Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

Alation

JANUARY 26, 2023

Lack of data governance can summon a whole range of problems, including: Lack of consistency For data to be useful, it should be consistent across all areas. A field might not be entered in the same way across different departments, which makes the data difficult to find and affects the accuracy of business intelligence (BI).

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

Jet Global

JULY 2, 2019

Ungoverned or uncatalogued data can leave businesses vulnerable both in terms of data quality (and organizational trust in that data), as well as in terms of security, regulatory, and compliance risks. Build your Business Intelligence Infrastructure on a Solid Foundation.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

TDAN

APRIL 30, 2019

Roles and responsibilities are the backbone of a successful information or data governance program. To operate an efficient and effective program and hold people formally accountable for doing the “right” thing at the “right” time, it requires the definition and deployment of roles that are appropriate for the culture of the organization.

Data Governance 79

Data Governance Data Quality IT Metadata 79

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. Second, you must establish a definition of “done.” In DataOps, the definition of done includes more than just some working code. Definition of Done. Monitoring Job Metadata.

Testing 152

Testing Metadata Dashboards Statistics 152

erwin

MAY 27, 2020

What’s desperately needed is a way to understand the relationships and interconnections between so many entities in data sets in detail. Visualizing data from anywhere defined by its context and definition in a central model repository, as well as the rules for governing the use of those data elements, unifies enterprise data management.

Modeling 98

Modeling Metadata Data Governance Visualization 98

CIO Business Intelligence

JUNE 12, 2024

“Most enterprise data is unstructured and semi-structured documents and code, as well as images and video. For example, gen AI can be used to extract metadata from documents, create indexes of information and knowledge graphs, and to query, summarize, and analyze this data.

Modeling 131

Modeling Testing Cost-Benefit IT 131

Domino Data Lab

JULY 22, 2019

There’s a really nice comfortable blend here of what’s important in business, in engineering, in data science, etc. I definitely want to provide some shout-outs. In data science, definitely, there are other people who’ve talked more about that and we’ll point to them. Then things changed.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Alation

MAY 31, 2023

American Family Insurance: Governance by Design – Not as an Afterthought Who: Anil Kumar Kunden , Information Standards, Governance and Quality Specialist at AmFam Group When: Wednesday, June 7, at 2:45 PM Why attend: Learn how to automate and accelerate data pipeline creation and maintenance with data governance, AKA metadata normalization.

Data Governance 52

Data Governance Insurance Metadata Data-driven 52

AWS Big Data

MARCH 1, 2024

End users access this data using third-party SQL clients and business intelligence tools. Solution overview In this post, we’ll use synthetic data very similar to BMO data with data classified as PII, PCI, or HPR. Users and groups exists in External IdP.

Data Lake 98

Data Lake Data Warehouse Management Risk 98

Alation

MARCH 21, 2023

When it embarked on a digital transformation and modernization initiative in 2018, the company migrated all its data to AWS S3 Data Lake and Snowflake Data Cloud to provide accessibility to data to all users. Using Alation, ARC automated the data curation and cataloging process. “So

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Alation

APRIL 12, 2022

CDOs have a mandate across the data value chain, across that whole life cycle of data. Data governance also extends across that life cycle. It’s not just about security or privacy or ensuring data quality; it’s also ensuring the right people can access it and use it to deliver value to the organization.”.

Data Quality 52

Data Quality Data Governance Metrics Data Strategy 52

BI-Survey

MARCH 4, 2022

The key challenge in setting up data governance is the definition of guidelines that set the necessary boundaries to any activities with data but at the same time support a positive, fearless atmosphere in which to use data and analytics as well as new use cases. Define responsibilities to make data understandable (e.g.,

Data-driven 52

Data-driven Data Strategy Data Governance Strategy 52

AWS Big Data

AUGUST 14, 2023

Some principles for the management of data mesh evolution, and the evaluation of data products against organizational goals, are explored later in this post. Data products vs. data definitions The following figure illustrates how data definitions are defined and inherited throughout the lineage of data products.

Management 77

Management Risk Measurement Optimization 77

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.”

Metadata 64

Metadata Data Governance Dashboards Software 64

BI-Survey

FEBRUARY 6, 2020

Only a minority of companies say they have a modern reporting landscape and regularly base decisions on data. These problems become even more obvious when contrasted with modern infrastructures built in the cloud and micro services as well as the challenges caused by exploding data volume and variety. This will and must change.

Reporting 59

Reporting Optimization Enterprise Data Quality 59

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52