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

CIO Business Intelligence

MARCH 25, 2025

Types of data debt include dark data, duplicate records, and data that hasnt been integrated with master data sources. Using the companys data in LLMs, AI agents, or other generative AI models creates more risk.

Risk 140

Risk Cost-Benefit Data-driven Digital Transformation 140

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 347

Enterprise Deep Learning Data Governance Risk 347

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

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

FEBRUARY 6, 2025

The hype around large language models (LLMs) is undeniable. They promise to revolutionize how we interact with data, generating human-quality text, understanding natural language and transforming data in ways we never thought possible. Even basic predictive modeling can be done with lightweight machine learning in Python or R.

Unstructured Data 115

Unstructured Data Manufacturing Data Governance Sales 115

CIO Business Intelligence

NOVEMBER 4, 2024

Over the next one to three years, 84% of businesses plan to increase investments in their data science and engineering teams, with a focus on generative AI, prompt engineering (45%), and data science/data analytics (44%), identified as the top areas requiring more AI expertise. Cost, by comparison, ranks a distant 10th.

Marketing 128

Marketing Data Quality Data Governance Digital Transformation 128

AWS Big Data

DECEMBER 19, 2024

Initially, the data inventories of different services were siloed within isolated environments, making data discovery and sharing across services manual and time-consuming for all teams involved. Implementing robust data governance is challenging. Oghosa Omorisiagbon is a Senior Data Engineer at HEMA.

Data Governance 52

Data Governance Publishing Data-driven Metadata 52

CIO Business Intelligence

APRIL 29, 2022

Forward-thinking transformation leaders have realised that more focus needs to be placed on ‘data-centric value creation’ and have made this the pre-eminent organising principle in their organisations. Many organisations focus too heavily on fine tuning their computational models in their pursuit of ‘quick-wins.’ About Andrew P.

Data Governance 145

Data Governance IT Risk Data Lake 145

CIO Business Intelligence

NOVEMBER 28, 2024

Unsurprisingly, more than 90% of respondents said their organization needs to shift to an AI-first operating model by the end of this year to stay competitive — and time to do so is running out. Focus on data governance and ethics With AI becoming more pervasive, the ethical and responsible use of it is paramount.

IT 130

IT Data Governance Risk Consulting 130

CIO Business Intelligence

DECEMBER 20, 2024

Data architecture definition Data architecture describes the structure of an organizations logical and physical data assets, and data management resources, according to The Open Group Architecture Framework (TOGAF). An organizations data architecture is the purview of data architects. Curate the data.

Data Architecture 122

Data Architecture Management Consulting Internet of Things 122

CIO Business Intelligence

NOVEMBER 27, 2024

Good data governance has always involved dealing with errors and inconsistencies in datasets, as well as indexing and classifying that structured data by removing duplicates, correcting typos, standardizing and validating the format and type of data, and augmenting incomplete information or detecting unusual and impossible variations in the data.

Enterprise 141

Enterprise Data Quality Structured Data Modeling 141

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 109

Data Governance Unstructured Data Metadata Data Lake 109

AWS Big Data

JANUARY 15, 2025

Data landscape in EUROGATE and current challenges faced in data governance The EUROGATE Group is a conglomerate of container terminals and service providers, providing container handling, intermodal transports, maintenance and repair, and seaworthy packaging services. Eliminate centralized bottlenecks and complex data pipelines.

IoT 100

IoT Machine Learning Metadata Data-driven 100

CIO Business Intelligence

JUNE 9, 2023

The ever-increasing emphasis on data and analytics has organizations paying more attention to their data governance strategies these days, as a recent Gartner survey found that 63% of data and analytics leaders say their organizations are increasing investment in data governance. The reason?

Data Governance 105

Data Governance Cost-Benefit Data-driven Publishing 105

O'Reilly on Data

MAY 21, 2019

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in London earlier this year. A typical data pipeline for machine learning.

Machine Learning 279

Machine Learning Technology Deep Learning Data Science 279

KDnuggets

DECEMBER 13, 2021

How exactly does AI model governance help tackle these issues? And how can you ensure you’re using it to best fit your needs? Read on.

Modeling 159

Modeling IT Data Governance 159

CIO Business Intelligence

JANUARY 21, 2025

The World Economic Forum shares some risks with AI agents , including improving transparency, establishing ethical guidelines, prioritizing data governance, improving security, and increasing education. Even simple use cases had exceptions requiring business process outsourcing (BPO) or internal data processing teams to manage.

Cost-Benefit 142

Cost-Benefit Data-driven Strategy Marketing 142

CIO Business Intelligence

APRIL 26, 2024

That data is in the process of being unified on a multilayered platform that offers a variety of data services, including data ingestion, data management, data governance, and data security. We’re modernizing existing products to get to this entire data analytics value chain.”

Modeling 114

Modeling IT Machine Learning Data Governance 114

O'Reilly on Data

FEBRUARY 4, 2019

In this post, I’ll describe some of the key areas of interest and concern highlighted by respondents from Europe, while describing how some of these topics will be covered at the upcoming Strata Data conference in London (April 29 - May 2, 2019). Data Platforms. Data Integration and Data Pipelines.

Machine Learning 279

Machine Learning Enterprise IoT Big Data 279

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. . Hydrosphere.io — Deploys batch Spark functions, machine-learning models, and assures the quality of end-to-end pipelines.

Testing 300

Testing Machine Learning Consulting Data Science 300

O'Reilly on Data

APRIL 25, 2019

The O’Reilly Data Show Podcast: Neelesh Salian on data lineage, data governance, and evolving data platforms. In this episode of the Data Show , I spoke with Neelesh Salian , software engineer at Stitch Fix , a company that combines machine learning and human expertise to personalize shopping.

Machine Learning 261

Machine Learning Data Governance Software Technology 261

David Menninger's Analyst Perspectives

NOVEMBER 19, 2024

Data lineage is now one of three core components of the company’s data observability platform, alongside automated monitoring and anomaly detection. Having trust in data is crucial to business decision-making.

Data Quality 130

Data Quality Dashboards Data-driven Software 130

DataKitchen

DECEMBER 7, 2021

If you can’t wait, check out this DataKitchen white paper, Build a Data Mesh Factory with DataOps. Data Teams: A Unified Management Model for Successful Data-Focused Teams, by Jesse Anderson. If your data nerd leads a team of data nerds, big data projects, or aspires to one day, “Data Teams” is the book for them. ??

Data-driven 246

Data-driven Data Governance Big Data Data Science 246

CIO Business Intelligence

DECEMBER 5, 2024

For instance, in claims management, insurers would assess claims based on incomplete, poorly cleaned data, leading to inaccuracies in evaluating claims. They had an AI model in place intended to improve fraud detection. However, the model underperformed, and its outputs showed discrepancies compared to manual validations.

Enterprise 105

Enterprise Insurance Unstructured Data Business Intelligence 105

AWS Big Data

AUGUST 13, 2024

Amazon DataZone has announced a set of new data governance capabilities—domain units and authorization policies—that enable you to create business unit-level or team-level organization and manage policies according to your business needs. Data domains form a foundational pillar in data governance frameworks.

Data Governance 109

Data Governance Metadata Enterprise Sales 109

DataKitchen

DECEMBER 13, 2021

DataOps is NOT Just DevOps for Data. Launch Your DataOps Journey with the DataOps Maturity Model. Data Governance as Code. 2021 Data Engineering Survey: Burned-Out Data Engineers are Calling for DataOps. Add DataOps Tests to Deploy with Confidence. Top 5 White Papers. The Seven Steps to Implement DataOps.

Data Architecture 246

Data Architecture Data Governance Testing Modeling 246

Cloudera

JUNE 14, 2024

At a time when artificial intelligence (AI) and tools like generative AI (GenAI) and large language models (LLMs) have exploded in popularity, getting the most out of organizational data is critical to driving business value and carving out a competitive market advantage.

Data Governance 74

Data Governance Data-driven Insurance Enterprise 74

O'Reilly on Data

FEBRUARY 11, 2020

They have too many different data sources and too much inconsistent data. They don’t have the resources they need to clean up data quality problems. The building blocks of data governance are often lacking within organizations. In other words, the sheer preponderance of data sources isn’t a bug: it’s a feature.

Data Quality 363

Data Quality Metadata Data Governance Publishing 363

O'Reilly on Data

FEBRUARY 11, 2019

Foundational data technologies. Machine learning and AI require data—specifically, labeled data for training models. Data lineage, data catalog, and data governance solutions can increase usage of data systems by enhancing trustworthiness of data. Data Platforms.

Big Data 269

Big Data Technology Machine Learning Deep Learning 269

CIO Business Intelligence

NOVEMBER 21, 2024

This is Dell Technologies’ approach to helping businesses of all sizes enhance their AI adoption, achieved through the combined capabilities with NVIDIA—the building blocks for seamlessly integrating AI models and frameworks into their operations.

IT 111

IT Cost-Benefit Optimization Manufacturing 111

AWS Big Data

DECEMBER 4, 2024

Under the federated mesh architecture, each divisional mesh functions as a node within the broader enterprise data mesh, maintaining a degree of autonomy in managing its data products. This model balances node or domain-level autonomy with enterprise-level oversight, creating a scalable and consistent framework across ANZ.

Metadata 93

Metadata Data Governance Data Quality Data-driven 93

CIO Business Intelligence

MARCH 6, 2024

What has IT’s role been in the transformation to a SaaS model? We built that end-to-end data model and process from scratch while we ran the old business. We knew we had a unique opportunity to build a new end-to-end architecture with a common AI-powered data model. Today, we’re a $1.6 Today, we’re a $1.6

Modeling 116

Modeling Management IT Metrics 116

CIO Business Intelligence

JANUARY 30, 2025

There have been many organizations that state that AI governance should come from governments first. While there is a lot of effort and content that is now available, it tends to be at a higher level which will require work to be done to create a governance model specifically for your organization.

Testing 93

Testing Metrics Cost-Benefit Modeling 93

CIO Business Intelligence

JANUARY 7, 2025

Transformational CIOs continuously invest in their operating model by developing product management, design thinking, agile, DevOps, change management, and data-driven practices. For AI to deliver safe and reliable results, data teams must classify data properly before feeding it to those hungry LLMs.

Digital Transformation 143

Digital Transformation Experimentation Cost-Benefit Strategy 143

O'Reilly on Data

MAY 9, 2023

Using AI means auditing the outputs of AI systems to ensure that they’re fair; it means documenting the behaviors of AI models and training data sets so that users know how the data was collected and what biases are inherent in that data. When a model makes a mistake, there has to be some kind of human accountability.

Modeling 296

Modeling Reporting Data Governance IT 296

AWS Big Data

NOVEMBER 22, 2024

Now, with support for dbt Cloud, you can access a managed, cloud-based environment that automates and enhances your data transformation workflows. This upgrade allows you to build, test, and deploy data models in dbt with greater ease and efficiency, using all the features that dbt Cloud provides.

Data Lake 83

Data Lake Data Warehouse Cost-Benefit Data Transformation 83