Sisense

AUGUST 28, 2020

We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways data teams are tackling the challenges of this new world to help their companies and their customers thrive. What is data integrity?

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

DataKitchen

DECEMBER 20, 2020

The DataOps Engineering skillset includes hybrid and cloud platforms, orchestration, data architecture, data integration, data transformation, CI/CD, real-time messaging, and containers.

Data-driven 147

Data-driven Manufacturing Data Architecture Data Analytics 147

Ontotext

MARCH 27, 2024

Poor data modeling capabilities of LPGs with vendor specific constructs to express semantic constraints hinders portability, expressibility, and semantic data integration. It accelerates data projects with data quality and lineage and contextualizes through ontologies , taxonomies, and vocabularies, making integrations easier.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. This ensures that the data is suitable for training purposes. These robust capabilities ensure that data within the data lake remains accurate, consistent, and reliable.

Data Lake 85

Data Lake Analytics Snapshot Optimization 85

DataKitchen

JANUARY 23, 2023

Like an apartment blueprint, Data lineage provides a written document that is only marginally useful during a crisis. This is especially true in the case of the one-to-many, producer-to-consumer relationships we have on our data architecture. Are problems with data tests? They measure data sets at a point in time.

Testing 130

Testing Data Governance Data Quality Data-driven 130