Six Data & Analytics Trends to Track in 2022
At Aspirent’s annual Data & Analytics practice planning meeting in January, we examined key trends in the marketplace—from cloud to the talent crunch—and what they might mean for our clients. Here’s a summary of the trends along with insights on how organizations can manage through inevitable challenges to accelerate progress.
- Vertical cloud
Clients are continuing a massive shift of applications to the cloud. A key trend among the major cloud providers is to offer optimized vertical solutions for industries including retail, health care, hospitality, and others. We expect these offerings to evolve quickly, provide more options for organizations to buy vs. build, and accelerate cloud migration initiatives.
- Data fabric
Data fabric integrates data across platforms to make it more readily available, but performance can be quite poor depending on where the data is located. Organizations will continue to push integration of data beyond the consolidated data lakes to provide integration across disparate data sets. A continued focused on data governance, cataloguing, and data quality can help organizations overcome the shortcomings of evolving data fabric architectures.
- Tech talent crunch
Growing demand for a limited supply of technology workers will drive companies to get creative about how they attract and retain talent—like leveraging advanced analytics to predict attrition and courting candidates with highly targeted marketing efforts. With talent shortages likely to inhibit adoption across technology domains, companies will continue to rely on services partners for expertise they are unable to hire to ensure delivery of their strategic initiatives.
- Optimization of cloud applications
Many organizations have executed an initial migration of applications from on-prem to cloud using a lift-and-shift approach that delivers quick-hit cost savings. But to take full advantage of the cost-effective compute capabilities that cloud has to offer, organizations ultimately will have to re-architect these applications.
- Increased data literacy to drive analytics adoption
Business and advanced analytics are of little value to an organization if people aren’t using them. Whether because of a lack of trust, understanding, or necessary skill sets, lagging analytics adoption rates must be improved if companies are going to enjoy the operational and go-to-market benefits. The fix: comprehensive data literacy and change management programs that start early and persist beyond rollout.
- End-to-end analytics
Traditional analytics have focused on performing downstream, after-the-fact data consolidation, transformation, visualization, and advanced analytics. But the evolution of these capabilities is generating increasing demand for real-time, advanced analytics (think Amazon-style recommendations) that are embedded in operational capabilities. Organizations that can successfully execute the end-to-end integration of operational data and analytic insights stand to gain significant business and industry advantages.
David Mobley, Aspirent Practices Leader