erwin

OCTOBER 24, 2019

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. And to truly understand it , you need to be able to create and sustain an enterprise-wide view of and easy access to underlying metadata. This isn’t an easy task.

Metadata 104

Metadata Management Data-driven Data Architecture 104

AWS Big Data

JULY 29, 2024

In this blog post, we’ll discuss how the metadata layer of Apache Iceberg can be used to make data lakes more efficient. You will learn about an open-source solution that can collect important metrics from the Iceberg metadata layer. This ensures that each change is tracked and reversible, enhancing data governance and auditability.

Metadata 119

Metadata Snapshot Data Lake Metrics 119

Octopai

DECEMBER 12, 2021

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? What is a metadata management tool? What are examples of metadata management tools?

Metadata 98

Metadata Management Data Quality Data Governance 98

CIO Business Intelligence

APRIL 8, 2025

Fragmented systems, inconsistent definitions, legacy infrastructure and manual workarounds introduce critical risks. As data-centric AI, automated metadata management and privacy-aware data sharing mature, the opportunity to embed data quality into the enterprises core has never been more significant.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

Octopai

JUNE 26, 2020

Steve needed a robust and automated metadata management solution as part of his organization’s data governance strategy. Metadata in data governance. What many enterprises have not yet come to terms with when implementing their data governance strategy and supporting tools, is the criticality of metadata in the process.

Metadata 98

Metadata Data Governance Enterprise Reporting 98

Octopai

OCTOBER 18, 2021

First, what active metadata management isn’t : “Okay, you metadata! Now, what active metadata management is (well, kind of): “Okay, you metadata! Metadata are the details on those tools: what they are, what to use them for, what to use them with. . That takes active metadata management. Quit lounging around!

Metadata 98

Metadata Management IT Data Quality 98

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. It ranks high (No.

Enterprise 349

Enterprise Deep Learning Data Governance Risk 349

AWS Big Data

DECEMBER 4, 2024

With this approach, each node in ANZ maintains its divisional alignment and adherence to data risk and governance standards and policies to manage local data products and data assets. Globally, financial institutions have been experiencing similar issues, prompting a widespread reassessment of traditional data management approaches.

Metadata 94

Metadata Data Governance Data Quality Data-driven 94

erwin

FEBRUARY 12, 2021

Managing an organization’s governance, risk and compliance (GRC) via its enterprise and business architectures means managing them against business processes (BP). Governance, risk and compliance are treated as isolated bubbles. Data-related risks are not connected with the data architects/data scientists.

Risk 98

Risk Slice and Dice Management Enterprise 98

O'Reilly on Data

JANUARY 8, 2019

Organizations will begin to identify and manage risks that accompany the use of machine learning in products and services, such as security and privacy, bias, safety, and lack of transparency. Sustaining machine learning in an enterprise.

Machine Learning 271

Machine Learning IoT Internet of Things Data Science 271

O'Reilly on Data

JUNE 14, 2024

At the same time, Miso went about an in-depth chunking and metadata-mapping of every book in the O’Reilly catalog to generate enriched vector snippet embeddings of each work. And when a question goes beyond the limits of possible citations, the tool will simply reply “I don’t know” rather than risk hallucinating.

Metadata 298

Metadata Publishing Modeling Data-driven 298

CIO Business Intelligence

NOVEMBER 19, 2024

As the next generation of AI training and fine-tuning workloads takes shape, limits to existing infrastructure will risk slowing innovation. For AI to be effective, the relevant data must be easily discoverable and accessible, which requires powerful metadata management and data exploration tools.

Management 116

Management Unstructured Data Deep Learning Metadata 116

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

O'Reilly on Data

JANUARY 28, 2019

Almost everyone who reads this article has consented to some kind of medical procedure; did any of us have a real understanding of what the procedure was and what the risks were? The outcome might not be what you want, but you've agreed to take the risk. In medicine, for the most part, things come out all right.

Insurance 246

Insurance Metadata Data Collection Marketing 246

erwin

JUNE 26, 2020

Organizations with particularly deep data stores might need a data catalog with advanced capabilities, such as automated metadata harvesting to speed up the data preparation process. Three Types of Metadata in a Data Catalog. The metadata provides information about the asset that makes it easier to locate, understand and evaluate.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

AWS Big Data

OCTOBER 29, 2024

The CDH is used to create, discover, and consume data products through a central metadata catalog, while enforcing permission policies and tightly integrating data engineering, analytics, and machine learning services to streamline the user journey from data to insight.

Data Lake 89

Data Lake Sales Metadata Machine Learning 89

DataKitchen

FEBRUARY 2, 2023

This will drive a new consolidated set of tools the data team will leverage to help them govern, manage risk, and increase team productivity. Enterprises are more challenged than ever in their data sprawl , so reducing risk and lowering costs drive software spending decisions. What will exist at the end of 2025?

Metadata 130

Metadata Testing Data Science Risk 130

erwin

JANUARY 9, 2020

It is a tried-and-true practice for lowering data management costs, reducing data-related risks, and improving the quality and agility of an organization’s overall data capability. That’s because it’s the best way to visualize metadata , and metadata is now the heart of enterprise data management and data governance/ intelligence efforts.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

AWS Big Data

NOVEMBER 6, 2024

As a result, two workers ended up running at about 65% CPU utilization, allowing us to safely scaling down the compute capacity without any performance risk. reduces the Amazon DynamoDB cost associated with KCL by optimizing read operations on the DynamoDB table storing metadata. Other benefits in KCL 3.0

Cost-Benefit 109

Cost-Benefit Metadata Optimization Publishing 109

erwin

OCTOBER 8, 2020

And you can’t risk false starts or delayed ROI that reduces the confidence of the business and taint this transformational initiative. 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

CIO Business Intelligence

DECEMBER 18, 2024

This ability builds on the deep metadata context that Salesforce has across a variety of tasks. But whats new, according to Amalgam Insights chief analyst Hyoun Park, is Agent Builders ability to suggest agent topics and instructions.

Enterprise 98

Enterprise IT Sales Metadata 98

erwin

MARCH 30, 2020

Unraveling Data Complexities with Metadata Management. Metadata management will be critical to the process for cataloging data via automated scans. Essentially, metadata management is the administration of data that describes other data, with an emphasis on associations and lineage. Data lineage to support impact analysis.

Metadata 122

Metadata IT Data Governance Data Quality 122

CIO Business Intelligence

SEPTEMBER 23, 2024

For sectors such as industrial manufacturing and energy distribution, metering, and storage, embracing artificial intelligence (AI) and generative AI (GenAI) along with real-time data analytics, instrumentation, automation, and other advanced technologies is the key to meeting the demands of an evolving marketplace, but it’s not without risks.

Manufacturing 122

Manufacturing Internet of Things Metadata Risk 122

Rocket-Powered Data Science

FEBRUARY 15, 2023

3) How do we get started, when, who will be involved, and what are the targeted benefits, results, outcomes, and consequences (including risks)? (2) Why should your organization be doing it and why should your people commit to it? (3) In short, you must be willing and able to answer the seven WWWWWH questions (Who?

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

O'Reilly on Data

MAY 21, 2019

Metadata and artifacts needed for audits. The technologies I’ve alluded to above—data governance, data lineage, model governance—are all going to be useful for helping manage these risks. There are real, not just theoretical, risks and considerations. Managing risk in machine learning”.

Machine Learning 279

Machine Learning Technology Deep Learning Data Science 279

IBM Big Data Hub

OCTOBER 16, 2023

As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits.

Risk 70

Risk Modeling Management Metadata 70

O'Reilly on Data

MARCH 31, 2020

You might have millions of short videos , with user ratings and limited metadata about the creators or content. Job postings have a much shorter relevant lifetime than movies, so content-based features and metadata about the company, skills, and education requirements will be more important in this case.

Management 363

Management Machine Learning Experimentation Metrics 363

erwin

APRIL 9, 2020

If we have not yet ingested and organized both at-rest and in-motion metadata from across our system landscape, then we may be at a disadvantage when it comes to business continuity. As a mitigation for this risk, my family has discussed how we will reunite should a disaster occur when we are outside the home.

Metadata 132

Metadata Risk Data Governance IT 132

erwin

JANUARY 30, 2020

However, more than 50 percent say they have deployed metadata management, data analytics, and data quality solutions. erwin Named a Leader in Gartner 2019 Metadata Management Magic Quadrant. And close to 50 percent have deployed data catalogs and business glossaries. Most have only data governance operations.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

erwin

JULY 12, 2019

Activating their metadata to drive agile data preparation and governance through integrated data glossaries and dictionaries that associate policies to enable stakeholder data literacy. We help customers overcome their data governance challenges, with risk management and regulatory compliance being primary concerns. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

Smart Data Collective

JULY 15, 2021

By using metadata (or short descriptions), data catalogs help companies gather, organize, retrieve, and manage information. A data catalog will usually have a search tool, a separate data discovery tool, a glossary, and a metadata registry. Metadata registries organize various data sets according to categories and fields.

Metadata 133

Metadata IT Data-driven Data Quality 133

Octopai

JANUARY 19, 2020

BCBS 239 is a document published by that committee entitled, Principles for Effective Risk Data Aggregation and Risk Reporting. The document, first published in 2013, outlines best practices for global and domestic banks to identify, manage, and report risks, including credit, market, liquidity, and operational risks.

Metadata 89

Metadata Risk Management Business Intelligence Data Governance 89

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

erwin

JULY 17, 2019

EA and BP modeling squeeze risk out of the digital transformation process by helping organizations really understand their businesses as they are today. Organizations need a real-time, accurate picture of the metadata landscape to: Discover data – Identify and interrogate metadata from various data management silos.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

erwin

DECEMBER 9, 2024

Will the new creative, diverse and scalable data pipelines you are building also incorporate the AI governance guardrails needed to manage and limit your organizational risk? Metadata is the basis of trust for data forensics as we answer the questions of fact or fiction when it comes to the data we see.

Metadata 52

Metadata Data Quality Sales Modeling 52

O'Reilly on Data

JUNE 19, 2019

Metadata and artifacts needed for a full audit trail. Related to this is the need to monitor bias, locality effects, and related risks. Managing risk in machine learning”. A catalog of validation data sets and the accuracy measurements of stored models. or locales (are German and Spanish users getting similar accuracy?).

Modeling 249

Modeling Machine Learning Testing Metrics 249

erwin

OCTOBER 31, 2019

While sometimes at rest in databases, data lakes and data warehouses; a large percentage is federated and integrated across the enterprise, introducing governance, manageability and risk issues that must be managed. So being prepared means you can minimize your risk exposure and the damage to your reputation. No Hocus Pocus.

Data Governance 105

Data Governance Metadata Risk Data Lake 105