erwin

APRIL 15, 2020

In our businesses, it is vital that we work to develop a deeper understanding of the sources, methods and quality of incoming third-party data. This deeper understanding will help us make better decisions about the risks and rewards of using that external data. Data Governance Methods for Data Distancing.

Data Governance 134

Data Governance Metadata Testing Reporting 134

erwin

MARCH 25, 2021

erwin recently hosted the second in its six-part webinar series on the practice of data governance and how to proactively deal with its complexities. Led by Frank Pörschmann of iDIGMA GmbH, an IT industry veteran and data governance strategist, the second webinar focused on “ The Value of Data Governance & How to Quantify It.”.

Data Governance 109

Data Governance IT Cost-Benefit Risk 109

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). Strengthen data security. How erwin Can Help. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

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

erwin

APRIL 2, 2021

With more companies increasingly migrating their data to the cloud to ensure availability and scalability, the risks associated with data management and protection also are growing. Data Security Starts with Data Governance. Is it sensitive data or are there any risks associated with it?

Data Governance 106

Data Governance Cost-Benefit Risk Metadata 106

CIO Business Intelligence

MAY 17, 2022

Even if the AI apocalypse doesn’t come to pass, shortchanging AI ethics poses big risks to society — and to the enterprises that deploy those AI systems. The following real-world implementation issues highlight prominent risks every IT leader must account for in putting together their company’s AI deployment strategy.

Risk 145

Risk Data Science Consulting Machine Learning 145

erwin

SEPTEMBER 19, 2019

Data governance isn’t a one-off project with a defined endpoint. Data governance, today, comes back to the ability to understand critical enterprise data within a business context, track its physical existence and lineage, and maximize its value while ensuring quality and security. Passing the Data Governance Ball.

Data Governance 108

Data Governance Cost-Benefit Enterprise Modeling 108

Alation

AUGUST 17, 2022

According to analysts, data governance programs have not shown a high success rate. According to CIOs , historical data governance programs were invasive and suffered from one of two defects: They were either forced on the rank and file — who grew to dislike IT as a result. The Risks of Early Data Governance Programs.

Data Governance 92

Data Governance Risk Data-driven Measurement 92

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 106

Data Governance Unstructured Data Metadata Data Lake 106

erwin

FEBRUARY 4, 2021

Better decision-making has now topped compliance as the primary driver of data governance. However, organizations still encounter a number of bottlenecks that may hold them back from fully realizing the value of their data in producing timely and relevant business insights. Data Governance Bottlenecks. Regulations.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

Alation

OCTOBER 5, 2021

What is data governance and how do you measure success? Data governance is a system for answering core questions about data. It begins with establishing key parameters: What is data, who can use it, how can they use it, and why? Why is your data governance strategy failing?

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

Alation

JANUARY 19, 2023

The words “ data governance ” and “fun” are seldom spoken together. The term data governance conjures images of restrictions and control that result in an uphill challenge for most programs and organizations from the beginning. Or they are spending too much time preparing the data for proper use.

Data Governance 94

Data Governance IT Metadata Recreation/Entertainment 94

erwin

JANUARY 24, 2019

They need their data mappings to fall under governance and audit controls, with instant access to dynamic impact analysis and lineage. With an automation framework, data professionals can meet these needs at a fraction of the cost of the traditional manual way. Benefits of an Automation Framework for Data Governance.

Data Governance 71

Data Governance Metadata Data-driven Cost-Benefit 71

CIO Business Intelligence

NOVEMBER 27, 2024

By eliminating time-consuming tasks such as data entry, document processing, and report generation, AI allows teams to focus on higher-value, strategic initiatives that fuel innovation. Above all, robust governance is essential.

Data Governance 132

Data Governance Risk Insurance Metadata 132

erwin

SEPTEMBER 10, 2020

Not Documenting End-to-End Data Lineage Is Risky Busines – Understanding your data’s origins is key to successful data governance. Not everyone understands what end-to-end data lineage is or why it is important. Data Lineage Tells an Important Origin Story.

Data Governance 131

Data Governance Key Performance Indicator Metadata Digital Transformation 131

Cloudera

AUGUST 4, 2021

And if data security tops IT concerns, data governance should be their second priority. Not only is it critical to protect data, but data governance is also the foundation for data-driven businesses and maximizing value from data analytics. But it’s still not easy. But it’s still not easy.

Data Governance 88

Data Governance Metadata Data-driven Enterprise 88

erwin

AUGUST 20, 2020

As a practice, EA involves the documentation, analysis, design and implementation of an organization’s assets and structure. With an enterprise architecture management suite (EAMS) , an organization can define and document its structure to more effectively determine how to achieve its goals. Reduced risks and costs.

Enterprise 140

Enterprise Cost-Benefit Risk Data Governance 140

Alation

SEPTEMBER 7, 2021

In this blog we will discuss how Alation helps minimize risk with active data governance. Now that you have empowered data scientists and analysts to access the Snowflake Data Cloud and speed their modeling and analysis, you need to bolster the effectiveness of your governance models.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

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

MARCH 8, 2019

GDPR) and to ensure peak business performance, organizations often bring consultants on board to help take stock of their data assets. This sort of data governance “stock check” is important but can be arduous without the right approach and technology. That’s where data governance comes in ….

Data Governance 65

Data Governance Metadata Data Warehouse Data Quality 65

erwin

JUNE 14, 2019

Its past successes – and future potential – are well documented, chronicled in the billion-dollar valuations of the frontrunners in the practice. Four main areas in retail demonstrate digital transformation, with a healthy data governance initiative driving them all. Data can tell you. Risks come with any investment.

Digital Transformation 111

Digital Transformation Data Governance Risk Data-driven 111

erwin

APRIL 9, 2020

As someone who works in data governance and intelligence , I’d like to look at three aspects of disaster planning and business continuity in particular. Documented Policies and Procedures. 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

CIO Business Intelligence

SEPTEMBER 17, 2024

All this while CIOs are under increased pressure to deliver more competitive capabilities, reduce security risks, connect AI with enterprise data, and automate more workflows — all areas where architecture disciplines have a direct role in influencing outcomes.

Enterprise 145

Enterprise Digital Transformation Cost-Benefit Risk 145

erwin

OCTOBER 17, 2019

it ensures not only access to proper documentation but also current, updated information. The Regulatory Rationale for Integrating Data Management & Data Governance. Data security/risk management. EA should be commonplace in data security planning. Data governance.

Enterprise 106

Enterprise Digital Transformation Data Governance Risk Management 106

CIO Business Intelligence

OCTOBER 2, 2024

And the other is retrieval augmented generation (RAG) models, where pieces of data from a larger source are vectorized to allow users to “talk” to the data. For example, they can take a thousand-page document, have it ingested by the model, and then ask the model questions about it. For us, it’s all part of data governance.

Management 141

Management Data Governance Cost-Benefit Structured Data 141

erwin

APRIL 29, 2020

In the event of a change in data expectations, data lineage provides a way to determine which downstream applications and processes are affected by the change and helps in planning for application updates. Business terms and data policies should be implemented through standardized and documented business rules.

Key Performance Indicator 111

Key Performance Indicator Metadata Data Governance Data Quality 111

CIO Business Intelligence

APRIL 1, 2024

Deloitte 2 meanwhile found that 41% of business and technology leaders said a lack of talent, governance, and risks are barriers to broader GenAI adoption. Capturing the “as-is” state of your environment, you’ll develop topology diagrams and document information on your technical systems. Assess your readiness.

Uncertainty 142

Uncertainty Data Lake Consulting Risk 142

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk. Humans can’t keep up.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Alation

FEBRUARY 10, 2021

The way enterprises implement data governance is changing. In the past, data governance either emphasized exercising tight control over data or fitting people into rigid roles and processes. With both approaches, data governance is a hurdle to productive data & analytics rather than an enabler.

Data Governance 52

Data Governance Data-driven Enterprise Risk 52

Octopai

JUNE 24, 2019

There are a number of scenarios that necessitate data governance tools. Businesses operating within strict industry regulations, utilizing analytics software, and/or regularly consolidating data in key subject areas will find themselves looking into data governance tools to help them achieve their goals.

Data Governance 58

Data Governance Metadata Unstructured Data Software 58

CIO Business Intelligence

DECEMBER 19, 2023

Create these six generative AI workstreams CIOs should document their AI strategy for delivering short-term productivity improvements while planning visionary impacts. These workstreams require documenting a vision, assigning leaders, and empowering teams to experiment.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

CIO Business Intelligence

OCTOBER 2, 2024

Data governance Strong data governance is the foundation of any successful AI strategy. It’s essential to regularly audit your AI systems to detect and mitigate biases in data collection, algorithm design and decision-making processes. Identify gaps related to ethics, transparency, risk and compliance.

Gap analysis 119

Gap analysis Risk Manufacturing Data Governance 119

CIO Business Intelligence

NOVEMBER 21, 2023

Ask IT leaders about their challenges with shadow IT, and most will cite the kinds of security, operational, and integration risks that give shadow IT its bad rep. That’s not to downplay the inherent risks of shadow IT.

IT 137

IT Risk Cost-Benefit Risk Management 137

erwin

JANUARY 17, 2020

In the modern context, data modeling is a function of data governance. While data modeling has always been the best way to understand complex data sources and automate design standards, modern data modeling goes well beyond these domains to accelerate and ensure the overall success of data governance in any organization.

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

O'Reilly on Data

JULY 28, 2020

This isn’t always simple, since it doesn’t just take into account technical risk; it also has to account for social risk and reputational damage. A product needs to balance the investment of resources against the risks of moving forward without a full understanding of the data landscape.

Marketing 362

Marketing Experimentation Metrics Testing 362

CIO Business Intelligence

MAY 13, 2024

watsonx.governance is a toolkit for governing generative AI and machine learning models. It focuses on three core areas of documentation: compliance, risk management, and model lifecycle management — processes IBM says are intertwined. Artificial Intelligence, Data Governance, Generative AI, IBM per resource unit.

Machine Learning 122

Machine Learning Risk Modeling Enterprise 122

DataKitchen

FEBRUARY 2, 2023

The crazy idea is that data teams are beyond the boom decade of “spending extravagance” and need to focus on doing more with less. This will drive a new consolidated set of tools the data team will leverage to help them govern, manage risk, and increase team productivity. What will exist at the end of 2025?

Metadata 130

Metadata Testing Risk Data Science 130