A data lake is the fastest way to get answers from all your data to all your users. It’s a centralized repository that allows you to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data, and run different types of analytics—from dashboards and visualizations to big data processing, real-time analytics, and machine learning—to guide better decisions.
In This Issue
In this month’s Architecture Monthly, we speak to AWS Analytics Tech Leader, Taz Sayed, about general architecture trends in data lakes, the questions customers need to ask themselves before considering a data lake, and we get his outlook on the role the cloud will play in future development efforts.
We also introduce you to two companies that are utilizing data lakes for deep analytics, point you to an AWS managed solution, provide some real-world videos, and more.
- Ask an Expert: Taz Sayed, Tech Leader, AWS Analytics
- Blog: Kayo Sports builds real-time view of the customer on AWS
- Case Study: Yulu Uses a Data Lake on AWS to Pedal a Change
- Solution: Data Lake on AWS
- Managed Solution: AWS Lake Formation
- Whitepaper: Building Big Data Storage Solutions (Data Lakes) for Maximum Flexibility
How to Access the Magazine
- Readers in the US, UK, Germany, and France can subscribe to the Kindle version of the magazine at Kindle Newsstand.
- View and download past issues as PDFs on the AWS Architecture Monthly webpage.
- Visit Flipboard, a personalized mobile magazine app that you can also read on your computer.