — and customers increasingly expect personalization and an ability to track their status, progress, app usage, and more. Adding customer-facing analytics to products, services, and experiences increases stickiness, engagement, and revenue. Zoom, LinkedIn, Slack, Strava, and Rosetta Stone have all marshaled data to benefit users and improve their ROI.

Upland Software’s annual app-user retention study gives significant weight to this trend. The survey found that app personalization (via data) for individual users enhances user experience and decreases abandonment rates.

25%

The improvement in retention rate for apps that used data-informed messaging pushes for audience engagement. 

“Putting data and analytics into products is the future — well, it’s the present, but not everyone is doing it yet,” says Charles Holive, Sisense Managing Director of Strategy Consulting. “It’s a crucial strategy to drive new revenue streams and protect existing ones by increasing value for your end users. If you are not finding ways to drive revenue with data, your successor will be — or your business will go under.”

Ryan Segar, Global VP of Sales Engineering

Skullcandy used predictive and sentiment analytics to not only anticipate return rates, but also to inform design improvements during product development. Daimler Trucks Asia took data from over 400 sensors and GPS monitors in order to find issues before they became maintenance problems and warranty claims. Listening to your customers and prospects is integral to creating your company’s next killer app or vertical-defining service. 

What it means for business leaders

Data trapped in myriad dashboards won’t drive your business forward. Moreover, the right application of data and insights will improve your products, your business, and your bottom line. 

40%

The percentage of IDC report respondents that said their product team was planning to use analytics in 2021 — up from 27% in 2020. 

“Every product team claims to be data driven in their decision-making, roadmap, adoption, and impact,” says Ryan Segar, Sisense Global VP of Sales Engineering. “The challenge is that there’s no standard or right way to perform these analyses, so results and assumptions vary even within the same team. The most successful teams gain access to the largest and most robust datasets available and never stop questioning, challenging, and discovering new insights every single day.”

Guy Levy-Yurista, Chief Strategy Officer

Datasets have become increasingly unwieldy, in both number and volume of sources. Humans are rapidly losing the ability to make sense of them with traditional tools. Meanwhile, AI has become smarter, more intuitive, and more able to harness data’s power; its biggest upside is creating augmented understanding for humans.

What it means for business leaders

If your company isn’t using AI, at best you’re leaving money on the table. At worst, you’re on a collision course with failure, which is accelerating at pace with the exponential growth of data volumes. Consider this: 43% of IDC survey respondents draw intelligence from 10 to 30 data sources. For 2021, that number jumps to 64%. Humans are simply not mentally equipped to handle the volumes of data that modern companies produce and that need to be distilled into insights to provide a deeper understanding of the complex, modern business environment. 

44%

The portion of IDC survey respondents who say that the ability for nontechnical users to access AI assistance is very important in their search for an analytics solution.

“AI is more than critical for enabling businesses to distill mountains of data into actionable, illuminating, and pertinent insights which then need to be infused throughout the business,” says Guy Levy-Yurista, Sisense Chief Strategy Officer. “Operating without AI in today’s world of data is like trying to fly by flapping your arms really fast. You’ll never get off the ground.”