Storing, processing, and moving data in the cloud efficiently and cost-effectively is a must for working with today’s enormous datasets. Data lakes answered the problem of silos found in many data warehouses. But as the pendulum swings back, there's a growing need for an additional solution that combines the strengths of both models, a need that’s led to the emergence of the data lakehouse. But with the number of data storage systems available, it can be hard to figure out which option is right for you.
In this event, you'll gain insights on how to increase the scalability, speed, and availability of your data, along with best practices for utilizing your data warehouse, data lake, or data lakehouse. Join in to learn how to make the right decisions for your particular use case.
What you’ll learn and how you can apply it
- Get an overview of the latest technologies for storing and managing your data
- Learn how to build a performant and scalable data lake
- Explore design considerations to make your data warehouse robust and reliable
- Discover the full management, storage, and analytics capabilities of a data lakehouse
- Understand how to apply data observability principles for your data lake
This course is for you because…
- You need to know the latest trends in storing, processing, and managing data.
- You want to improve the scalability, speed, and availability of your data.
- You work with a variety of data sources that need to be pulled together and analyzed.
- You want to better understand the systems that you already use and learn how to take full advantage of their capabilities.
Table of contents
- Welcome and Chris Messina: Keynote—Lakes, Streams, Tags, and Emergence
- Michael Armbrust: Keynote—Emergence of Open Data Lakehouse Architecture for Analytics and ML (Sponsored by Databricks)
- Rukmani Gopalan: Designing Scalable, Performant, and Secure Data Lakes for Your Enterprise
- Joyce Avila: Analyzing Data at Scale with a Cloud Data Warehouse
- Harshida Patel: Utilizing the Lake House for Data Storage and Analytics
- Victor Lee: Delivering Smarter AI with Analytical Graph Databases, Data Lakes, and Data Warehouses (Sponsored by TigerGraph)
- Barr Moses and Ryan Kearns: Data Observability—How to Build More Reliable Data Warehouses Lakes
- Paul Lacey: The Lakehouse—Connecting Data and Teams to Bridge the Information Gap (Sponsored by Matillion)
- Alicia Moniz: Extending Data Pipelines - Strategies for Getting Data to the Cloud Quickly
- Title: Strata Data Superstream Series: Data Warehouses, Data Lakes, and Data Lakehouses
- Release date: August 2021
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 0636920587064
You might also like
What is it about the top tech product companies such as Amazon, Apple, Google, Netflix, and …
Software development today is embracing events and streaming data, which optimizes not only how technology interacts …
Deep Learning for Vision Systems
How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers …
Data Architecture: From Zen to Reality explains the principles underlying data architecture, how data evolves with …