Ontotext

FEBRUARY 12, 2024

It also breaks down the code and data monolith and distributes it across the domain teams, which results in better management and scalability. The data mesh concept will mitigate cognitive overload when building data-driven organizations that require intense technical, domain, and operational knowledge.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

AWS Big Data

NOVEMBER 9, 2023

It does this by helping teams handle the T in ETL (extract, transform, and load) processes. It allows users to write data transformation code, run it, and test the output, all within the framework it provides. As part of their cloud modernization initiative, they sought to migrate and modernize their legacy data platform.

Data Warehouse 104

Data Warehouse Testing Data Quality Reporting 104

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. Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack.

Data Lake 85

Data Lake Analytics Snapshot Optimization 85

Ontotext

MARCH 27, 2024

They also don’t have features for enterprise data management such as schema language, data validation capabilities, interoperable serialization formats, or a proper modeling language. RDF is used extensively for data publishing and data interchange and is based on W3C and other industry standards.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

DataKitchen

JANUARY 23, 2023

Data lineage and a data catalog are better together because they provide a more complete and accurate view of the data. It allows organizations to see how data is being used, where it is coming from, its quality, and how it is being transformed.

Testing 130

Testing Data Governance Data Quality Data-driven 130

IBM Big Data Hub

FEBRUARY 9, 2023

In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture. Don’t try to do everything at once!

Data Governance 84

Data Governance Business Objectives Strategy Data Quality 84

Sisense

AUGUST 28, 2020

Uncomfortable truth incoming: Most people in your organization don’t think about the quality of their data from intake to production of insights. However, as a data team member, you know how important data integrity (and a whole host of other aspects of data management) is.

Data Integration 101

Data Integration Testing Data Quality Data-driven 101