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From Cloud Revolution to the Democratization of Data
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From Cloud Revolution to the Democratization of Data

From Cloud Revolution to the Democratization of Data

Three thought leaders explore how cloud technology is reshaping data architecture and revolutionizing analytics.

By Drew Fitzpatrick, June 10, 2021

The recent Modern Data Stack Conference EMEA kicked off with a dramatic-sounding claim: Data analytics is rapidly becoming as simple and reliable as electricity. The conference brings together data professionals from across Europe and adjacent regions to explore how a unified, cloud-based data stack can make analytics accessible to everyone. In the keynote, Fivetran VP of EMEA Nate Spohn explained that cloud technology — particularly automated data integration and cloud data warehouses — is driving advances in analytics.

Automated data integration allows organizations to easily centralize data from almost any source, he said, and cloud data warehouses offer extremely low-cost storage and dynamically scalable compute. Modern business intelligence tools make it easy to share insights and empower business users organization-wide.

This represents a massive leap forward from high-maintenance, on-prem data architecture. To discuss this shift and its implications, Spohn was joined by three leading thinkers in the data space: Bob Muglia, entrepreneur and former CEO of Snowflake; Alex Biller, VP of Platform at Snowflake; and Magnus Carlsson, Head of Innovation at Capgemini. 

Cloud Architecture Can Make Anyone a “Master of Data”

Bob Muglia picked up the theme of a big technological leap, stressing the degree to which limitations of scale in the old on-prem world had hobbled organizations. “They put data in silos because the system simply couldn't support what people were trying to do, and you had to break it up to do analytics,” he said.

Muglia described the critical components of the modern data stack:

  • Data warehouse or other destination in the cloud

  • Automated data pipeline to simplify extraction from a wide variety of data sources

  • Data transformation tool

  • Data visualization or business intelligence tool

“In the data warehouse, you do the transformations into the dimensional schema that's used for analytics,” Muglia explained. “In the modern data stack, this happens in the data warehouse instead in a proprietary ETL tool, and it happens with SQL and tools like dbt.”

The MDS enables broad democratization of data, Muglia said. Data teams can work with different sources without any specialized engineering expertise: “Five years ago, a few companies in Silicon Valley could do this. Now, because of cloud breakthroughs, everyone has the capabilities to be a master of data.”

A Critical Tool in the Data Age

The modern data stack has become a critical tool as data volumes have exploded, according to Alex Biller of Snowflake. Before the advent of cloud data warehouses, organizations tried to cope with high costs and a lack of scale by creating data lakes and data marts in addition to data warehouses. “All of a sudden, the central source of truth is living in three different places,” Biller said. “When you start making things more complicated, it just slows down time to value.”

Cloud-based analytics offers back-to-basics simplicity, Biller noted. He recommends tools that are intuitive to use and part of a tightly integrated data stack. Regardless of whether you’re integrating big or small data, or structured or unstructured data, the priority must be to quickly get to the point where you start accessing the data for insights — not wasting time and resources managing the processes around analytics. 

“A modern data stack has one set of code,” Biller said. “It is very easy to use — and it works for all the different sources that an organization has. The way that organizations move forward is to be able to literally click one button and start syncing their data and have it available for analysis within minutes.”

A Platform for Future Possibilities 

There was a consensus among the keynote speakers that the modern data stack will accelerate new business models and open up market opportunities. Capgemini’s Magnus Carlsson expects that it will allow many more organizations to monetize their data, as well as spurring advances in virtualization that will help move data around more easily.

Alex Biller predicts new partnerships. He gave the example of carmakers sharing GPS and cellular data from connected vehicles with telcos to help improve network coverage. “I'm really excited at the partnerships we're seeing and the connections between organizations that can be made by using data that lives outside of their own four walls,” he said. 

Nate Spohn of Fivetran summed up the big benefit of modern data stacks for most companies — the accelerated journey to becoming truly data-driven. “Almost anybody across an organization will be able to ask a question of data and get the answer almost immediately,” he said. “It can very significantly shift a culture when you are no longer battling about differing opinions and you have the data in front of you.”

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