datapine

FEBRUARY 22, 2022

IT should be involved to ensure governance, knowledge transfer, data integrity, and the actual implementation. Then, you can look for areas where “communication barriers result in failing to use data to its full business potential” and use them as a baseline to improve. Because it is that important.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

AWS Big Data

JULY 20, 2023

This functionality has proven to be extremely useful in identifying potential data quality issues and swiftly resolving them by reverting to a previous state with known data integrity. These robust capabilities ensure that data within the data lake remains accurate, consistent, and reliable.

Data Lake 84

Data Lake Analytics Snapshot Optimization 84

Domino Data Lab

APRIL 3, 2019

The longer answer is that in the context of machine learning use cases, strong assumptions about data integrity lead to brittle solutions overall. They co-evolve due to challenges and opportunities among any of the three areas. In other words, don’t plan on 100% security, 100% privacy, 100% correctness, 100% fairness, etc.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84