Remove Metadata Remove Reporting Remove Unstructured Data
article thumbnail

The state of data quality in 2020

O'Reilly on Data

They don’t have the resources they need to clean up data quality problems. The building blocks of data governance are often lacking within organizations. These include the basics, such as metadata creation and management, data provenance, data lineage, and other essentials. An additional 7% are data engineers.

article thumbnail

SAP Datasphere Powers Business at the Speed of Data

Rocket-Powered Data Science

Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. Datasphere manages and integrates structured, semi-structured, and unstructured data types.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Monitoring Apache Iceberg metadata layer using AWS Lambda, AWS Glue, and AWS CloudWatch

AWS Big Data

In the era of big data, data lakes have emerged as a cornerstone for storing vast amounts of raw data in its native format. They support structured, semi-structured, and unstructured data, offering a flexible and scalable environment for data ingestion from multiple sources.

Metadata 126
article thumbnail

Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

We also examine how centralized, hybrid and decentralized data architectures support scalable, trustworthy ecosystems. As data-centric AI, automated metadata management and privacy-aware data sharing mature, the opportunity to embed data quality into the enterprises core has never been more significant.

article thumbnail

What Is a Metadata Catalog? (And How it Can Dramatically Improve Your Data Accuracy)

Octopai

If you’re a mystery lover, I’m sure you’ve read that classic tale: Sherlock Holmes and the Case of the Deceptive Data, and you know how a metadata catalog was a key plot element. In The Case of the Deceptive Data, Holmes is approached by B.I. Some of these data assets are structured and easy to figure out how to integrate.

article thumbnail

Have we reached the end of ‘too expensive’ for enterprise software?

CIO Business Intelligence

In many cases, this eliminates the need for specialized teams, extensive data labeling, and complex machine-learning pipelines. The extensive pre-trained knowledge of the LLMs enables them to effectively process and interpret even unstructured data. This enables proactive maintenance and helps prevent potential failures.

Software 128
article thumbnail

5 Ways Data Modeling Is Critical to Data Governance

erwin

They also face increasing regulatory pressure because of global data regulations , such as the European Union’s General Data Protection Regulation (GDPR) and the new California Consumer Privacy Act (CCPA), that went into effect last week on Jan. So here’s why data modeling is so critical to data governance.