erwin

FEBRUARY 7, 2019

Organization’s cannot hope to make the most out of a data-driven strategy, without at least some degree of metadata-driven automation. The volume and variety of data has snowballed, and so has its velocity. As such, traditional – and mostly manual – processes associated with data management and data governance have broken down.

Metadata 96

Metadata Insurance Data-driven Cost-Benefit 96

erwin

NOVEMBER 6, 2020

Prashant Parikh, erwin’s Senior Vice President of Software Engineering, talks about erwin’s vision to automate every aspect of the data governance journey to increase speed to insights. Although AI and ML are massive fields with tremendous value, erwin’s approach to data governance automation is much broader.

Data Governance 97

Data Governance Metadata Data-driven Visualization 97

Alation

FEBRUARY 3, 2022

They make testing and learning a part of that process. Using this methodology, teams will test new processes, monitor performance, and adjust based on results. DataOps practices help organizations overcome challenges caused by fragmented teams and processes and delays in delivering data in consumable forms.

Data Governance 98

Data Governance Measurement Metadata Testing 98

AWS Big Data

OCTOBER 30, 2024

With this launch of JDBC connectivity, Amazon DataZone expands its support for data users, including analysts and scientists, allowing them to work in their preferred environments—whether it’s SQL Workbench, Domino, or Amazon-native solutions—while ensuring secure, governed access within Amazon DataZone. Choose Test connection.

Visualization 116

Visualization Data Lake Testing Data Governance 116

O'Reilly on Data

DECEMBER 19, 2018

have a large body of tools to choose from: IDEs, CI/CD tools, automated testing tools, and so on. are only starting to exist; one big task over the next two years is developing the IDEs for machine learning, plus other tools for data management, pipeline management, data cleaning, data provenance, and data lineage.

Machine Learning 279

Machine Learning Software Metadata Testing 279

O'Reilly on Data

MAY 21, 2019

You also need solutions that let you understand what data you have and who can access it. About a third of the respondents in the survey indicated they are interested in data governance systems and data catalogs. A catalog or a database that lists models, including when they were tested, trained, and deployed.

Machine Learning 279

Machine Learning Technology Deep Learning Data Science 279

erwin

JANUARY 24, 2019

With an automation framework, data professionals can meet these needs at a fraction of the cost of the traditional manual way. In data governance terms, an automation framework refers to a metadata-driven universal code generator that works hand in hand with enterprise data mapping for: Pre-ETL enterprise data mapping.

Data Governance 71

Data Governance Metadata Data-driven Cost-Benefit 71

CIO Business Intelligence

NOVEMBER 27, 2024

Good data governance has always involved dealing with errors and inconsistencies in datasets, as well as indexing and classifying that structured data by removing duplicates, correcting typos, standardizing and validating the format and type of data, and augmenting incomplete information or detecting unusual and impossible variations in the data.

Enterprise 141

Enterprise Data Quality Structured Data Modeling 141

O'Reilly on Data

APRIL 2, 2019

We’ve become accustomed to the need for data governance and provenance, understanding and controlling the many databases that are combined in a modern data-driven application. A catalog or a database that lists models, including when they were tested, trained, and deployed.

Machine Learning 269

Machine Learning Modeling Data Science Software 269

DataKitchen

FEBRUARY 2, 2023

A combined, interoperable suite of tools for data team productivity, governance, and security for large and small data teams. As an analogy, the DevOps space has seen consolidation in code storage, CI/CD, team workflow, value stream management, testing, and other tools into one platform.

Metadata 130

Metadata Testing Data Science Risk 130

DataKitchen

JANUARY 5, 2021

The data teams share a common objective; to create analytics for the (internal or external) customer. Execution of this mission requires the contribution of several groups: data center/IT, data engineering, data science, data visualization, and data governance.

Testing 147

Testing Data Governance Metadata Visualization 147

Cloudera

MARCH 9, 2021

In this blog, we’ll highlight the key CDP aspects that provide data governance and lineage and show how they can be extended to incorporate metadata for non-CDP systems from across the enterprise. The SDX layer of CDP leverages the full spectrum of Atlas to automatically track and control all data assets.

Data Governance 97

Data Governance Metadata Enterprise Data Processing 97

DataKitchen

AUGUST 16, 2024

Data Pipeline Observability: Optimizes pipelines by monitoring data quality, detecting issues, tracing data lineage, and identifying anomalies using live and historical metadata. This capability includes monitoring, logging, and business-rule detection.

Marketing 124

Marketing Data Quality Testing Metadata 124

Alation

FEBRUARY 17, 2023

This past week, I had the pleasure of hosting Data Governance for Dummies author Jonathan Reichental for a fireside chat , along with Denise Swanson , Data Governance lead at Alation. Can you have proper data management without establishing a formal data governance program?

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

erwin

APRIL 16, 2020

We’re excited about our recognition as a March 2020 Gartner Peer Insights Customers’ Choice for Metadata Management Solutions. This automation results in greater accuracy, faster analysis and better decision-making for data governance and digital transformation initiatives.

Metadata 52

Metadata Management Data Governance Digital Transformation 52

IBM Big Data Hub

JULY 28, 2022

Metadata enrichment is about scaling the onboarding of new data into a governed data landscape by taking data and applying the appropriate business terms, data classes and quality assessments so it can be discovered, governed and utilized effectively. Scalability and elasticity.

Metadata 56

Metadata Machine Learning Data Quality Statistics 56

CIO Business Intelligence

FEBRUARY 2, 2024

Developer, Professional Certification Mastering Data Management and Technology SAP Certified Application Associate – SAP Master Data Governance The Art of Service Master Data Management Certification The Art of Service Master Data Management Complete Certification Kit validates the candidate’s knowledge of specific methods, models, and tools in MDM.

Management 116

Management Data Governance Cost-Benefit Testing 116

datapine

SEPTEMBER 29, 2022

This person (or group of individuals) ensures that the theory behind data quality is communicated to the development team. 2 – Data profiling. Data profiling is an essential process in the DQM lifecycle. This means there are no unintended data errors, and it corresponds to its appropriate designation (e.g.,

Data Quality 241

Data Quality Metrics Data-driven Management 241

CIO Business Intelligence

OCTOBER 13, 2023

Application data architect: The application data architect designs and implements data models for specific software applications. Information/data governance architect: These individuals establish and enforce data governance policies and procedures.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

erwin

AUGUST 7, 2019

A data catalog benefits organizations in a myriad of ways. With the right data catalog tool, organizations can automate enterprise metadata management – including data cataloging, data mapping, data quality and code generation for faster time to value and greater accuracy for data movement and/or deployment projects.

Metadata 90

Metadata Data Governance Data Quality Data Warehouse 90

erwin

DECEMBER 9, 2024

If you are not observing and reacting to the data, the model will accept every variant and it may end up one of the more than 50% of models, according to Gartner , that never make it to production because there are no clear insights and the results have nothing to do with the original intent of the model.

Metadata 52

Metadata Data Quality Sales Modeling 52

CIO Business Intelligence

MAY 10, 2023

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. This was on display during the initial test releases of Google Bard, where it provided a factually inaccurate answer on the James Webb Space Telescope based on reference data it ingested.

Metadata 98

Metadata Data Governance Modeling Technology 98

Alation

MAY 31, 2023

The Data Governance & Information Quality Conference (DGIQ) is happening soon — and we’ll be onsite in San Diego from June 5-9. If you’re not familiar with DGIQ, it’s the world’s most comprehensive event dedicated to, you guessed it, data governance and information quality. The best part?

Data Governance 52

Data Governance Insurance Metadata Data-driven 52

IBM Big Data Hub

MARCH 25, 2022

There are many different approaches, but you’ll want an architecture that can be used regardless of your data estate. In other words, the obstacles of data access, data integration and data protection are minimized, rendering maximum flexibility to the end users. Protection is applied on each data pipeline.

Metadata 104

Metadata Data Quality Data Governance Data Integration 104

AWS Big Data

MAY 7, 2024

Data governance is a key enabler for teams adopting a data-driven culture and operational model to drive innovation with data. Amazon DataZone allows you to simply and securely govern end-to-end data assets stored in your Amazon Redshift data warehouses or data lakes cataloged with the AWS Glue data catalog.

Metadata 87

Metadata Data Lake Data Processing Data-driven 87

AWS Big Data

FEBRUARY 26, 2025

S3 Tables integration with the AWS Glue Data Catalog is in preview, allowing you to stream, query, and visualize dataincluding Amazon S3 Metadata tablesusing AWS analytics services such as Amazon Data Firehose , Amazon Athena , Amazon Redshift, Amazon EMR, and Amazon QuickSight. With AWS Glue 5.0,

Analytics 59

Analytics Data Lake Metadata Data Warehouse 59

AWS Big Data

JUNE 10, 2024

In this post, we delve into the key aspects of using Amazon EMR for modern data management, covering topics such as data governance, data mesh deployment, and streamlined data discovery. Organizations have multiple Hive data warehouses across EMR clusters, where the metadata gets generated.

Data Lake 96

Data Lake Metadata Data Warehouse Data Processing 96

AWS Big Data

JULY 18, 2024

The current method is largely manual, relying on emails and general communication, which not only increases overhead but also varies from one use case to another in terms of data governance. Data domain producers publish data assets using datasource run to Amazon DataZone in the Central Governance account.

Data Lake 122

Data Lake Publishing Metadata Data-driven 122

Cloudera

OCTOBER 7, 2021

Application Logic: Application logic refers to the type of data processing, and can be anything from analytical or operational systems to data pipelines that ingest data inputs, apply transformations based on some business logic and produce data outputs.

Metadata 124

Metadata Cost-Benefit Enterprise Interactive 124

AWS Big Data

JULY 8, 2024

Introduction to OpenLineage compatible data lineage The need to capture data lineage consistently across various analytical services and combine them into a unified object model is key in uncovering insights from the lineage artifact. Now let’s harvest the lineage metadata using CloudShell. Choose Run.

Visualization 109

Visualization Metadata Publishing Sales 109

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Less data gets decompressed, deserialized, loaded into memory, run through the processing, etc.

Metadata 105

Metadata Data Science Machine Learning Data-driven 105

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. But sometimes there isn’t enough data,” says Thurai.

Modeling 140

Modeling Testing Cost-Benefit Metadata 140

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.” Why keep data at all?

Metadata 64

Metadata Data Governance Dashboards Software 64

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. So questions linger about whether transformed data can be trusted.

Data Governance 40

Data Governance Risk Metadata Management 40

IBM Big Data Hub

FEBRUARY 26, 2024

The financial services industry has been in the process of modernizing its data governance for more than a decade. But as we inch closer to global economic downturn, the need for top-notch governance has become increasingly urgent. Download the Gartner® Market Guide for Active Metadata Management 1.

Cost-Benefit 90

Cost-Benefit Metadata Data Governance Reporting 90

Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

Data Architecture 85

Data Architecture Risk Management Risk Management 85

AWS Big Data

APRIL 25, 2024

This approach allows the team to process the raw data extracted from Account A to Account B, which is dedicated for data handling tasks. This makes sure the raw and processed data can be maintained securely separated across multiple accounts, if required, for enhanced data governance and security. secretsmanager ).

Metadata 116

Metadata Data Processing Management Testing 116