Data analytics are more important than ever for businesses to stay agile, but the technology and data science aren't always where they need to be.
The sudden shift to work-from-home caught many traditional companies by surprise. This opened the door for startups and agile competitors to steal market share. Fitness company Zumba, for example, switched in less than two months from in-person training to a platform for online classes, while other better-known fitness giants stumbled along, hoping their gyms would soon reopen.
Those well versed in business intelligence (BI) and analytics tend to have a higher capability for rapid change, and thus tended to fare better during this past COVID-plagued year by harnessing BI to predict faster, observe trends more rapidly, and to switch gears accordingly.
But just as the business world is transforming, so too is the BI landscape. A new paper by BI vendor Qlik.com lays out some of the top BI trends for 2021.
BI as a service
Not surprisingly, SaaS, PaaS and other -aaS vendors have had a marquee year. Those reluctant to move online or add more cloud applications had their hand forced during 2020. BI and analytics vendors are among those who cashed in. That’s why Gartner predicts that by 2022, public cloud services will be essential for 90% of data and analytics innovation.
2020 saw data visualization explode into the mainstream via real-time COVID-19 dashboards on cable network news. The general public has gained broader access to all kinds of political, weather, financial, health, and other data sources. As a result, the art of data storytelling and infographics came into its own. The data literacy level of the population has risen. This, in turn, is driving BI and visualization tools to offer more context, and to become more user friendly to bring data to a wider user base.
AI hits business mainstream
Up-to-date and business-ready data have become more important than ever. Quarterly forecasts are no longer enough. Thus, artificial intelligence (AI) and machine learning are being introduced to increase the accuracy and timeliness of alerts, data refreshes, and more frequent forecasts. Supply chain disruption and unnecessary panic buying of items like toilet paper can be tackled by tying AI into data feeds to ensure current, accurate information. This is all about making data business ready. That means it must be curated for analytics consumption, made accessible as close to real time as possible, and tied into business logic to provide detailed insights. Gartner, therefore, predicts that 75% of enterprises will operationalize AI by 2024, driving a 5X increase in streaming data and analytics infrastructure.
Data science lacking
Advanced analytics deployments have surged in the wake of the pandemic. And this has brought into sharper focus challenges such as predictive models not encompassing data from a long enough period, failure to understand the role of outliers, and simulations that vary widely from reality. Thus, BI vendors are being tasked with building better what-if analysis engines, incorporating AI into their tools, and providing humans with data that enables them to consider the implications of anomalies that live outside preconceived hypotheses. Further, advanced analytics need to be embedded in more places to deliver faster results to more people. Look for a major overhaul of many BI and analytics tools in 2021 as a result.
The great digital switch
Demand for data and analytics is likely to stay strong for some time. But change is a-coming! Back in 2008, the financial crisis proved to be the springboard for stronger analytics features rather than the report-centric approach of traditional BI. Digitalization is now driving greater convergence and integration between data management and analytics. And with COVID-19 induced financial stress upon us, the time is ripe for BI tools to take advantage of newly available and accessible digital streams to bring more timely and contextualized insights to business leaders.
This article was originally published on 01-15-2021