Alation

JUNE 28, 2022

This is where metadata, or the data about data, comes into play. Your metadata management framework provides the underlying structure that makes your data accessible and manageable. What is a Metadata Management Framework? Your framework should include the following: Global metadata: applies to all information.

Metadata 52

Metadata Management Data Governance Machine Learning 52

erwin

NOVEMBER 6, 2019

erwin released its State of Data Governance Report in February 2018, just a few months before the General Data Protection Regulation (GDPR) took effect. IDC Technology Spotlight, Data Intelligence in Context: Get the report (… it’s free). Can the 80/20 Rule Be Reversed? Click here to take the brief survey.

Metadata 102

Metadata Data Governance Management Cost-Benefit 102

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

erwin

JANUARY 9, 2020

For decades, data modeling has been the optimal way to design and deploy new relational databases with high-quality data sources and support application development. Today’s data modeling is not your father’s data modeling software. So here’s why data modeling is so critical to data governance.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

erwin

NOVEMBER 19, 2020

erwin has once again been positioned as a Leader in the Gartner “2020 Magic Quadrant for Metadata Management Solutions.”. We invite you to download the report and quadrant graphic. This year, erwin had the largest move of any player on the Quadrant and moved up significantly in terms of “Ability to Execute” and also in “Vision.”.

Metadata 98

Metadata Management Digital Transformation Data Governance 98

erwin

MAY 27, 2020

Data modeling supports collaboration among business stakeholders – with different job roles and skills – to coordinate with business objectives. What, then, should users look for in a data modeling product to support their governance/intelligence requirements in the data-driven enterprise? Nine Steps to Data Modeling.

Modeling 98

Modeling Metadata Data Governance Visualization 98

erwin

JULY 2, 2020

Users discuss how they are putting erwin’s data modeling, enterprise architecture, business process modeling, and data intelligences solutions to work. IT Central Station members using erwin solutions are realizing the benefits of enterprise modeling and data intelligence. Data Modeling with erwin Data Modeler.

Enterprise 122

Enterprise Modeling Metadata Data Governance 122

Rocket-Powered Data Science

MARCH 20, 2023

Content includes reports, documents, articles, presentations, visualizations, video, and audio representations of the insights and knowledge that have been extracted from data. Datasphere provides full-spectrum data governance: metadata management, data catalogs, data privacy, data quality, and data lineage (provenance) tracking.

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Unstructured Data 325

CIO Business Intelligence

NOVEMBER 15, 2023

One vehicle might be an annual report, one similar to those that have been published for years by public companies—10ks and 10qs and all those other filings by which stakeholders judge a company’s performance, posture, and potential. Such a report has a legacy already, if only a short one. And don’t just rattle off project metadata.

Publishing 121

Publishing Reporting IT Finance 121

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Foundation models: The power of curated datasets Foundation models , also known as “transformers,” are modern, large-scale AI models trained on large amounts of raw, unlabeled data.

Risk 73

Risk Modeling Management Metadata 73

erwin

OCTOBER 18, 2019

erwin positioned as a Leader in Gartner’s “2019 Magic Quadrant for Metadata Management Solutions”. We were excited to announce earlier today that erwin was named as a Leader in the @Gartner _inc “2019 Magic Quadrant for Metadata Management Solutions.”. GET THE REPORT NOW. This graphic was published by Gartner, Inc.

Metadata 63

Metadata Management Reporting Marketing 63

erwin

DECEMBER 17, 2020

What is Microsoft’s Common Data Model (CDM), and why is it so powerful? The same is true for data, with a number of vendors creating data models by vertical industry (financial services, healthcare, etc.) Here, it is intelligently integrated and connected to the metadata from the data sources that feed enterprise applications.

Modeling 90

Modeling Metadata Data-driven Data Lake 90

Octopai

APRIL 19, 2021

Aptly named, metadata management is the process in which BI and Analytics teams manage metadata, which is the data that describes other data. In other words, data is the context and metadata is the content. Without metadata, BI teams are unable to understand the data’s full story. Donna Burbank.

Metadata 52

Metadata Management Business Intelligence Data Governance 52

erwin

MAY 2, 2022

How to create a solid foundation for data modeling of OLTP systems. As you undertake a cloud database migration , a best practice is to perform data modeling as the foundation for well-designed OLTP databases. This makes mastering basic data modeling techniques and avoiding common pitfalls imperative. Data modeling basics.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

Alation

SEPTEMBER 1, 2022

BARC has named Alation a leader in the new BARC Score Data Intelligence Platforms Report. Download the full report. The goal of this report is to “evaluate software that provides a large number of different users with the agility they need to use data in an effective and efficient way.” The solution?

Reporting 52

Reporting Metadata Data Governance Interactive 52

Alation

FEBRUARY 13, 2020

In an earlier blog, I defined a data catalog as “a collection of metadata, combined with data management and search tools, that helps analysts and other data users to find the data that they need, serves as an inventory of available data, and provides information to evaluate fitness data for intended uses.”.

Metadata 52

Metadata Management Data Lake Data Governance 52

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g. Model Visibility.

Machine Learning 83

Machine Learning Modeling Metadata Recreation/Entertainment 83

AWS Big Data

JULY 14, 2023

Defining and capturing a business capability model If an enterprise doesn’t have a system to capture the business capability model, consider defining and finding a way to capture the model for better insight and visibility, and then map it with digital assets like APIs. It keeps evolving with business requirements and usage.

Modeling 73

Modeling Visualization Reporting Measurement 73

erwin

APRIL 16, 2020

We’re excited about our recognition as a March 2020 Gartner Peer Insights Customers’ Choice for Metadata Management Solutions. Metadata management is key to sustainable data governance and any other organizational effort that is data-driven. Critical Application for Information Governance ” -Information Scientist, Healthcare Industry.

Metadata 52

Metadata Management Data Governance Digital Transformation 52

DataRobot Blog

MAY 10, 2022

Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . The regulatory guidance presented in these documents laid the foundation for evaluating and managing model risk for financial institutions across the United States.

Risk 64

Risk Modeling Machine Learning Data Quality 64

Jet Global

SEPTEMBER 22, 2023

Jet Analytics from insightsoftware helps bridge the gap between reporting and data visualization. Designed to work with Microsoft Dynamics ERPs, Jet Analytics is a cost-effective data preparation, automation, and modeling solution that extends the Microsoft framework to speed-up and de-risk the delivery of a modern data warehouse.

Visualization 52

Visualization Reporting Data Warehouse OLAP 52

AWS Big Data

FEBRUARY 2, 2023

In this post, we discuss a solution using Amazon Athena to query AWS Cost and Usage Reports and Amazon S3 Inventory reports to analyze the cost by prefixes and objects in an S3 bucket. Enable the Cost and Usage Reports. AWS Billing and Cost Management – Create Cost and Usage Reports. Run queries in Athena.

Reporting 89

Reporting Data Lake Management Optimization 89

Cloudera

APRIL 1, 2024

Download the complimentary 2023 Gartner Magic Quadrant for Cloud Database Management Systems report. The Gartner Magic Quadrant report is complemented with the Gartner Critical Capabilities for Analytics report which scores all the vendors on their technical strengths. Unlike software, ML models need continuous tuning.

Unstructured Data 104

Unstructured Data Cost-Benefit Metadata Machine Learning 104

O'Reilly on Data

FEBRUARY 11, 2020

These include the basics, such as metadata creation and management, data provenance, data lineage, and other essentials. They’re still struggling with the basics: tagging and labeling data, creating (and managing) metadata, managing unstructured data, etc. They don’t have the resources they need to clean up data quality problems.

Data Quality 299

Data Quality Metadata Data Governance Publishing 299

Ontotext

OCTOBER 11, 2023

These delved deep into the transformative potential of Large Language Models (LLMs) and the need for semantic technologies to ensure high-quality training data for these models. He also shared key findings on how companies use (not that responsibly) training data to work with models. Are LLMs Knowledgeable? A demonstrator.

Metadata 69

Metadata Cost-Benefit Marketing Modeling 69

Ontotext

MAY 2, 2024

Another challenge is the data models that represent how insights and analytics teams see the world. These models are as important to companies as their frontline products and determine how data is managed, consumed, combined, joined, and analyzed. Here we talk about metadata management, catalog of catalogs, and so on.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

CIO Business Intelligence

MAY 10, 2023

As companies open this “pandora’s box” of new capabilities, they must be prepared to manage data inputs and outputs in secure ways or risk allowing their private data to be consumed in public AI models. AI relies upon large sets of data fed into it to help create output but is limited by the quality of data that is consumed by the model.

Metadata 98

Metadata Data Governance Modeling Technology 98

CIO Business Intelligence

JANUARY 15, 2024

In 2019, NASA’s Science Mission Directorate (SMD) released a report based on a series of interviews with scientists that made it clear those scientists needed a centralized search capability to help them find the data they needed. Her team spent about a year trying to understand the information landscape, the data, and the metadata schemas.

Informatics 123

Informatics Metadata Data mining Digital Transformation 123

CIO Business Intelligence

OCTOBER 13, 2023

They often report to data infrastructure and data science leads. Application data architect: The application data architect designs and implements data models for specific software applications. Data scientists are experts in applying computer science, mathematics, and statistics to building models.

Data Architecture 130

Data Architecture Data Warehouse Statistics Visualization 130

Ontotext

APRIL 10, 2024

In most enterprises data teams lack a data map and data asset inventory and are often unaware of data that exists across the organization, its associated profile, quality and associated metadata. Most do manual reconciliations which result in downstream challenges and reporting errors. For example, a product data tag is basic metadata.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

AWS Big Data

OCTOBER 11, 2023

Also, a data model that allows table truncations at a regular frequency (for example, every 15 seconds) to store only relevant data in tables can cause locking and performance issues. Datasets used for generating insights are curated using materialized views inside the database and published for business intelligence (BI) reporting.

Management 107

Management Metadata Analytics Dashboards 107

DataKitchen

FEBRUARY 2, 2023

Most data governance tools today start with the slow, waterfall building of metadata with data stewards and then hope to use that metadata to drive code that runs in production. In reality, the ‘active metadata’ is just a written specification for a data developer to write their code.

Metadata 130

Metadata Testing Risk Data Science 130

CIO Business Intelligence

AUGUST 3, 2023

That hard, ongoing work includes integrating siloed data, modeling, and understanding it, as well as maintaining and securing it over time. Using the metadata-driven Cinchy Data Collaboration Platform reduced a typical modeling and integration effort from 18 months to six weeks, he says.

Analytics 95

Analytics Data Lake Metadata Cost-Benefit 95

erwin

OCTOBER 8, 2020

But even with the “need for speed” to market, new applications must be modeled and documented for compliance, transparency and stakeholder literacy. With all these diverse metadata sources, it is difficult to understand the complicated web they form much less get a simple visual flow of data lineage and impact analysis.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

Jen Stirrup

MARCH 29, 2023

Data as a product as well as a foundation The data foundation is critical for all types of reporting and analytics. They need a solid data foundation to support primary data initiatives such as data integration, cataloging, semantic modeling, warehousing, federation, and virtualization through a unified interface to get value.

Metadata 121

Metadata Data Warehouse Data Integration Business Intelligence 121

DataKitchen

SEPTEMBER 21, 2023

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

IBM Big Data Hub

OCTOBER 4, 2023

Another IDC study showed that while 2/3 of respondents reported using AI-driven data analytics, most reported that less than half of the data under management is available for this type of analytics. Also, a lakehouse can introduce definitional metadata to ensure clarity and consistency, which enables more trustworthy, governed data.

Data Lake 81

Data Lake Metadata Cost-Benefit Data Warehouse 81