2021 Analytics Trends You Need to Know

Will this be the year the masses move beyond the dashboard? 

The COVID-19 pandemic brought data and analytics to the fore: World leaders and common people pored over dashboards, charts, and reports to suss out infection rates and medical supply levels in a desperate bid to flatten the curve and save lives. 

Businesses of all kinds used data and analytics to survive as well. Those left standing likely owe part of their existence to a savvy use of the data at their disposal, leveraged by their hardworking and scrappy workforces. As the new year ramps up, these same teams will rely even more on data. Staying ahead of the 2021 analytics trends will only help them expand their niches. 

In a recent survey by International Data Corporation (IDC) on behalf of Sisense, 66% of business leaders said the ability to deeply embed analytics into applications and processes was very or extremely important to them. Every company wants to make better decisions based on data and analysis, and putting insights and actions together right where people need them will move the needle on adoption.

Widespread infusion of insights into workflows, intuitive AI, code-driven analytics, and customer-facing data in apps are just a few of the 2021 analytics trends that will change the way the world works. Read on to understand how.

Ashley Kramer, Chief Product and Marketing Officer

This may be the most significant 2021 analytics trend. BI adoption has stalled at about 30% across industries. Dashboards promised do-it-yourself insights and a single source of truth, but people just aren’t using them. Years of training and positive intent have failed to create the widespread embrace of data that companies need in order to survive in a changing business world. 

What it means for business leaders

A signature weakness of dashboards is that they require an inefficient and focus-intensive deviation from a user’s central workflow. Dashboards also lack inherent analysis or guidance; they describe what has occurred but don’t prod users to make decisions or recommend particular choices based on data. That’s the missing link for companies to become truly data driven.


The number of business consulting companies that plan to use standalone BI&A platforms. Fewer than 5% do now.

“The challenge of standalone dashboards is we can’t act on them,” says Ashley Kramer, Sisense Chief Product and Marketing Officer. “Instead of requiring people to change the way they work to access insights, we see successful organizations flipping the script and infusing analytics where people work. By putting the right intelligence into workflows, processes, and applications, analytics-fueled decisions become automatic and instinctive, so organizations can surpass their objectives.”

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).


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.


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. 


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. 


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.”

Harvard Business Review: Getting Strategic Value from Data Analytics When Initial Attempts Fail

Sisense surveyed almost 200 respondents — across different industries and positions — to understand their outlook on the role data and analytics could and should play in their companies. Less than 24% of study participants believe their organizations use data effectively, yet 94% say it’s essential to their ongoing innovation strategy.

Read what they had to say in our report, with Harvard Business Review Analytic Services: Getting Strategic Value from Data Analytics When Initial Attempts Fail.