erwin

APRIL 4, 2019

A strong data governance framework is central to the success of any data-driven organization because it ensures this valuable asset is properly maintained, protected and maximized. But despite this fact, enterprises often face push back when implementing a new data governance initiative or trying to mature an existing one.

Data Governance 75

Data Governance Data Quality Risk Management Data-driven 75

TDAN

JANUARY 19, 2021

In October 2020, the Office of the Comptroller of the Currency (OCC) announced a $400 million civil monetary penalty against Citibank for deficiencies in enterprise-wide risk management, compliance risk management, data governance, and internal controls.

Data Governance 80

Data Governance Risk Management Risk Management 80

IBM Big Data Hub

NOVEMBER 28, 2022

Metadata management performs a critical role within the modern data management stack. It helps blur data silos, and empowers data and analytics teams to better understand the context and quality of data. This, in turn, builds trust in data and the decision-making to follow.

Metadata 56

Metadata Data Quality Data-driven Data Governance 56

erwin

SEPTEMBER 17, 2020

Replace manual and recurring tasks for fast, reliable data lineage and overall data governance. It’s paramount that organizations understand the benefits of automating end-to-end data lineage. The importance of end-to-end data lineage is widely understood and ignoring it is risky business.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

erwin

APRIL 29, 2020

An understanding of the data’s origins and history helps answer questions about the origin of data in a Key Performance Indicator (KPI) reports, including: How the report tables and columns are defined in the metadata? Who are the data owners? Data lineage offers proof that the data provided is reflected accurately.

Key Performance Indicator 111

Key Performance Indicator Metadata Data Governance Data Quality 111

Octopai

JANUARY 19, 2020

It will not surprise you to learn all 11 of the bank-relevant principles are related to data in some form or fashion. Here’s a sampling: – Principle 1 covers data governance, including “a firm’s policies on data confidentiality, integrity, and availability, as well as risk-management policies.”.

Metadata 89

Metadata Risk Management Business Intelligence Data Governance 89

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.

Metadata 52

Metadata Data Quality Data Governance Software 52

Octopai

JUNE 19, 2023

Everyone has access to the same data and the same understanding of what the data represents, reducing miscommunications and discrepancies. Catalogs also allow for better Risk Management; data catalogs help businesses maintain regulatory compliance by providing a clear record of what data is stored and how it’s used.

Metadata 98

Metadata Data Governance Measurement Risk Management 98

Alation

DECEMBER 8, 2022

Data governance is growing in urgency and prominence. As regulations grow more complex (and compliance fines more onerous) organizations aren’t just adapting data governance frameworks to drive compliance – they’re leveraging governance to fuel a growing range of use cases, from collaboration to stewardship, discovery, and more.

Data Governance 52

Data Governance Data-driven Reporting Strategy 52

TDAN

APRIL 6, 2021

There is an ever-increasing awareness of concerns about data privacy, corporate data breaches, increasing demands for regulatory compliance. There are also emerging concerns about the ways that big data analytics potentially influence and bias automated decision-making.

Risk Management 64

Risk Management Risk Management Big Data 64

Octopai

JULY 9, 2020

When conducted manually, however, which has tended to be the normal mode of operation before companies discovered automation – or machine learning data lineage solutions, data lineage can be extremely tedious and time-consuming for BI & Analytics teams. Automated Data Lineage Enables Data Teams to Deliver Faster Results.

Insurance 98

Insurance Risk Management Machine Learning Metadata 98

Alation

JUNE 14, 2021

And third is what factors CIOs and CISOs should consider when evaluating a catalog – especially one used for data governance. The Role of the CISO in Data Governance and Security. They want CISOs putting in place the data governance needed to actively protect data. So CISOs must protect data.

Data Governance 97

Data Governance Recreation/Entertainment Data Lake Metadata 97

erwin

DECEMBER 20, 2018

The driving factors behind data governance adoption vary. Whether implemented as preventative measures (risk management and regulation) or proactive endeavors (value creation and ROI), the benefits of a data governance initiative is becoming more apparent. Defining Data Governance.

Data Governance 40

Data Governance ROI Risk Management Metadata 40

Cloudera

JUNE 29, 2023

To improve the way they model and manage risk, institutions must modernize their data management and data governance practices. Up your liquidity risk management game Historically, technological limitations made it difficult for financial institutions to accurately forecast and manage liquidity risk.

Data Architecture 85

Data Architecture Risk Management Risk Management 85

erwin

NOVEMBER 13, 2020

Data Security & Risk Management. Innovation Management. Data Center Consolidation. Application Portfolio Management. Data Governance (knowing what data you have and where it is). Digital Transformation. Compliance/Legislation. Artificial Intelligence. Mergers and Acquisitions.

Enterprise 131

Enterprise Digital Transformation Key Performance Indicator Data-driven 131

IBM Big Data Hub

APRIL 20, 2023

This trust depends on an understanding of the data that inform risk models: where does it come from, where is it being used, and what are the ripple effects of a change?

Risk 68

Risk Risk Management Reporting Metadata 68

Domino Data Lab

APRIL 3, 2019

Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form.

Machine Learning 84

Machine Learning Data Governance Metadata Data Science 84

Alation

NOVEMBER 30, 2021

This means data protection and risk mitigation must be promoted and consolidated with other enterprise risk management processes. Data governance is the path to accomplishing this. The first step is recognizing the direct relationship between data governance and risk.

Data Governance 52

Data Governance Risk Management Risk Enterprise 52

Ontotext

APRIL 21, 2021

The problem was the left hand had no way of knowing the systemic issues around data governance, risk management and compliance framework. Through rich metadata and automated reasoning , it is possible to express the complexity of assets and their relationships. Conclusion.

Metadata 59

Metadata Finance Cost-Benefit Data Quality 59

Alation

MARCH 14, 2023

All critical data elements (CDEs) should be collated and inventoried with relevant metadata, then classified into relevant categories and curated as we further define below. Store Where individual departments have their own databases for metadata management, data will be siloed, meaning it can’t be shared and used business-wide.

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

Alation

OCTOBER 26, 2021

They enjoy improved governance, which follows from documenting ownership of business terms and formulas. And, by implementing continuous data reviews, finance teams better support compliance and risk management. In many ways, the catalog is a foundational platform for human collaboration around trusted data.

Finance 52

Finance Data Transformation Enterprise Metrics 52

Alation

FEBRUARY 8, 2022

Making the experts responsible for service streamlines the data-request pipeline, delivering higher quality data into the hands of those who need it more rapidly. Some argue that data governance and quality practices may vary between domains. Interoperable and governed by global standards. ” 1.

Data Governance 52

Data Governance Data-driven Metadata Enterprise 52

AWS Big Data

AUGUST 14, 2023

In the same way, overly restrictive data governance practices that either prevent data products from taking root at all, or pare them back too aggressively (deforestation), can over time create “data deserts” that drive both the producers and consumers of data within an organization to look elsewhere for their data needs.

Management 98

Management Risk Measurement Optimization 98

Grooper

OCTOBER 23, 2019

Lack of competitiveness or business losses seem to be the main drivers to becoming more proactive with data governance and management. What you’re shooting for is enterprise-wide information governance. Responsibility for managing your company’s data must be clearly defined and supported.

Metrics 59

Metrics Measurement Data-driven Strategy 59

Laminar Security

MAY 3, 2023

They define DSPM technologies this way: “DSPM technologies can discover unknown data and categorize structured and unstructured data across cloud service platforms. Start by using DSG to establish the data security policies and posture, and then take the final three steps to assess the DSPM deployment.”

Management 40

Management Risk Risk Management Data Processing 40

TDAN

SEPTEMBER 17, 2019

There have been a couple of different things converged in my media feeds that highlight a key issue that all data management professionals and leaders in information management need to be conscious of – Group Think. This manifests itself in at least two ways in the following examples I’ll use to illustrate my points.

Management 80

Management Risk Management Risk Data Governance 80

Andrew White

JANUARY 11, 2021

What are you seeing as the differences between a Chief Analytics Officer and the Chief Data Officer? Governance. Value Management or monetization. Risk Management (most likely within context of governance). Product Management. See The Future of Data and Analytics: Reengineering the Decision, 2025.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

TDAN

APRIL 20, 2021

Modern airplanes travel the world through all kinds of weather via the use of radar. Oxford Dictionary defines radar as “a system for detecting the presence, direction, distance and speed of an object. Radar is used to indicate there is something that has not yet come to the attention of a person or a group.” […].

Risk 52

Risk Risk Management Metadata Data Governance 52

CIO Business Intelligence

MARCH 5, 2025

Chinas Interim Measures for Generative AI Services Aligns with global emphasis on transparency, content moderation, and data governance, similar to the EU AI Act and OECD principles. Emphasizes governance and risk management similar to the EU AI Act and Canadas Bill C-27.

Risk 121

Risk Risk Management Measurement Modeling 121

erwin

APRIL 21, 2020

Another foundational purpose of a data catalog is to streamline, organize and process the thousands, if not millions, of an organization’s data assets to help consumers/users search for specific datasets and understand metadata , ownership, data lineage and usage.

Measurement 97

Measurement Sales Data Governance Metadata 97

erwin

APRIL 21, 2020

One of the biggest lessons we’re learning from the global COVID-19 pandemic is the importance of data, specifically using a data catalog to comply, collaborate and innovate to crisis-proof our businesses. Catalog critical systems and data elements, plus enable the calculation and evaluation of key performance measures.

Measurement 96

Measurement Sales Data Governance Metadata 96

CIO Business Intelligence

MAY 14, 2025

The collision of traditional EA with cognitive-driven data architectures Enterprise architecture has a storied history of providing organizations with a structured methodology for aligning IT systems with business goals, focusing on standardized business processes, data governance and technology stacks.

Enterprise 115

Enterprise Data Architecture Data-driven Data Quality 115