DataKitchen

AUGUST 8, 2023

Data Observability leverages five critical technologies to create a data awareness AI engine: data profiling, active metadata analysis, machine learning, data monitoring, and data lineage. Like an apartment blueprint, Data lineage provides a written document that is only marginally useful during a crisis. Are problems with data tests?

Data Quality 130

Data Quality Testing Snapshot Reporting 130

AWS Big Data

JUNE 5, 2023

If you also needed to preserve the history of DAG runs, you had to take a backup of your metadata database and then restore that backup on the newly created environment. Amazon MWAA manages the entire upgrade process, from provisioning new Apache Airflow versions to upgrading the metadata database. or v2.0.2, and higher environment.

Snapshot 73

Snapshot Metadata Testing Data-driven 73

Cloudera

JULY 14, 2023

They also provide a “ snapshot” procedure that creates an Iceberg table with a different name with the same underlying data. You could first create a snapshot table, run sanity checks on the snapshot table, and ensure that everything is in order. Hive creates Iceberg’s metadata files for the same exact table.

Snapshot 69

Snapshot Metadata Data Warehouse Testing 69

DataKitchen

JANUARY 23, 2023

DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data testing is an essential aspect of DataOps Observability; it helps to ensure that data is accurate, complete, and consistent with its specifications, documentation, and end-user requirements. Did it fail?

Testing 130

Testing Data Governance Data Quality Data-driven 130

AWS Big Data

NOVEMBER 16, 2023

Building a starter version of anything can often be straightforward, but building something with enterprise-grade scale, security, resiliency, and performance typically requires knowledge and adherence to battle-tested best practices, and using the right tools and features in the right scenario. system implemented with Amazon Redshift.

Enterprise 83

Enterprise Data Warehouse Snapshot Cost-Benefit 83

AWS Big Data

JUNE 9, 2023

It is crucial that you perform testing to ensure that a table format meets your specific use case requirements. Refer to Working with other AWS services in the Lake Formation documentation for an overview of table format support when using Lake Formation with other AWS services.

Data Lake 113

Data Lake Metadata Optimization Statistics 113

AWS Big Data

NOVEMBER 29, 2023

dbt lets data engineers quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, continuous integration and continuous delivery (CI/CD), and documentation. 05:34:22 Connection test: [OK connection ok] 05:34:22 All checks passed!

Data Lake 102

Data Lake Management Metrics Data Warehouse 102