Best practices for building a cloud data lake operation—from people and tools to processes
Other content in this Stream

Qubole's native connector for Tableau simplifies BI on any data lake, delivering unparalleled response time with optimized Presto.

Introduction Qubole provides powerful automation that optimizes underlying cloud compute management for data lakes. Qubole cluster management continuously optimizes both performance and cost by...

Learn more about Workload-Aware-Auto-Scaling-- an alternative architectural approach to Auto-Scaling that is better suited for the Cloud and applications like Hadoop, Spark and Presto.

How to make all of your data available to users for a multitude of use cases, ranging from analytics to machine learning and artificial intelligence.

TiVo shares best practices for ingesting, processing, and making available for analysis terabytes of streaming and batch viewership data from millions of households

USA Today publisher Gannet cut costs thanks to Qubole’s autoscaling and downscaling capabilities, and the ability to isolate workloads to separate clusters

Ibotta cut costs thanks to Qubole’s autoscaling and downscaling capabilities, and the ability to isolate workloads to separate clusters.

Which vendors rank highest in customer satisfaction for big data processing

Best practices for working with different datasets, and when to use Apache Spark, Presto and other engines

How companies address common big data challenges and gain greater value from their data

How to support more data and users with fewer resources in this free ebook

Learn all about the differences between data lakes and data warehouses

Analyze predetermined data sets as well as discover, query, and visualize virtually any type of data

The Denver Data Engineering meetup will be hosted at the Ibotta office and feature speakers from Ibotta, Snowflake, and Qubole. Our speakers will be discussing the prevalence of cloud computing and it