IBM Data Science in Practice

APRIL 26, 2024

Metadata Enrichment: Empowering Data Governance Data Quality Tab from Metadata Enrichment Metadata enrichment is a crucial aspect of data governance, enabling organizations to enhance the quality and context of their data assets. More on metadata enrichment can be read here.

SQL 130

SQL Data Quality Data Governance Data Scientist 130

IBM Journey to AI blog

JULY 3, 2024

Align your data strategy to a go-forward architecture, with considerations for existing technology investments, governance and autonomous management built in. Look to AI to help automate tasks such as data onboarding, data classification, organization and tagging.

AI 45

AI Data Quality AI Database 45

Alation

MAY 16, 2023

Data is a valuable resource, especially in the world of business. A McKinsey survey found that companies that use customer analytics intensively are 19 times higher to achieve above-average profitability. But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines.

Data Pipeline 69

Data Pipeline Data Governance Data Lakes Data Warehouse 69

phData

JUNE 20, 2024

Data is integral to many processes and decisions when a data culture thrives. More complex analyses can be performed on trusted data as the analytics capability matures to gain further insight. Data as the foundation of what the business does is great – but how do you support that?

Data Governance 52

Data Governance Analytics Analytics Power BI 52

Alation

JUNE 14, 2021

Dan Kirsch, Analyst, Hurwitz Associates, agrees that CISOs must take responsibility, when he says that “data protection is absolutely part of the CISO’s job. For this reason, smart CISOs are making sure that analytics and AI teams have data security in mind and are using secure data platforms. What do we know?

Data Governance 97

Data Governance Data Lakes Data Classification Data Quality 97

Alation

AUGUST 26, 2021

Why keep data at all? Answering these questions can improve operational efficiencies and inform a number of data intelligence use cases, which include data governance, self-service analytics, and more. Data Intelligence: Origin, Evolution, Use Cases. Examples of Data Intelligence use cases include: Data governance.

Data Governance 64

Data Governance ML ML Augmented Analytics 64

Alation

MAY 16, 2023

Data is a valuable resource, especially in the world of business. A McKinsey survey found that companies that use customer analytics intensively are 19 times higher to achieve above-average profitability. But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines.

Data Pipeline 40

Data Pipeline Data Governance Data Lakes Data Warehouse 40