Remove Analytics Remove Data Processing Remove Enterprise Remove Metadata
article thumbnail

The importance of data ingestion and integration for enterprise AI

IBM Big Data Hub

Data ingestion must be done properly from the start, as mishandling it can lead to a host of new issues. 4 key components to ensure reliable data ingestion Data quality and governance: Data quality means ensuring the security of data sources, maintaining holistic data and providing clear metadata.

article thumbnail

Gartner Data & Analytics Summit 2022 in London: 3 Key Takeaways

Alation

Alation attended last week’s Gartner Data and Analytics Summit in London from May 9 – 11, 2022. Gartner Data & Analytics Summit 2022: Keynote Highlights. Active metadata gives you crucial context around what data you have and how to use it wisely. These are three areas in which analytics is rapidly advancing.

Insiders

Sign Up for our Newsletter

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

Trending Sources

article thumbnail

Empowering data mesh: The tools to deliver BI excellence

erwin

erwin® by Quest is well-known for its data modeling tool, erwin® Data Modeler by Quest , used to draw data models and engineer database schemas across the enterprise. erwin also provides data governance, metadata management and data lineage software called erwin Data Intelligence by Quest.

article thumbnail

Power enterprise-grade Data Vaults with Amazon Redshift – Part 2

AWS Big Data

This post discusses the most pressing needs when designing an enterprise-grade Data Vault and how those needs are addressed by Amazon Redshift in particular and AWS cloud in general. The first post in this two-part series discusses best practices for designing enterprise-grade data vaults of varying scale using Amazon Redshift.

article thumbnail

Petabyte-scale log analytics with Amazon S3, Amazon OpenSearch Service, and Amazon OpenSearch Ingestion

AWS Big Data

You can take all your data from various silos, aggregate that data in your data lake, and perform analytics and machine learning (ML) directly on top of that data. You can now analyze infrequently queried data in cloud object stores and simultaneously use the operational analytics and visualization capabilities of OpenSearch Service.

Data Lake 115
article thumbnail

Use your corporate identities for analytics with Amazon EMR and AWS IAM Identity Center

AWS Big Data

To enable your workforce users for analytics with fine-grained data access controls and audit data access, you might have to create multiple AWS Identity and Access Management (IAM) roles with different data permissions and map the workforce users to one of those roles. Both enterprise users from Okta are provisioned in IAM Identity Center.

article thumbnail

Modernize your ETL platform with AWS Glue Studio: A case study from BMS

AWS Big Data

For the past 5 years, BMS has used a custom framework called Enterprise Data Lake Services (EDLS) to create ETL jobs for business users. BMS’s EDLS platform hosts over 5,000 jobs and is growing at 15% YoY (year over year). It retrieves the specified files and available metadata to show on the UI.