Octopai

JUNE 26, 2020

Steve, the Head of Business Intelligence at a leading insurance company, pushed back in his office chair and stood up, waving his fists at the screen. We’re dealing with data day in and day out, but if isn’t accurate then it’s all for nothing!” Enterprise data governance. Metadata in data governance.

Metadata 84

Metadata Data Governance Enterprise Reporting 84

IBM Big Data Hub

MAY 9, 2024

Healthcare organizations need a strong data governance framework to help ensure compliance with regulations like the Health Insurance Portability and Accountability Act of 1996 (HIPAA) in the US and the General Data Protection Regulation (GDPR) in the EU. That’s exactly what enterprise-wide data lineage does.

Data Governance 70

Data Governance Data Quality Insurance Predictive Analytics 70

erwin

MARCH 30, 2020

This data will be collected from organizations such as, the World Health Organization (WHO), the Centers for Disease Control (CDC), and state and local governments across the globe. Privately it will come from hospitals, labs, pharmaceutical companies, doctors and private health insurers. Data lineage to support impact analysis.

Metadata 122

Metadata IT Data Governance Data Quality 122

AWS Big Data

MARCH 7, 2023

Sources Data can be loaded from multiple sources, such as systems of record, data generated from applications, operational data stores, enterprise-wide reference data and metadata, data from vendors and partners, machine-generated data, social sources, and web sources.

Analytics 74

Analytics Data Warehouse Data Lake Metadata 74

IBM Big Data Hub

OCTOBER 12, 2023

Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. Metadata includes details specific to an AI model such as: The AI model’s creation (when it was created, who created it, etc.)

Cost-Benefit 79

Cost-Benefit Metadata Data Governance Modeling 79

Andrew White

JANUARY 11, 2021

As such banking, finance, insurance and media are good examples of information-based industries compared to manufacturing, retail, and so on. As such any Data and Analytics strategy needs to incorporate data sovereignty as per of its D&A governance program. where performance and data quality is imperative?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Domino Data Lab

JULY 22, 2019

He also really informed a lot of the early thinking about data visualization. It involved a lot of interesting work on something new that was data management. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. It’s not going to happen.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109