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.

Metadata 52

Metadata Management Business Intelligence Data Governance 52

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. Monitoring Job Metadata. Monitoring and tracking is an essential feature that many data teams are looking to add to their pipelines. Second, you must establish a definition of “done.”

Testing 157

Testing Metadata Dashboards Statistics 157

Octopai

JUNE 15, 2020

Business intelligence databases are dynamic repositories that must often be adjusted based on organizational and or regulatory requirements. With the insurance company’s current data architecture, the process would have no chance of being completed in time for the change. Download the webinar.

Insurance 52

Insurance Metadata Business Intelligence Data Warehouse 52

CIO Business Intelligence

JUNE 23, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes. Cloud Management

Data Lake 85

Data Lake Data Warehouse Machine Learning Cost-Benefit 85

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 90

Data Lake Data Warehouse Machine Learning Cost-Benefit 90

Cloudera

AUGUST 30, 2022

Modern data architectures. To eliminate or integrate these silos, the public sector needs to adopt robust data management solutions that support modern data architectures (MDAs). Deploying modern data architectures. Lack of sharing hinders the elimination of fraud, waste, and abuse. Forrester ).

Data Architecture 76

Data Architecture Data Lake Metadata Data Warehouse 76

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