Data has taken center stage in almost every business – driving critical business decisions and providing the foundation for better customer experiences. Behind the scenes is the modern data stack – helping companies extract data from various sources and transform that data into analytics and insights.
But as many businesses struggle with economic uncertainty, AI tools advance in leaps and bounds and the cloud continues to dominate, what does the future of the data stack look like – and how will it adapt or evolve?
In this article, Martin Casado, General Partner at Andreessen Horowitz, Matt Arellano, Managing Director with Accenture and George Fraser, CEO of Fivetran, weigh in on the biggest challenges and opportunities facing the data world in 2023.
In good times and bad, data creates a competitive advantage
Data can play a different role in good times and bad times, but what's become clear is that data is essential to the health of any company. In today's economic climate, businesses need data to make more effective decisions around hiring, supply chains, customer experience, operations and more.
"If you look at the macroeconomics and what's going on across every industry, your decisions today need to be data focused and data bound," says Arellano. "[Data] gives you the retrospective understanding of what's happening but also allows you to make some predictions with confidence on what you should be doing in the future."
Data also enables differentiation in the marketplace, which is critical during economic uncertainty. "Data underlies differentiation between companies," says Casado. "As companies are trying to jostle for a position, [data] is the primary way they do so."
Ongoing data stack investments remain essential
Becoming data-driven often involves an investment in technology, and the most integral and valuable tools are often automated and involve moving huge amounts of data from applications and databases to cloud-based destinations for advanced analytic capabilities.
"It isn't risky anymore," adds Casado. “If you're not on [the modern data stack], you're probably becoming a laggard."
According to Fivetran CEO George Fraser, he's seeing larger companies connecting more data sources than previously. “In hard economic times, one of the ways that people are value engineering is by replacing data pipelines that are built and maintained in-house at great cost with automated data pipelines provided by Fivetran,” says Fraser.
Regardless of company size, investment in data should remain a priority.
"If you have a dollar to spend and 30 cents goes to data, and then you have 50 cents to spend, the same proportions should still go to data if not more in these contraction times," Casado explains.
The continued acquisition of more data sources is essential, especially in leaner economic times, as business leaders need data at their fingertips to be able to make very short-term decisions to pivot the business either for cash optimization or growth purposes.
Building new data-driven solutions
The modern data stack is becoming central to software development and how applications are built. This is due to the rise of the cloud data warehouse, which is one of the great epochs allowing companies to take all of their data and put it in one place.
There are now cloud data warehouse native applications, where the application is plugging into the data from various different APIs using a tool like Fivetran.
"It’s becoming table stakes to build these applications with the proper infrastructure from a cloud perspective, but the proper pipelining processes and ultimately the people around are also important,” says Arellano.
Fraser notes that about 10 percent of Fivetran's customers use Fivetran primarily through the API. “They're using it as a building block in something else. We have customers where Fivetran's data movement is really fundamental to their business, so much so that if the pipeline were to go down, they just could not operate.”
What the modern data stack makes possible
In today’s digital and data-first world, the modern data stack provides a more suitable tooling infrastructure for the amounts of data and the types of initiatives companies want to do on top of data than traditional or legacy data tools.
“You can view the modern data stack almost as you would view a software engineering discipline,” says Casado. He sees the primary benefit of the modern data stack as the differentiation it enables as businesses today must compete on what they extract from data — everything from pricing to fraud to customer identity matching.
“My team sees maybe 3,000 companies a year and the way that they differentiate is how they manage their data,” says Casado. “When the modern data stack is implemented, you're in a position to just worry about what the data says and not all of the mechanics to get you there. And once that happens, it opens up an entirely new discipline on what you can pull from to differentiate.”