Remove Data Analytics Remove Data Integration Remove Metadata Remove Unstructured Data
article thumbnail

Data governance in the age of generative AI

AWS Big Data

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

article thumbnail

Five benefits of a data catalog

IBM Big Data Hub

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Insiders

Sign Up for our Newsletter

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

article thumbnail

Use Amazon Athena to query data stored in Google Cloud Platform

AWS Big Data

As customers accelerate their migrations to the cloud and transform their businesses, some find themselves in situations where they have to manage data analytics in a multi-cloud environment, such as acquiring a company that runs on a different cloud provider. For instructions, refer to Setting up databases and tables in AWS Glue.

article thumbnail

Data architecture strategy for data quality

IBM Big Data Hub

Both approaches were typically monolithic and centralized architectures organized around mechanical functions of data ingestion, processing, cleansing, aggregation, and serving. Monitor and identify data quality issues closer to the source to mitigate the potential impact on downstream processes or workloads.

article thumbnail

A hybrid approach in healthcare data warehousing with Amazon Redshift

AWS Big Data

Loading complex multi-point datasets into a dimensional model, identifying issues, and validating data integrity of the aggregated and merged data points are the biggest challenges that clinical quality management systems face. It is a data modeling methodology designed for large-scale data warehouse platforms.

article thumbnail

The Superpowers of Ontotext’s Relation and Event Detector

Ontotext

From a technological perspective, RED combines a sophisticated knowledge graph with large language models (LLM) for improved natural language processing (NLP), data integration, search and information discovery, built on top of the metaphactory platform. Let’s have a quick look under the bonnet.

article thumbnail

How Ruparupa gained updated insights with an Amazon S3 data lake, AWS Glue, Apache Hudi, and Amazon QuickSight

AWS Big Data

An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data. The AWS Glue job can transform the raw data in Amazon S3 to Parquet format, which is optimized for analytic queries. All the metadata of the tables is stored in the AWS Glue Data Catalog, including the Hudi tables.