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Big Data Engineering for Machine Learning
How big data engines are used for exploring and preparing data, building pipelines, and delivering data sets to ML applications
Learn how we helped MiQ scale their data lake ecosystem to be on par with their company's growth
What is an Open Data Lake?
A data lake, where data is stored in an open format and accessed through open standards-based interfaces, is defined as an Open Data Lake.
Learn how we helped Gaia implement a data lake platform and migrate from a legacy data warehouse environment
TiVo shares best practices for ingesting, processing, and making available for analysis terabytes of streaming and batch viewership data from millions of households
Using Qubole Presto for Interactive and Ad-Hoc Queries
Tips for when to use Presto versus Apache Spark, and how to enable self-service access to your data lake
Modern Data Engineering and The Rise of Apache Airflow
Brief introduction to Apache Airflow, its optimal use cases, and real-world examples
Real-world data science practitioners offer perspectives and advice on six common Machine Learning problems
Migrating to a Modern Cloud-Native Data Lake with Microsoft Azure and Qubole
Benefits of migrating to a cloud-native data lake and how to choose the right data architecture
Enterprise-Scale Big Data Analytics on Google Cloud Platform
Why a unified experience with native notebooks, a command workbench, and integrated Apache Airflow are a must.
Why You Need a Cloud Platform to Succeed with Big Data
The benefits of a single cloud platform and centralized access to data
O'Reilly ebook: Operationalizing the Data Lake
Best practices for building a cloud data lake operation—from people and tools to processes
How to Increase the Scalability of HiveServer2 with Qubole
Technical overview of Qubole's HiveServer2 solution that distributes memory-intensive processes and enables scalability
1:24Data Science on Qubole Data Platform
The best tool for every task in the data science life cycle — in a single, cloud-native platform