David Menninger's Analyst Perspectives

NOVEMBER 19, 2024

To improve data reliability, enterprises were largely dependent on data-quality tools that required manual effort by data engineers, data architects, data scientists and data analysts.  With the aim of rectifying that situation, Bigeye’s founders set out to build a business around data observability.

Data Quality 130

Data Quality Dashboards Data-driven Software 130

Anmut

JANUARY 30, 2025

They made us realise that building systems, processes and procedures to ensure quality is built in at the outset is far more cost effective than correcting mistakes once made. How about data quality? Redman and David Sammon, propose an interesting (and simple) exercise to measure data quality.

Data Quality 52

Data Quality Cost-Benefit Statistics Data-driven 52

CIO Business Intelligence

NOVEMBER 27, 2024

Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. But along with siloed data and compliance concerns , poor data quality is holding back enterprise AI projects.

Enterprise 141

Enterprise Data Quality Modeling Structured Data 141

Smart Data Collective

JULY 25, 2024

Mastering data governance in a multi-cloud environment is key! Delve into best practices for seamless integration, compliance, and data quality management.

Data Governance 128

Data Governance Data Quality Management Big Data 128

AWS Big Data

OCTOBER 10, 2023

Data governance is the process of ensuring the integrity, availability, usability, and security of an organization’s data. Due to the volume, velocity, and variety of data being ingested in data lakes, it can get challenging to develop and maintain policies and procedures to ensure data governance at scale for your data lake.

Data Quality 111

Data Quality Data Governance Data Lake Testing 111

CIO Business Intelligence

NOVEMBER 4, 2024

Data security, data quality, and data governance still raise warning bells Data security remains a top concern. Respondents rank data security as the top concern for AI workloads, followed closely by data quality. AI applications rely heavily on secure data, models, and infrastructure.

Marketing 128

Marketing Data Quality Data Governance Digital Transformation 128

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

Alation

JANUARY 20, 2022

Several weeks ago (prior to the Omicron wave), I got to attend my first conference in roughly two years: Dataversity’s Data Quality and Information Quality Conference. Ryan Doupe, Chief Data Officer of American Fidelity, held a thought-provoking session that resonated with me. Step 2: Data Definitions.

Data Quality 94

Data Quality Data Governance Metrics Statistics 94

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 346

Enterprise Deep Learning Data Governance Risk 346

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

TDAN

DECEMBER 2, 2020

Ensuring data quality is an important aspect of data management and these days, DBAs are increasingly being called upon to deal with the quality of the data in their database systems more than ever before. The importance of quality data cannot be overstated.

Data Quality 90

Data Quality Metadata Data Governance Management 90

TDAN

JUNE 30, 2020

You may already have a formal Data Governance program in place. Or … you are presently going through the process of trying to convince your Senior Leadership or stakeholders that a formal Data Governance program is necessary. Maybe you are going through the process of convincing the stakeholders that Data […].

Data Governance 145

Data Governance Data Quality Metadata Data Strategy 145

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 123

Data Governance Unstructured Data Metadata Data Lake 123

erwin

FEBRUARY 13, 2020

When an organization’s data governance and metadata management programs work in harmony, then everything is easier. Data governance is a complex but critical practice. Data Governance Attitudes Are Shifting. Data Governance Attitudes Are Shifting.

Metadata 135

Metadata Data Governance Management Cost-Benefit 135

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. Alation is a founding member, along with Collibra.

Data Governance 123

Data Governance Metadata Unstructured Data Structured Data 123

CIO Business Intelligence

DECEMBER 10, 2024

Align data strategies to unlock gen AI value for marketing initiatives Using AI to improve sales metrics is a good starting point for ensuring productivity improvements have near-term financial impact. When considering the breadth of martech available today, data is key to modern marketing, says Michelle Suzuki, CMO of Glassbox.

Sales 143

Sales Metrics Data-driven Measurement 143

erwin

OCTOBER 29, 2020

Automating data governance is key to addressing the exponentially growing volume and variety of data. Data readiness is everything. Data readiness depends on automation to create the data pipeline. We asked participants to “talk to us about data value chain bottlenecks.”

Data Governance 105

Data Governance Metadata Digital Transformation ROI 105

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

CIO Business Intelligence

MAY 24, 2023

The first published data governance framework was the work of Gwen Thomas, who founded the Data Governance Institute (DGI) and put her opus online in 2003. They already had a technical plan in place, and I helped them find the right size and structure of an accompanying data governance program.

Data Governance 118

Data Governance Data Quality Data Collection Publishing 118

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

DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . QuerySurge – Continuously detect data issues in your delivery pipelines. OwlDQ — Predictive data quality.

Testing 312

Testing Machine Learning Consulting Data Quality 312

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

CIO Business Intelligence

APRIL 29, 2022

Despite soundings on this from leading thinkers such as Andrew Ng , the AI community remains largely oblivious to the important data management capabilities, practices, and – importantly – the tools that ensure the success of AI development and deployment. Further, data management activities don’t end once the AI model has been developed.

Data Governance 145

Data Governance IT Risk Data Lake 145

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

Cloudera

MARCH 3, 2022

Whether the enterprise uses dozens or hundreds of data sources for multi-function analytics, all organizations can run into data governance issues. Bad data governance practices lead to data breaches, lawsuits, and regulatory fines — and no enterprise is immune. . Everyone Fails Data Governance.

Data Governance 100

Data Governance Enterprise Data Quality Metadata 100

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

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

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. Slow Down, Ask Questions.

Data Governance 108

Data Governance Cost-Benefit Enterprise Modeling 108

TDAN

MARCH 15, 2022

1 In this article, I will apply it to the topic of data quality. I will do so by comparing two butterflies, each that represent a common use of data quality: firstly and most commonly in situ for existing systems, and secondly for use […]. We know the phrase, “Beauty is in the eye of the beholder.”1

Data Quality 98

Data Quality IT Data Governance Data Strategy 98

TDAN

MARCH 16, 2021

The purpose of this article is to provide a model to conduct a self-assessment of your organization’s data environment when preparing to build your Data Governance program. Take the […].

Data Governance 105

Data Governance Testing Modeling Data Quality 105

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

CIO Business Intelligence

FEBRUARY 6, 2025

Its about investing in skilled analysts and robust data governance. This means fostering a culture of data literacy and empowering analysts to critically evaluate the tools and techniques at their disposal. It also means establishing clear data governance frameworks to ensure data quality, security and ethical use.

Unstructured Data 115

Unstructured Data Manufacturing Data Governance Sales 115

Octopai

JUNE 26, 2020

In order to figure out why the numbers in the two reports didn’t match, Steve needed to understand everything about the data that made up those reports – when the report was created, who created it, any changes made to it, which system it was created in, etc. Enterprise data governance. Metadata in data governance.

Metadata 98

Metadata Data Governance Enterprise Reporting 98

Alation

FEBRUARY 3, 2022

DataOps practices help organizations overcome challenges caused by fragmented teams and processes and delays in delivering data in consumable forms. So how does data governance relate to DataOps? Data governance is a key data management process. Continuous Improvement Applied to Data Governance.

Data Governance 98

Data Governance Measurement Metadata Testing 98

Octopai

JULY 11, 2022

And when business users don’t complain, but you know the data isn’t good enough to make these types of calls wisely, that’s an even bigger problem. How are you, as a data quality evangelist (if you’re reading this post, that must describe you at least somewhat, right?), Tie data quality directly to business objectives.

Data Quality 98

Data Quality Strategy Business Objectives Sales 98

CIO Business Intelligence

OCTOBER 29, 2024

Good data provenance helps identify the source of potential contamination and understand how data has been modified over time. This is an important element in regulatory compliance and data quality. AI-native solutions have been developed that can track the provenance of data and the identities of those working with it.

Enterprise 134

Enterprise Broadcasting Risk Sales 134