AWS Big Data

APRIL 20, 2023

Apache Spark is a popular framework that you can use to build applications for use cases such as ETL (extract, transform, and load), interactive analytics, and machine learning (ML). Amazon Redshift integration for Apache Spark helps developers seamlessly build and run Apache Spark applications on Amazon Redshift data.

Data Lake 73

Data Lake Data Warehouse Sales Data-driven 73

AWS Big Data

APRIL 19, 2023

Many customers run big data workloads such as extract, transform, and load (ETL) on Apache Hive to create a data warehouse on Hadoop. To configure AWS CLI interaction with AWS, refer to Quick setup. He is passionate about big data and data analytics. Apache Hive has performed pretty well for a long time.

Metadata 76

Metadata Testing Data Lake Consulting 76

AWS Big Data

APRIL 30, 2024

It can generate data integration jobs for extracts and loads to S3 data lakes including file formats like CSV, JSON, and Parquet, and ingestion into open table formats like Apache Hudi, Delta, and Apache Iceberg. Configure an IAM role to interact with Amazon Q.

Data Integration 99

Data Integration Data Lake Data Warehouse Software 99

Domino Data Lab

APRIL 3, 2019

Most of the data management moved to back-end servers, e.g., databases. So we had three tiers providing a separation of concerns: presentation, logic, data. Note that data warehouse (DW) and business intelligence (BI) practices both emerged circa 1990. We keep feeding the monster data. There are models everywhere.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Cloudera

DECEMBER 12, 2018

After having rebuilt their data warehouse, I decided to take a little bit more of a pointed role, and I joined Oracle as a database performance engineer. I spent eight years in the real-world performance group where I specialized in high visibility and high impact data warehousing competes and benchmarks.

Data Warehouse 42

Data Warehouse Marketing Big Data Data Lake 42