Key Data Trends Shaping Businesses in 2022 and Beyond
Which data-related trends will be the most important to keep an eye on?
- By Ravi Shankar
- December 17, 2021
COVID-19 has pushed every industry and organization to embrace digital transformation at scale, upending the way many businesses will operate for the foreseeable future. Organizations no longer tolerate monolithic and centralized data architecture; they are embracing flexibility, modularity, and distributed data architecture to help drive innovation and modernize processes.
Expect these three trends to be top of mind for CIOs and CDOs:
Trend #1: Data fabric will become the foundation for the distributed enterprise
As digital business and online sales channels proliferate and remote work becomes the norm, it creates a complex and diverse ecosystem of devices, applications, and data infrastructure. The data infrastructure can span on-premises, single cloud, multicloud, and hybrid-cloud implementations (or a combination of these) spread across regional boundaries. On top of that, there are too many choices for data infrastructures that many organizations are adopting, namely data warehouses, data lakes, cloud-based object storage, and so on, but there is no single solution to knit this data together.
Organizations are realizing that no single infrastructure is able to solve all organizational data and analytics needs. Even the latest trend of developing data lakehouses in the cloud is falling short. All of this is driving the rapid adoption of data fabric architectures, a technology that knits together various data repositories across cloud and regional boundaries in a seamless fashion.
In 2022, organizations will create a data fabric to drive enterprisewide data and analytics -- and to automate many of the data exploration, data ingestion, data integration, and data preparation tasks. By enabling organizations to choose their preferred data integration, data preparation, data cataloging, and semantic tools, a data fabric will allow organizations to reduce time to delivery, making it a preferred data management approach in the coming year.
Trend #2: Decision intelligence will make inroads for enterprisewide decision support
Organizations have been acquiring vast amounts of data and are looking to leverage that information to help make more informed decisions. Decision intelligence is making inroads across enterprises as regular dashboards and BI platforms are being augmented with AI/ML-driven decision support systems.
In 2022, decision intelligence has the potential to make assessments not only better but also faster, given that machine-generated decisions can be processed at speeds that humans simply cannot achieve. The caveat: machines still lack consciousness and do not understand the implications of decision outcomes. Look for organizations to incorporate decision intelligence into their BI stack to continuously measure outcomes and avoid unintended consequences by tweaking the decision parameters accordingly. As decision intelligence becomes mainstream, decision intelligence engineers and data scientists will also have to closely collaborate with business teams to achieve their desired business goals.
Trend #3: The importance of small and wide data for the future of analytics will rise
AI/ML is transforming the way organizations operate, but to be successful, it is also dependent on historical data analytics, aka, big data analytics. Big data analytics is here to stay, but in many cases this old historical data loses its value.
In 2022, organizations will look to leverage small data analytics to create hyper-personalized experiences for their individual customers and understand customer sentiment about a specific product or service within a short time window. Although wide data analytics is a comparatively new concept and has yet to find widespread adoption, given the pace at which organizations are making use of unstructured and structured data together, expect to see small and wide data analytics gain better traction across organizations as we enter 2022.
Closing Thoughts About 2022
There is no slowing down of data dependency for businesses across industries and regional boundaries. Almost every industry player is looking to establish themselves as a technology company first, aka, the Amazon or Netflix way. Organizations have pushed the gas pedal on their digital transformation journey; now they understand that they need to be mindful of how they integrate and manage enterprise data that is distributed, still easily accessible, trusted, and governed. AI/ML and data science hold great promise for the future, but in 2022 human intervention will be recognized as an irreplaceable participant in achieving intended business outcomes.
Ravi Shankar is senior vice president and chief marketing officer at Denodo, a provider of data virtualization software. He is responsible for Denodo’s global marketing efforts, including product marketing, demand generation, communications, and partner marketing. Ravi brings to his role more than 25 years of marketing leadership from enterprise software leaders such as Oracle and Informatica. Ravi holds an MBA from the Haas School of Business at the University of California, Berkeley. You can contact the author at firstname.lastname@example.org.