2022 trends commentary from Denodo


Trend #1: Data fabric becomes the foundation for the distributed enterprise.

As digital business and online sales channels proliferate and remote work becomes the norm, it will create a complex and diverse ecosystem of devices, applications, and data infrastructure. In particular, data infrastructure will span on-premises, single cloud, multi-cloud, hybrid-cloud, or a combination of these, spread across regional boundaries with no single solution to knit this data together.

This is why, in 2022, we will see organisations continuing to refine their data integration capabilities and  create a data fabric to drive enterprise-wide data and analytics. It will also be used to automate many of the data exploration, ingestion, integration, and preparation tasks. By enabling organisations to choose their preferred tools, these data fabrics will reduce time-to-delivery and make it a preferred data management approach in the coming year.


Trend #2: Decision intelligence makes inroads for enterprise-wide decision support.

Organisations have been acquiring vast amounts of data and need to leverage that information to drive business outcomes. Decision intelligence is making inroads across enterprises, as regular dashboards and Business Intelligence (BI) platforms are augmented with AI/ML-driven decision support systems.

In 2022, decision intelligence has the potential to make assessments better and faster, given machine-generated decisions can be processed at speeds that humans simply cannot. The caveat – machines still lack consciousness and do not understand the implications of the decision outcome. Look for organisations to incorporate decision intelligence into their BI stack to continuously measure the outcome to avoid unintended consequences by tweaking the decision parameters accordingly.


Trend #3: Adoption of Data Mesh structures and the use of “Data Products”.

As organisations grow in size and complexity, central data teams will be forced to deal with a wide array of functional units and associated data consumers. This will make it difficult to understand the data requirements for all cross-functional teams and offer the right set of “data products” to their consumers. Data mesh is a new decentralised data architecture approach for data analytics that aims to remove bottlenecks and take data decisions closer to those who understand the data.

In 2022 and beyond, larger organisations with distributed data environments will implement a data mesh architecture to minimise data silos, avoid duplication of effort, and ensure consistency. Data mesh will create a unified infrastructure enabling domains to create and share data products while enforcing standards for interoperability, quality, governance, and security. It will drive more self-service data infrastructures and an increasing use of models using Data-as-a-Service.


Trend #4: Organisations embrace composable data and analytics to empower data consumers.

Monolithic architectures are already a thing of the past, but next year we can expect even smaller footprints. As global companies deal with distributed data across regional, cloud and data centre boundaries, consolidating that data in one central location is no longer practical. That’s where composable data architecture becomes paramount and brings agility to data infrastructure. Data management infrastructure is extremely diverse and usually every organisation uses multiple systems or modules that together constitute their data management environment. Being able to build a low-code, no code data infrastructure provides flexibility and user friendliness, as it empowers business users to put together their desired data management stack and makes them less dependent on IT.

In 2022, expect organisations to accelerate building composable data and analytics environments that can bring faster business value and outcomes.


Trend #5: Small and wide data analytics begin to catch on

AI/ML is transforming the way organisations operate, but to be successful, it is also dependent on historical data analytics, aka big data analytics. While big data analytics is here to stay, in many cases this old historical data continues to lose its value.

In 2022, organisations will leverage small data analytics to create hyper-personalised experiences for their individual customers to understand customer sentiment around a specific product or service within a short time window. While wide data analytics is comparatively a new concept and yet to find widespread adoption – given the pace at which organisations are making use of unstructured and structured data together – expect to see small and wide data analytics to gain better traction across organisations as we enter 2022.


Trend #6: Further adoption of Cloud

In 2022, we can expect to see cloud adoption increase even further. This should come as no surprise, given recent research found that the percentage of organisations moving advanced workloads to the cloud has increased 25% year-on-year.

Despite cloud’s increasing prevalence and widespread adoption, many organisations are still facing some challenges, specifically around data being stored in multiple locations. The traditional integration approach of consolidating all data in the same location is no longer feasible because of the large data volumes involved and the diversity of the data processing mechanism.

Next year, the focus of cloud projects will shift to integration. Building a unified infrastructure to access and manage data across multiple locations will become a priority. Therefore, companies will turn to visualised data infrastructure to support vendor agnostic architectures. This will enable businesses to be more agile in the long term.