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TDWI Upside - Where Data Means Business

The 2020 Superpower: Data

Data will have a greater impact on an enterprise's bottom line in 2020. These three trends are leading the way.

The 1982 film Blade Runner was set 37 years in the future -- at the end of 2019. As we head into 2020, we can say with confidence that the film correctly predicted virtual home assistants and video calls, but didn't quite get it right with flying cars.

For Further Reading:

Guided Analytics and the Future of Data Science in the Enterprise

How and Why Your Enterprise Should Democratize Data Science

3 Major Decisions When Choosing Your Data Platform

Both on and off screen, predictions of what new technologies could arrive, what could turn mainstream, and what could disappear are always interesting to read (and, of course, to compare with reality at a later date). Looking ahead to the new year, what trends can we expect to see in the world of data and analytics?

2020 Trend #1: Enterprises will recognize the real value of data

Data has often been described as "the new oil." Without doubt, it is an incredibly powerful resource, and one that provides us with great potential. Through correlations and causality chains, we can gain a better understanding of the world around us. Data-driven automation allows us to focus on tasks with higher value, ultimately generating more impact by doing what matters most.

However, data tells us about the world as it is -- not what it could or should be. As we become more aware of what data can and can't do, we also gain a better understanding of where its true value lies. In 2020, we can expect to see people look at the value of data in new ways. Ultimately, data can only show us what is and as such, it can only take us so far in the decision-making process.

2020 Trend #2: Data science is made available to new users

Data and data science do not exist in isolation and must always be grounded in a strong understanding of the wider context of the organization. By democratizing the technology and opening up the data science process to also incorporate the business and subject-matter experts, we can expect to see stronger and more impactful outcomes of these projects.

Next year, the range of products that focus on helping business users find the ideal way to model a scenario, understand the algorithms in action, and how the result can be productively used will grow. Being a data-driven organization will become a realistic option for companies of all sizes and industries thanks to new tools that open up the world of data science to nonexperts. New no-code technologies, for example, have automated many of the more sophisticated data science processes, making data science tools easier to use even for those without a background in programming.

The simpler and more ubiquitous it becomes, the more people can take advantage of the technology. Building models and running algorithms will become part of the business user's domain. We will see more products that leverage automatically trained models to generate forecasts and find correlations to automate standard analytics processes.

2020 Trend #3: A new data platform emerges

This year, we'll see a new type of data platform emerge that understands data in terms of a value chain that covers data management, quality, storage, and ultimately its consumption in analytics. With a clear shift in focus from individual functions to data connectivity, enterprises will start to move away from isolated, special-purpose applications that address specific points of the data journey towards an integrated, interconnected set of solutions that span the entire data value chain.

Data can only help us make decisions with confidence if we can:

  • Understand how we can source data at scale regardless of where it comes from
  • Store and process the data regardless of size
  • Build reusable data assets and define their semantics to make them understandable to nontechnical users.
  • Allow these assets to be used by and provide insights to everyone, not just data scientists and IT professionals

The solutions that form this chain might be from one vendor or multiple providers. Regardless of the company behind the technology, each element of the chain must be optimized to deliver the value of the data. Even the best analytics solutions cannot provide accurate results if the quality of the data is in doubt.

Ultimately, this shift in the way we think about data and its connectivity will open up new possibilities for its use and the value we can derive from it. Far from being an idea restricted to the world of science fiction, we can use the data at our disposal and transform it into a "superpower" that allows everyone to see more, understand more, do more, and, best of all, have a greater business impact.

About the Author

Gerrit Kazmaier is EVP for SAP HANA and Analytics. In this role, he is responsible for the development and market strategy of SAP’s database, data management, and analytics solution portfolio. After winning the prestigious SAP Hasso Plattner Founders’ Award in 2014 with his team for the creation of a high-performance spatial engine in SAP HANA, Kazmaier went on to lead the software development of a new generation of analytics and data management solutions for the cloud. You can reach the author on Twitter and LinkedIn.


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