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. Creating a High-Quality Data Pipeline.

Data Governance 40

Data Governance Risk Metadata Management 40

erwin

APRIL 29, 2020

For that reason, businesses must think about the flow of data across multiple systems that fuel organizational decision-making. The CEO also makes decisions based on performance and growth statistics. Regulatory compliance places greater transparency demands on firms when it comes to tracing and auditing data. Data Governance.

Metadata 111

Metadata Key Performance Indicator Data Governance Data Quality 111

datapine

SEPTEMBER 29, 2022

This person (or group of individuals) ensures that the theory behind data quality is communicated to the development team. 2 – Data profiling. Data profiling is an essential process in the DQM lifecycle. This is also the point where data quality rules should be reviewed again. date, month, and year).

Data Quality 241

Data Quality Metrics Data-driven Management 241

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. This may also entail working with new data through methods like web scraping or uploading.

Enterprise 72

Enterprise Data Integration Data Quality Contextual Data 72