phData

AUGUST 10, 2023

The implementation of a data vault architecture requires the integration of multiple technologies to effectively support the design principles and meet the organization’s requirements. Data Acquisition: Extracting data from source systems and making it accessible. as well as calculating business keys.

SQL 52

SQL Data Observability Data Quality Data Pipeline 52

DagsHub

AUGUST 23, 2024

Datafold is a tool focused on data observability and quality. It is particularly popular among data engineers as it integrates well with modern data pipelines (e.g., Source: [link] Monte Carlo is a code-free data observability platform that focuses on data reliability across data pipelines.

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

IBM Journey to AI blog

JULY 3, 2024

This includes integration with your data warehouse engines, which now must balance real-time data processing and decision-making with cost-effective object storage, open source technologies and a shared metadata layer to share data seamlessly with your data lakehouse.

AI 45

AI AI Data Quality Database 45

Precisely

JULY 12, 2024

Data integrity is based on four main pillars: Data integration : Regardless of its original source, on legacy systems, relational databases, or cloud data warehouses, data must be seamlessly integrated in order to gain visibility into all your data in a timely fashion.

Data Quality 105

Data Quality Data Governance Database Analytics 105

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 example, a data steward can filter all data by ‘“endorsed data’” in a Snowflake data warehouse, tagged with ‘bank account’.

Data Quality 98

Data Quality Data Governance ETL Data Observability 98

Alation

FEBRUARY 8, 2022

Signals around the quality and integrity of the data are essential if people are to understand and trust it. Data provenance and lineage, for example, clarify an asset’s origin and past usages, important details for a newcomer to understand and trust that asset. Self-describing. Plane 3: Mesh Supervision Plane.

Data Governance 52

Data Governance Data Engineering Data Engineer Data Engineering 52

Precisely

OCTOBER 16, 2023

The cloud is especially well-suited to large-scale storage and big data analytics, due in part to its capacity to handle intensive computing requirements at scale. BI platforms and data warehouses have been replaced by modern data lakes and cloud analytics solutions.

Analytics 72

Analytics Analytics Big Data Analytics Big Data Analytics 72