Octopai

APRIL 19, 2021

Aptly named, metadata management is the process in which BI and Analytics teams manage metadata, which is the data that describes other data. In other words, data is the context and metadata is the content. Without metadata, BI teams are unable to understand the data’s full story. Dataconomy.

Metadata 52

Metadata Management Business Intelligence Data Governance 52

DataKitchen

OCTOBER 11, 2021

Monitoring Job Metadata. Monitoring and tracking is an essential feature that many data teams are looking to add to their pipelines. Figure 7 shows how the DataKitchen DataOps Platform helps to keep track of all the instances of a job being submitted and its metadata. About the Author. Priyanjna Sharma.

Testing 157

Testing Metadata Dashboards Statistics 157

Rita Sallam

JULY 22, 2016

By contrast, traditional BI platforms are designed to support modular development of IT-produced analytic content, specialized tools and skills, and significant upfront data modeling, coupled with a predefined metadata layer, is required to access their analytic capabilities. You can see it On Demand here. Moving to Modern.

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

Jet Global

MAY 1, 2023

Learn how embedded analytics are different from traditional business intelligence and what analytics users expect. Embedded Analytics Definition Embedded analytics are the integration of analytics content and capabilities within applications, such as business process applications (e.g., that gathers data from many sources.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52