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

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

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

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

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

IBM Big Data Hub

NOVEMBER 28, 2022

Metadata management performs a critical role within the modern data management stack. However, as data volumes continue to grow, manual approaches to metadata management are sub-optimal and can result in missed opportunities. This puts into perspective the role of active metadata management. What is Active Metadata management?

Metadata 56

Metadata Data Quality Data-driven Data Governance 56

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

DECEMBER 4, 2024

Our customers tell us that the fragmented nature of permissions and access controls, managed separately within individual data sources and tools, leads to inconsistent implementation and potential security risks. Having confidence in your data is key. The tools to transform your business are here. We’re excited to see what you’ll build next!

Data Analytics 102

Data Analytics Analytics Data Lake Data Quality 102

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

erwin

JULY 17, 2019

Part Two of the Digital Transformation Journey … In our last blog on driving digital transformation , we explored how enterprise architecture (EA) and business process (BP) modeling are pivotal factors in a viable digital transformation strategy. Analyze metadata – Understand how data relates to the business and what attributes it has.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

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

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

erwin

SEPTEMBER 10, 2020

In a previous blog , I explained that data lineage is basically the history of data, including a data set’s origin, characteristics, quality and movement over time. Data lineage helps answer questions about the origin of data in key performance indicator (KPI) reports, including: How are the report tables and columns defined in the metadata?

Data Governance 131

Data Governance Key Performance Indicator Metadata Digital Transformation 131

Alation

JANUARY 9, 2023

Alation joined with Ortecha , a data management consultancy, to publish a white paper providing insights and guidance to stakeholders and decision-makers charged with implementing or modernising data risk management functions. The Increasing Focus On Data Risk Management. Download the complete white paper now.

Risk Management 52

Risk Management Risk Management Metadata 52

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

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

Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. In this tutorial, we will illustrate how RAPIDS can be used to tackle the Kaggle Home Credit Default Risk challenge. With the Home Credit Default Risk Challenge, overfitting is very easy.

Machine Learning 137

Machine Learning Data Science Data Lake Modeling 137

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

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

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

erwin

MAY 31, 2019

The typical notion is that enterprise architects and data (and metadata) architects are in opposite corners. At Avydium , we believe there’s an important middle ground where different architecture disciplines coexist, including enterprise, solution, application, data, metadata and technical architectures. Where do these layers connect?

Data-driven 104

Data-driven Enterprise Metadata Strategy 104

erwin

MAY 20, 2020

Where crisis leads to vulnerability, data governance as an emergency service enables organization management to direct or redirect efforts to ensure activities continue and risks are mitigated. Discover risks. The coronavirus, to most, is an unprecedented and continued unpredictable state of emergency on many levels.

Data Governance 144

Data Governance Metadata Risk Strategy 144

erwin

AUGUST 28, 2020

Put simply, DG is about maximizing the potential of an organization’s data and minimizing the risk. Organizations with a effectively governed data enjoy: Better alignment with data regulations: Get a more holistic understanding of your data and any associated risks, plus improve data privacy and security through better data cataloging.

Data Governance 145

Data Governance IT Cost-Benefit Metadata 145

Cloudera

AUGUST 3, 2021

Advanced analytics empower risk reduction . Advanced analytics and enterprise data are empowering several overarching initiatives in supply chain risk reduction – improved visibility and transparency into all aspects of the supply chain balanced with data governance and security. . Digital Transformation is not without Risk.

Analytics 111

Analytics Digital Transformation Forecasting Risk 111

erwin

SEPTEMBER 3, 2020

You can collect complete application ecosystem information; objectively identify connections/interfaces between applications, using data; provide accurate compliance assessments; and quickly identify security risks and other issues. You can better manage risk because of real-time data coming into the EA space.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

erwin

JANUARY 17, 2020

Data models provide visualization, create additional metadata and standardize data design across the enterprise. Thanks to organizations like Amazon, Netflix and Uber, businesses have changed how they leverage their data and are transforming their business models to innovate – or risk becoming obsolete. SQL or NoSQL?

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

IBM Big Data Hub

OCTOBER 4, 2022

Today, AI presents an enormous opportunity to turn data into insights and actions, to amplify human capabilities, decrease risk and increase ROI by achieving break through innovations. Manual processes that introduce risk and make it hard to scale. Challenges around managing risk. It is an imperative.

Metadata 97

Metadata Risk Management Risk Experimentation 97

O'Reilly on Data

MARCH 20, 2019

Like many others, I’ve known for some time that machine learning models themselves could pose security risks. An attacker could use an adversarial example attack to grant themselves a large loan or a low insurance premium or to avoid denial of parole based on a high criminal risk score. Newer types of fair and private models (e.g.,

Modeling 278

Modeling Machine Learning Predictive Modeling Consulting 278

datapine

SEPTEMBER 29, 2022

It involves: Reviewing data in detail Comparing and contrasting the data to its own metadata Running statistical models Data quality reports. Data processes that depended upon the previously defective data will likely need to be re-initiated, especially if their functioning was at risk or compromised by the defected data.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Rocket-Powered Data Science

JULY 19, 2023

The latter is associated primarily with “watching” the data for interesting patterns, while precursor analytics is associated primarily with training the business systems to quickly identify those specific patterns and events that could be associated with high-risk events, thus requiring timely attention, intervention, and remediation.

Data-driven 188

Data-driven Enterprise Analytics Machine Learning 188

DataKitchen

OCTOBER 20, 2023

Payload DJs facilitate capturing metadata, lineage, and test results at each phase, enhancing tracking efficiency and reducing the risk of data loss. Example 3: Insurance Card Tracking In the pharmaceutical industry, disjointed business processes can cause data loss as customer information navigates through different systems.

Insurance 169

Insurance Metadata Data-driven Data Quality 169

erwin

NOVEMBER 6, 2020

Metadata Harvesting and Ingestion : Automatically harvest, transform and feed metadata from virtually any source to any target to activate it within the erwin Data Catalog (erwin DC). Data Cataloging: Catalog and sync metadata with data management and governance artifacts according to business requirements in real time.

Data Governance 97

Data Governance Metadata Data-driven Visualization 97

CIO Business Intelligence

JULY 10, 2024

And what are the risks that GenAI investments in this domain will turn out to be duds that fail to create real value? However, there is a risk that GenAI tools will draw inaccurate conclusions when summarizing information or translating natural language into query code. Which cybersecurity capabilities does GenAI unlock?

Risk 123

Risk Marketing Metadata Technology 123

erwin

JANUARY 23, 2025

IDC, BARC, and Gartner are just a few analyst firms producing annual or bi-annual market assessments for their research subscribers in software categories ranging from data intelligence platforms and data catalogs to data governance, data quality, metadata management and more. and/or its affiliates in the U.S.

Metadata 52

Metadata Data Quality Data Governance Software 52

O'Reilly on Data

MARCH 23, 2023

What is it, how does it work, what can it do, and what are the risks of using it? But Transformers have some other important advantages: Transformers don’t require training data to be labeled; that is, you don’t need metadata that specifies what each sentence in the training data means. What Are the Risks? O’Reilly, 2022).

IT 348

IT Modeling Testing Risk 348