O'Reilly on Data

APRIL 2, 2019

Model packaging: companies are using MLflow to incorporate custom logic and dependencies as part of a model’s package abstraction before deploying it to their production environment (example: a recommendation system might be programmed to not display certain images to minors). Model governance.

Machine Learning 271

Machine Learning Modeling Data Science Software 271

O'Reilly on Data

FEBRUARY 11, 2020

They don’t have the resources they need to clean up data quality problems. The building blocks of data governance are often lacking within organizations. These include the basics, such as metadata creation and management, data provenance, data lineage, and other essentials. And that’s just the beginning.

Data Quality 363

Data Quality Metadata Data Governance Publishing 363

erwin

OCTOBER 8, 2020

That means your cloud data assets must be available for use by the right people for the right purposes to maximize their security, quality and value. Why You Need Cloud Data Governance. Regulatory compliance is also a major driver of data governance (e.g., GDPR, CCPA, HIPAA, SOX, PIC DSS).

Data Governance 145

Data Governance Metadata Testing Data Lake 145

erwin

JANUARY 30, 2020

I’m excited to share the results of our new study with Dataversity that examines how data governance attitudes and practices continue to evolve. Defining Data Governance: What Is Data Governance? . 1 reason to implement data governance. Most have only data governance operations.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

Rocket-Powered Data Science

MARCH 20, 2023

Datasphere goes beyond the “big three” data usage end-user requirements (ease of discovery, access, and delivery) to include data orchestration (data ops and data transformations) and business data contextualization (semantics, metadata, catalog services).

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Machine Learning 325

AWS Big Data

JANUARY 15, 2025

Data landscape in EUROGATE and current challenges faced in data governance The EUROGATE Group is a conglomerate of container terminals and service providers, providing container handling, intermodal transports, maintenance and repair, and seaworthy packaging services. Eliminate centralized bottlenecks and complex data pipelines.

IoT 109

IoT Machine Learning Metadata Data-driven 109

erwin

SEPTEMBER 3, 2020

Why should you integrate data governance (DG) and enterprise architecture (EA)? Data governance provides time-sensitive, current-state architecture information with a high level of quality. Data governance provides time-sensitive, current-state architecture information with a high level of quality.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

CIO Business Intelligence

SEPTEMBER 19, 2024

It will do this, it said, with bidirectional integration between its platform and Salesforce’s to seamlessly delivers data governance and end-to-end lineage within Salesforce Data Cloud. Additional to that, we are also allowing the metadata inside of Alation to be read into these agents.”

Data Governance 123

Data Governance Metadata Unstructured Data Structured Data 123

erwin

AUGUST 28, 2020

Organizations with a solid understanding of data governance (DG) are better equipped to keep pace with the speed of modern business. In this post, the erwin Experts address: What Is Data Governance? Why Is Data Governance Important? What Is Good Data Governance? What Is Data Governance?

Data Governance 145

Data Governance IT Cost-Benefit Metadata 145

erwin

APRIL 16, 2021

Data governance is best defined as the strategic, ongoing and collaborative processes involved in managing data’s access, availability, usability, quality and security in line with established internal policies and relevant data regulations. Data Governance Is Business Transformation. Predictability.

Data Governance 128

Data Governance Metadata Cost-Benefit Data-driven 128

erwin

OCTOBER 29, 2020

Automating data governance is key to addressing the exponentially growing volume and variety of data. Data readiness is everything. In a COVID and post-COVID world, organizations need to radically change as we look to reimagine business models and reform the way we approach almost everything.

Data Governance 105

Data Governance Metadata Digital Transformation ROI 105

erwin

JANUARY 3, 2020

Understanding the data governance trends for the year ahead will give business leaders and data professionals a competitive edge … Happy New Year! Regulatory compliance and data breaches have driven the data governance narrative during the past few years.

Data Governance 139

Data Governance Digital Transformation IoT Metadata 139

erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. What Is Metadata? Harvest data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

AWS Big Data

DECEMBER 4, 2024

Under the federated mesh architecture, each divisional mesh functions as a node within the broader enterprise data mesh, maintaining a degree of autonomy in managing its data products. This model balances node or domain-level autonomy with enterprise-level oversight, creating a scalable and consistent framework across ANZ.

Metadata 104

Metadata Data Governance Data Quality Data-driven 104

CIO Business Intelligence

MARCH 24, 2023

Data governance definition Data governance is a system for defining who within an organization has authority and control over data assets and how those data assets may be used. It encompasses the people, processes, and technologies required to manage and protect data assets.

Data Governance 142

Data Governance Management Metadata Data Quality 142

O'Reilly on Data

MARCH 18, 2020

Whether it’s controlling for common risk factors—bias in model development, missing or poorly conditioned data, the tendency of models to degrade in production—or instantiating formal processes to promote data governance, adopters will have their work cut out for them as they work to establish reliable AI production lines.

Enterprise 350

Enterprise Deep Learning Data Governance Risk 350

erwin

JANUARY 17, 2020

What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise.

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

erwin

MAY 13, 2020

The role of data modeling (DM) has expanded to support enterprise data management, including data governance and intelligence efforts. After all, you can’t manage or govern what you can’t see, much less use it to make smart decisions. Types of Data Models: Conceptual, Logical and Physical.

Data Governance 93

Data Governance Enterprise Modeling Management 93

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 122

Data Governance Unstructured Data Metadata Data Lake 122

erwin

MARCH 4, 2021

Modern data governance is a strategic, ongoing and collaborative practice that enables organizations to discover and track their data, understand what it means within a business context, and maximize its security, quality and value. The What: Data Governance Defined. Data governance has no standard definition.

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

erwin

JULY 12, 2019

In light of recent, high-profile data breaches, it’s past-time we re-examined strategic data governance and its role in managing regulatory requirements. for alleged violations of the European Union’s General Data Protection Regulation (GDPR). How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

AWS Big Data

JULY 29, 2024

It addresses many of the shortcomings of traditional data lakes by providing features such as ACID transactions, schema evolution, row-level updates and deletes, and time travel. In this blog post, we’ll discuss how the metadata layer of Apache Iceberg can be used to make data lakes more efficient.

Metadata 125

Metadata Snapshot Data Lake Metrics 125

erwin

DECEMBER 19, 2019

To help you prepare for 2020, we’ve compiled some of the most popular data governance and metadata management blog posts from the erwin Experts from this year. The Best Data Governance and Metadata Management Blog Posts of 2019. Four Use Cases Proving the Benefits of Metadata-Driven Automation.

Metadata 75

Metadata Data Governance Management Digital Transformation 75

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 are these rampant and often uncontrolled projects to collect metadata properly motivated? What Is Metadata?

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

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

TDAN

JUNE 15, 2021

Data Governance describes the practices and processes organizations use to manage the access, use, quality and security of an organizations data assets. The data-driven business era has seen a rapid rise in the value of organization’s data resources.

Data Governance 105

Data Governance Modeling Data-driven Management 105

erwin

OCTOBER 31, 2019

The Regulatory Rationale for Integrating Data Management & Data Governance. Now, as Cybersecurity Awareness Month comes to a close – and ghosts and goblins roam the streets – we thought it a good time to resurrect some guidance on how data governance can make data security less scary.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

AWS Big Data

OCTOBER 29, 2024

To achieve this, they aimed to break down data silos and centralize data from various business units and countries into the BMW Cloud Data Hub (CDH). However, the initial version of CDH supported only coarse-grained access control to entire data assets, and hence it was not possible to scope access to data asset subsets.

Data Lake 106

Data Lake Sales Metadata Machine Learning 106

AWS Big Data

DECEMBER 19, 2024

Initially, the data inventories of different services were siloed within isolated environments, making data discovery and sharing across services manual and time-consuming for all teams involved. Implementing robust data governance is challenging.

Data Governance 52

Data Governance Publishing Data-driven Metadata 52

CIO Business Intelligence

APRIL 29, 2022

Forward-thinking transformation leaders have realised that more focus needs to be placed on ‘data-centric value creation’ and have made this the pre-eminent organising principle in their organisations. Many organisations focus too heavily on fine tuning their computational models in their pursuit of ‘quick-wins.’ About Andrew P.

Data Governance 145

Data Governance IT Data Lake Risk 145

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. This is live and dynamic.”.

Enterprise 122

Enterprise Modeling Metadata Data Governance 122

erwin

NOVEMBER 14, 2019

Data governance tools used to occupy a niche in an organization’s tech stack, but those days are gone. The rise of data-driven business and the complexities that come with it ushered in a soft mandate for data governance and data governance tools. Data Governance Tools for Regulatory Compliance.

Data Governance 105

Data Governance Data-driven Cost-Benefit Metadata 105

erwin

OCTOBER 24, 2019

Untapped data, if mined, represents tremendous potential for your organization. While there has been a lot of talk about big data over the years, the real hero in unlocking the value of enterprise data is metadata , or the data about the data. Metadata Is the Heart of Data Intelligence.

Metadata 104

Metadata Management Data-driven Data Architecture 104

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

Octopai

DECEMBER 12, 2021

What enables you to use all those gigabytes and terabytes of data you’ve collected? Metadata is the pertinent, practical details about data assets: what they are, what to use them for, what to use them with. Without metadata, data is just a heap of numbers and letters collecting dust. Where does metadata come from?

Metadata 98

Metadata Management Data Quality Data Governance 98

Alation

NOVEMBER 4, 2021

The practitioner asked me to add something to a presentation for his organization: the value of data governance for things other than data compliance and data security. Now to be honest, I immediately jumped onto data quality. Data quality is a very typical use case for data governance.

Data Governance 94

Data Governance Metadata Data Quality Enterprise 94

O'Reilly on Data

MAY 21, 2019

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in London earlier this year. A typical data pipeline for machine learning.

Machine Learning 279

Machine Learning Technology Deep Learning Data Science 279