IBM Big Data Hub

OCTOBER 16, 2023

As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits.

Risk 71

Risk Modeling Management Metadata 71

datapine

SEPTEMBER 29, 2022

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes.

Data Quality 241

Data Quality Metrics Data-driven Management 241

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. And there’s control of that landscape to facilitate insight and collaboration and limit risk.

Data Governance 40

Data Governance Risk Metadata Management 40

Octopai

DECEMBER 11, 2022

Banks didn’t accurately assess their credit and operational risk and hold enough capital reserves, leading to the Great Recession of 2008-2009. Let’s take a look at several regulatory standards and explore automated data lineage’s role in smoothing and improving data compliance. Data lineage and financial risk data compliance.

Insurance 52

Insurance Risk Metadata Reporting 52

Alation

MARCH 22, 2022

DataOps requires an array of technology to automate the design, development, deployment, and management of data delivery, with governance sprinkled on for good measure. So, how can you quickly take advantage of the DataOps opportunity while avoiding the risk and costs of DIY? As with any next big thing, there is no free lunch.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

IBM Big Data Hub

JANUARY 9, 2024

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. Increased variance: Variance measures consistency.

Enterprise 72

Enterprise Data Integration Data Quality Contextual Data 72

erwin

APRIL 16, 2024

In this blog, we’ll delve into the critical role of governance and data modeling tools in supporting a seamless data mesh implementation and explore how erwin tools can be used in that role. erwin also provides data governance, metadata management and data lineage software called erwin Data Intelligence by Quest.

Metadata 52

Metadata Data Quality Data Governance Modeling 52