What does the future of data analytics look like? Gartner provides the answer listing the top 10 trends in data and analytics enterprise leaders should focus on as they prepare for the post-pandemic reset from 2022.
Highlights:
- AI will shift from piloting to operationalizing AI
- Cloud is a given
- The growing importance of Contextualisation and Graph Analytics
- The convergence of Data and Analytics
- Data Exchanges and Marketplaces
- The Blockchain imperative
Data Analytics Trend #1 Smarter, Faster and Responsible AI
Gartner lists Smarter, Faster and Responsible AI as one of the top most leading trends in data analytics 2022 and beyond. By the end of 2024, 75% of enterprises will shift from piloting to operationalizing AI.
Investments made in new chip architectures such as neuromorphic hardware that can be deployed on edge devices are accelerating AI and ML computations and workloads. This could lead to more scalable AI solutions that have higher business impact.
This is driving a 5X increase in streaming data and analytics infrastructures.
Also read: Investments in AI are set to double in the next four years.
Also read: The AI Talent Crisis Is A Myth
#2 Decline of the Dashboard
A cursory look at Gartner’s top 10 data and analytics trends for 2022 indicates the future of Dashboard isn’t looking brighter.
“Dynamic data stories with more automated and consumerized experiences will replace visual, point-and-click authoring and exploration”, noted Gartner.
As a result, the amount of time users spend using predefined dashboards will decline.
The shift to in-context data stories means that the most relevant insights will stream to each user based on their context, role or use.
These dynamic insights leverage technologies such as augmented analytics, NLP, streaming anomaly detection and collaboration.
#3 Decision Intelligence
Decision intelligence brings together a number of disciplines, including decision management and decision support. It encompasses applications in the field of complex adaptive systems that bring together multiple traditional and advanced disciplines.
Over 33% of large organizations will have analysts practising decision intelligence, including decision modelling by 2023
Also read: Gartner Marketing Data Analytics Survey reveals the unimpressive state of Analytics
#4 X Analytics
The rise of X Analytics, an umbrella term coined by Gartner, where X is the data variable for a range of different structured and unstructured content such as text analytics, video analytics, audio analytics, etc.
Data and analytics leaders could use X analytics to solve society’s toughest challenges of the present and future, including climate change, disease prevention and wildlife protection.
#5 Augmented Data Management
Augmented data management uses ML and AI techniques to optimize and improve operations. It also converts metadata from being used in auditing, lineage and reporting to powering dynamic systems.
Using the existing usage and workload data, an augmented engine can tune operations and optimize configuration, security and performance.
Gartner recommended data and analytics leaders to look for augmented data management enabling active metadata to simplify and consolidate their architectures.
Also read: Data is central to our decision-making: ANZ Bank
#6 The Cloud Imperative
As data and analytics moves to the cloud, Gartner recognised the importance of cloud as an important trend in 2022. By 2022, public cloud services will be essential for 90% of data and analytics innovation.
Leaders still struggle to align the right services to the right use cases, which leads to unnecessary increased governance and integration overhead.
Data and analytics leaders need to prioritize workloads that can exploit cloud capabilities and focus on cost optimization and other benefits, noted Gartner.
Also read: Gartner forecasts 6.3% growth in Public Cloud Services Market despite COVID
#7 The power of one: Data and Analytics converge
Data and analytics capabilities have traditionally been considered distinct capabilities and managed accordingly.
The convergence of data and analytics will increase interaction and collaboration between historically separate data and analytics roles, notes Gartner.
Vendors offering end-to-end workflows enabled by augmented analytics blur the distinction
This impacts not only the technologies and capabilities provided, but also the people and processes that support and use them.
Gartner recommends incorporating both data and analytics tools and capabilities into the analytics stack.
#8 Data Marketplaces and Exchanges
Data marketplaces and exchanges provide single platforms to consolidate third-party data offerings.
These marketplaces and exchanges provide centralized availability and access (to X analytics and other unique data sets, for example) that create economies of scale to reduce costs for third-party data.
By 2022, 35% of large organizations will be either sellers or buyers of data via formal online data marketplaces, up from 25% in 2020
#9 Blockchain in Data and Analytics
One of the major challenges in the world of data and analytics is data lineage. Blockchain can address this providing the full lineage of assets and transactions.
Ledger database management systems (DBMSs) will provide a more attractive option for single-enterprise auditing of data sources. By 2021, Gartner estimates that most permissioned blockchain uses will be replaced by ledger DBMS products.
Gartner recommended data and analytics should position blockchain technologies as supplementary to their existing data management infrastructure.
Also Read: Will Blockchain Become the Next ‘Game-Changer’ for the Insurance Industry?
#10 The Rise of Graph Analytics
Graph Analytics helps find unknown relationships in data
Graph analytics is a set of analytic techniques that allows for the exploration of relationships between entities of interest such as organizations, people and transactions.
By 2023, graph technologies will facilitate rapid contextualization for decision making in 30% of organizations worldwide.
