Data Strategy Trends For 2021 Everyone Need To Know

2020 unexpectedly presented many companies with new challenges: How do I adapt my IT infrastructure to the change to remote working? How do I provide employees with all the necessary information? How do I optimize the flow of data in order to make the right decisions for the future in uncertain times?

Spread of the AI-supported data fabric

The pandemic made it clearer than ever that the provision of information for business needs to be accelerated significantly. However, this can often no longer be achieved with conventional data integration methods. The integration of new data sources into heterogeneous infrastructures is becoming increasingly complex and it simply takes too long before new queries can be made available to data consumers. Against this background, more and more companies are turning away from traditional data architectures and relying on more agile forms of data integration, such as those of the logical data fabric. This concept stands for seamless data integration in heterogeneous environments as well as the fast provision of information for the business.

This trend will consolidate in 2021 and more and more organizations will pursue a holistic data strategy. The concept of the data fabric, in particular, will play an important role here. These agile architectures enable reliable real-time data flow without physical replication of the data. In addition, the implementation of AI technologies in the data fabric will continue to establish itself in order to ensure more automation, especially in the areas of data discovery, performance optimization, and workload management.

Cloud integration instead of cloud migration

Most companies are now in the cloud migration phase: more than 60 percent of organizations use the cloud and 25 percent are even pursuing a cloud-first approach, according to a current study. In the context of the Covid-19 pandemic, this trend has intensified and many companies have recognized the advantages of cloud computing. So far, the focus has been on the migration of data to the cloud. Although this approach promises success, it can lead to so-called “technical debts” – that is, negative consequences due to insufficient technical implementation of software – because the new systems are often only very loosely docked to the existing IT infrastructure.

In 2021 the focus will shift from pure migration to full integration of the cloud into the data strategy. Gone are the days of trying to physically consolidate all data in one place: Given the sheer volume and heterogeneity of the data, this seems out of date. Rather, modern architectures such as the logical data warehouse or the logical data fabric promise seamless integration of all company data without physical replication. Complex access authorizations can be managed centrally and securely and the data can be made available to the business in real-time for analysis.

Monetization of data

The best possible use of data for advanced analytics to derive strategic recommendations for action is already a high priority for most organizations. For this purpose, investments are made in the modernization of data architectures in order to supply the data consumers from the business with the required data sets.

In 2020, the pandemic made us realize the importance of having quick access to accurate and complete data in order to make the right decisions. Many large companies therefore already have valuable data services in place. In 2021 we will observe that more and more companies are providing their data services and, on the other hand, including 3rd party data services in their own analytics.

For example, geolocation data can already be obtained from telecommunications companies, financial companies offer information on the valuation of financial assets, and companies in the real estate sector sell statistics on the housing market. This trend of monetizing data will spread to other industries and sectors in 2021. From a technological point of view, the need for data-as-a-service tools, such as GraphQL, data virtualization, or API management tools, will therefore increase.

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