Pickl AI

OCTOBER 11, 2023

Data Observability and Data Quality are two key aspects of data management. The focus of this blog is going to be on Data Observability tools and their key framework. The growing landscape of technology has motivated organizations to adopt newer ways to harness the power of data.

Data Observability 52

Data Observability Data Quality Data Pipeline Data Governance 52

Alation

MAY 24, 2022

This has created many different data quality tools and offerings in the market today and we’re thrilled to see the innovation. People will need high-quality data to trust information and make decisions. For instance, via lineage, analysts can understand if upstream data dependencies have reliable data quality. “At

Data Quality 98

Data Quality Data Governance ETL Data Observability 98

IBM Journey to AI blog

DECEMBER 16, 2022

It seamlessly integrates with IBM’s data integration, data observability, and data virtualization products as well as with other IBM technologies that analysts and data scientists use to create business intelligence reports, conduct analyses and build AI models.

Data Quality 52

Data Quality Data Governance Data Wrangling Data Scientist 52

ODSC - Open Data Science

DECEMBER 3, 2024

Understanding data mesh Data mesh is a decentralized architecture type that allows different departments to access data independently. It’s different from traditional data architecture, which usually has dedicated data engineering teams that provide access to information after other departments request it.

Data Pipeline 40

Data Pipeline Data Governance Data Analyst Data Observability 40

Pickl AI

JUNE 7, 2024

Integration: Airflow integrates seamlessly with other data engineering and Data Science tools like Apache Spark and Pandas. Scalability: It is suitable for enterprise-level data integration needs, offering scalability for handling large datasets efficiently. Read More: Advanced SQL Tips and Tricks for Data Analysts.

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40