CIOs and their C-suite colleagues understand the value of data in helping to identify new business opportunities, create better experiences for customers, and improve decision making across the organization. Many also realize, however, that getting maximum value from their data requires a modern architecture that is no longer limited by the scale and cost of storing and analyzing large amounts of data.
In Episode 2 of the AWS-sponsored Ahead of the Pack podcast, host Tim Crawford talks with two experts on the building a modern data architecture: Herain Oberoi, Director of Databases, Analytics, and Blockchain Marketing with AWS, and Elliott Cordo, VP of Technology Insights with Equinox Media, part of the Equinox Group of lifestyle and fitness brands.
In the podcast, Oberoi emphasized the rapid gains that organizations can capture by moving away from legacy enterprise data warehouses to a more nimble cloud-based data lake architecture.
“Most organizations start with one or more data warehouses,” he said. “Once you start moving to a data lake architecture, you can start to break down the data silos and analyze the data in a variety of ways, such as real-time and operational analytics, that go beyond standard querying and reporting.”
The beauty of a data lake, Oberoi explained, is that because the data is stored in standards-based, open formats, you can analyze it in a variety of ways – including some that you may not have anticipated.
Cordo echoed the benefits around flexibility and efficiency. “Instead of relying on a single database platform or a data warehousing platform to solve all your problems, you’re assembling a series of tools and technologies to solve [individual] problems most efficiently,” he said.
Listen to the podcast to hear more insights on building a modern data architecture, including:
- How Equinox used a modern data ecosystem, including cloud-based data lakes and purpose-built databases, to quickly launch and scale a new digital fitness service
- Why the cloud is the “perfect” platform for data and analytics
- The concepts behind the AWS Data Flywheel approach