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.

Data Quality 241

Data Quality Metrics Data-driven Management 241

CIO Business Intelligence

JUNE 23, 2022

Yet as companies fight for skilled analyst roles to utilize data to make better decisions , they often fall short in improving the data supply chain and resulting data quality. Without a solid data supply-chain management practices in place, data quality often suffers. First mile/last mile impacts.

Data Quality 97

Data Quality Key Performance Indicator Metrics KPI 97

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

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. So questions linger about whether transformed data can be trusted.

Data Governance 40

Data Governance Risk Metadata Management 40

Alation

MARCH 22, 2022

As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT. So, how can you quickly take advantage of the DataOps opportunity while avoiding the risk and costs of DIY?

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

DataKitchen

DECEMBER 9, 2022

DataOps observability involves the use of various tools and techniques to monitor the performance of data pipelines, data lakes, and other data-related infrastructure. This can include tools for tracking the flow of data through pipelines, and for measuring the performance of data-related systems and processes.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

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 78

Enterprise Data Integration Data Quality Contextual Data 78