By Gerrit Kazmaier, EVP, SAP HANA & Analytics, SAP SE

The 2020 Data Warehouse - What to Expect

Data warehouses are a critical element to any enterprise's data management strategy and as we begin a new year, it will only become more vital. The concept of data warehousing has evolved over time to become more mature. For example, ten years ago, data was typically collected out of operational source systems and managed in a fairly structured way. Getting insights out of a classical data warehouse combined with a business intelligence (BI) application was much simpler back when data was "small." But today, enterprises manage big data in much more complex system environments. It's not about centralizing all data but rather the ability to connect to multiple storage systems used for different types of data without moving it.

In addition to growing complexity, the ways in which data is consumed have changed over the years as well. As businesses take a broader approach to data science and look to empower all business users to leverage insights, we can expect to see more companies using their data warehouse in innovative ways to democratize data in 2020.

A focus on data flow

To turn data into business value, businesses must change their approach. Instead of thinking in terms of specific tools, the focus should be on how data flows across multiple tools to provide an interconnected and consistent view of data across operations, customers, suppliers and employees. The storage, quality, and context of data can no longer be treated as isolated factors, but rather as integral, connected components of the data value chain. With this in mind, we can expect to see a new kind of platform that interprets data as part of this larger value chain in 2020. This model will be built upon the utilization of analytics and place increased emphasis on data connectivity vs. individual functions.

Having a data lake and a data warehouse in the cloud that can connect to other databases is the answer to creating a simpler path for all enterprise data to flow through. By adopting this model, enterprises will experience the benefits of unlimited storage at a minimal cost, flexible data lakes and high-performance data warehouses that enable real-time business analytics. As businesses pivot from applications that only address specific points of the data journey to integrated solutions that cover the entire journey, they will be able to greater harness the maximum value of data.

A democratized data science approach

As enterprises make this shift, they will also bring data science to other areas of the business, empowering more people to be involved. A democratized approach not only means that business users can leverage data-driven insights, it also makes them part of the data value chain, and will allow enterprises to experience better results from these types of projects in 2020.

While no-code technologies have already made it possible to automate advanced data science processes - meaning that even those users without technical knowledge can benefit from these tools - we expect to see more technologies for these types of users this year. Especially in advanced analytics and machine learning, the algorithms must be closely aligned with the business acumen of the users. The availability and versatility of tools for all skill levels will grow significantly, offering users help in a variety of ways, including scenario modeling, quality assessment, and operationalization.

For enterprises to experience more impactful results of data-driven approaches this year, it is crucial for them to consider the key parts of the data value chain: storage, quality, and context. Most importantly, they should also prioritize interconnectivity that is made possible by having a data warehouse in the cloud. For success in 2020, businesses should remember that without a comprehensive, secure, consistent, and fast data management system, essential data loses its value.

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About the Author

Gerrit Kazmaier is EVP, SAP HANA and Analytics with global responsibility for the development, product management, and solution management of these portfolios of solutions. As head of development, product management, and solution management for these two areas, he is responsible for building, innovating, and driving the market strategy for SAP’s flagship in-memory database platform SAP HANA as well as SAP’s Analytics solutions.