AWS Big Data

APRIL 3, 2024

Data engineers use Apache Iceberg because it’s fast, efficient, and reliable at any scale and keeps records of how datasets change over time. Apache Iceberg offers integrations with popular data processing frameworks such as Apache Spark, Apache Flink, Apache Hive, Presto, and more.

Data Lake 96

Data Lake Snapshot Metadata Data Architecture 96

AWS Big Data

APRIL 25, 2024

As the queries finish running, an UNLOAD operation is invoked from the Redshift data warehouse to the S3 bucket in Account A. The pipeline then starts running stored procedures and SQL commands on Redshift Serverless.

Metadata 106

Metadata Data Processing Management Testing 106

AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 115

Data Lake Analytics Dashboards Metrics 115

AWS Big Data

MARCH 11, 2024

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, straightforward, and secure analytics at scale. Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the most widely used cloud data warehouse.

Analytics 65

Analytics Data Warehouse Optimization Metrics 65

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. We keep feeding the monster data.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Domino Data Lab

JULY 22, 2019

He also really informed a lot of the early thinking about data visualization. It involved a lot of interesting work on something new that was data management. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. Then we roll out a decade later.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109