Explore how data lakes drive decisions with Mai-Lan Tomsen Bukovec and Tomer Shiran

“Fundamentally, every business today is a data business.”

– Mai-Lan Tomsen Bukovec

In today’s interconnected and digital world, businesses must make decisions quickly, and they must be right. To stay competitive, companies have to leverage data lakes as the foundation for agile business decision making, analytics, and even AI/ML decisions. At the core of this is Amazon S3, which has more data lakes at-scale than any other cloud provider and has enabled numerous companies to succeed in the cloud. Recently, Mai-Lan Tomsen Bukovec (Vice President, Block and Object Storage, AWS) sat down with Tomer Shiran (Founder and CPO, Dremio) to discuss how enterprises have leveraged data lakes built on Amazon S3 to drive innovation.

Innovation through Amazon S3 data lakes

A timely example of data lake-driven innovation is how quickly Moderna developed their mRNA vaccine for COVID-19. Bringing a new drug to the market can take decades and often costs hundreds of millions, if not billions, of dollars in research and development (R&D). New drugs require screening thousands of compounds before testing and rigorous FDA approvals. Moderna runs their entire drug design studio on AWS Compute and AWS Storage infrastructure. With an AWS architected design studio, Moderna was able to use machine learning to rapidly test multiple mRNA sequences, optimizing them for production and testing.

Another powerful example is how AWS Partner Vyaire was able to quickly scale to meet unprecedented demand for ventilators during 2020. At the outset of the pandemic, Vyaire saw a 20x increase in order volume after being contacted by the US government. They had to innovate on the spot, scaling their production from 30 ventilators per week to over 600 per day, which required a highly customized manufacturing process. To do this, Vyaire leveraged their recently built Amazon S3 data lake and analytics infrastructure on AWS to quickly analyze ventilator quality in real-time, ensuring quality control while meeting increased demand.

Highlighting Amazon S3’s versatility across multiple industries, Domino’s Pizza Enterprises Limited is another example of a company that innovates using an Amazon S3 data lake. Dominos rapidly built predictive technologies to reduce pizza making and delivery times to make it easier for customers to get their food takeout and delivery quickly. To do this, they leveraged Amazon SageMaker and critical order-data stored in an Amazon S3 data lake to predict the likelihood of food orders. This enabled stores to begin predictively making orders without waste or product getting stale before delivery, an unbelievable feat compared to processes even 1–2 years ago.

At the core of each of these three company’s data lake is Amazon S3. Beyond that, each company can leverage a wide variety of analytic tools to unlock insights in their data. IDC says that digital data is growing at a rate of 40% year over year. Solutions like Dremio are critical to successfully querying and taking action on the data in these data lakes – helping you shrink decision-making time from weeks to minutes.

Conclusion

So what are the next steps? It all starts with putting that first dataset in the cloud. This creates a virtuous flywheel effect, where companies add more datasets that drive additional insights and spark further innovation. If you’re interested in learning more about how Dremio enables lightning fast queries on AWS data lakes, watch this video to hear Tomer Shiran (Founder and CPO, Dremio) and Mai-Lan Tomsen Bukovec (Vice President, Block and Object Storage, AWS) discuss emerging trends in data lakes and how they enabled rapid business transformation.

Thanks for reading this post about digital transformation with data lakes built on AWS. If you have any thoughts or questions, leave them in the comments section or begin your own data lake transformation with Dremio for AWS.