Top 10 Data and Analytics Trends for 2021 Posted on : Nov 13 - 2020

How has the COVID-19 pandemic impacted the world of data and analytics in the enterprise? Here are the trends for 2021.

Enterprise organizations have embraced the ideas behind advanced analytics technologies over the past several years, beginning with buzz words like big data and moving onto topics such as machine learning and artificial intelligence. But the promise of these technologies can sometimes get lost in the reality of implementing them in the real-world enterprise. Depending on what survey you are looking at, how you define the technologies, and what questions you ask, enterprise organizations' adoption of advanced analytics, machine learning, and AI varies quite a bit.

But the technologies have captured the attention of both the IT pros in the trenches and the top enterprise executives who recognize its promise for everything from cutting costs, to increasing revenue, to accelerating innovation and improving competitiveness in the market.

Last year Gartner said that enterprise AI deployments to production hit 19%. But as the technology becomes more mainstream through more support from vendors, a bigger talent pool, and a host of technology advances, enterprises will be in a better position to put artificial intelligence to work in a number of ways that hadn't been considered.

With that in mind, during its recent Gartner IT Symposium, the analyst firm unveiled its Top 10 Strategic Technology Trends in Data and Analytics, 2020, a list designed to take organizations "from crisis to opportunity," as enterprises recover from the effects of the pandemic on business and IT initiatives.

1. Smarter, faster, more responsible AI. Gartner is forecasting that 75% of enterprises will shift from piloting to operationalizing AI by the end of 2024, driving a 5x increase in streaming data and analytics infrastructures. There are challenges with current approaches. Pre-covid models based on large amounts of historical data may no longer be valid.

But the disruptions in AI will enable learning algorithms such as reinforcement learning, interpretable learning such as explainable AI, and efficient infrastructures such as edge computing and new kinds of chips.

2. Decline of the dashboard. Data stories, (not dashboards) will become the most widespread way of consuming analytics by 2025, and 75% of these stories will be automatically generated using augmented analytics techniques. AI and machine learning techniques are making their way into business intelligence platforms. In dashboards users have to do a lot of manual work to dive into further insights. But these data stories provide the insights without requiring the user to perform their own analysis. View More