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.

Testing 130

Testing Data Governance Data Quality Data-driven 130

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale. This post is not intended to provide detailed technical guidance (e.g.

Data Lake 115

Data Lake Metadata Optimization Statistics 115

AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. We begin with a Data lake reference architecture followed by an overview of operational data processing framework.

Data Lake 93

Data Lake Data Processing Metadata Snapshot 93

AWS Big Data

APRIL 3, 2024

By analyzing the historical report snapshot, you can identify areas for improvement, implement changes, and measure the effectiveness of those changes. In our example, we have configured a ruleset against a table containing patient data within a healthcare synthetic dataset generated using Synthea.

Data Quality 91

Data Quality Visualization Metadata Metrics 91

AWS Big Data

OCTOBER 18, 2023

Choose Test connection to verify that AWS SCT can connect to your source Azure Synapse project. Choose Test connection to verify that AWS SCT can connect to your target Redshift workgroup. When the test is successful, choose OK. Select Use SSL to encrypt AWS SCT connection to Data Extraction Agent. Choose Test connection.

Analytics 98

Analytics Data Warehouse Testing Dashboards 98