Top 8 Future-Proof Analytics Trends for 2021

After a most unpredictable year full of black swan events, now is the time for data scientists and business analysts to humbly take the hard-learned lessons of 2020 and move forward. 

This is not one of those “crystal ball” new year prediction blogs! Rather than chase buzzword mysticism of highfalutin prognostication, let us default to a tried-and-true model for charting a future-proof course forward: industry research trends. 

The Eight Trends That Will Matter Most

Industry analysts and researchers often seek validation of directional trends with a minimum of three data points. It’s the magic number, and the basis for establishing the beginning of observing an emergent “pattern.” As such, the following is an index of these rolled up trends as themes which echoed persistently from industry analysts as top analytics trends for 2021. 

Intelligent, Adaptable Business

Very complex global market conditions will demand more shifts and pivots again in 2021, and organizations will need to be lean and agile enough to respond in real-time. If 2020 taught us anything it's that in business climates with rapidly changing global market conditions, decisions must be data-informed, but, perhaps most importantly, nimble enough to adapt to both risk as well as new opportunities as they develop—on much shorter frequencies and turnaround.  

More AI-Driven Automation in the Workplace 

With as many as one in every four remote workers supported by new forms of automation (Robotic Process Automation (RPA), etc.), more artificial intelligence (AI) proof-of-concept projects will continue to roll off the line and progress into production environments. While there will be more automation in decision environments, humans will remain a vital cog in the decision-making process. 

Growth on the Edge 

Computing continues to get closer to where data is actually generated. As a result, real-time analysis of those edge events is being built into models sooner—when and where decision makers need it. With the explosion of sensors and connected smart devices, ever-increasing Internet of Things (IoT) data exhaust will be the fuel for optimization loops to predict and improve future performance. 

Trust and Ethics: More Accountable AI

Trust will remain the top spot reason why executive decision makers don’t believe AI-recommendation systems. While 94% of leaders who’ve adopted AI trust their data, only 64% of those trust it to be reliable enough for business change. Further operationalization of “responsible AI” will be underpinned by the growing discussion of digital ethics and bias.  

Closed-Loop Decision Models

Businesses will need to leverage learnings and harness collective knowledge as a shared asset in 2021. Using closed-loop decision models to accomplish this, organizations can accelerate knowledge sharing and develop pipelines to support learning.  

Convergence of Analytics Technology Continues  

Whether machine learning, data management, or governance, these formerly discrete market categories will continue to intersect. This hyperconverged platform approach brings visual analytics, data science, and streaming capabilities together in a seamless experience, delivering immersive, smart, and real-time business insights. 

Interactive Discovery Is Now Table Stakes

With Natural Language Query (NLQ) and similar capabilities making great strides, these features and functionality have now become commoditized and are no longer differentiating in the market. “Analytics culture” will remain a top barrier to full realization and adoption of augmented intelligence. 

More Momentum in Network Graph Analytics

Interest in graph and network analysis will continue to grow in future years. Organizations seeking connections across datasets will implement network graph analytics to identify the most valuable relationships and explore unknowns.  

For more top analytics landscape trends, follow my musings on Twitter.