O'Reilly on Data

NOVEMBER 28, 2023

Generative AI has been the biggest technology story of 2023. In enterprises, we’ve seen everything from wholesale adoption to policies that severely restrict or even forbid the use of generative AI. Our survey focused on how companies use generative AI, what bottlenecks they see in adoption, and what skills gaps need to be addressed.

Enterprise 344

Enterprise Testing Modeling Reporting 344

erwin

DECEMBER 9, 2024

When it comes to using AI and machine learning across your organization, there are many good reasons to provide your data and analytics community with an intelligent data foundation. For instance, Large Language Models (LLMs) are known to ultimately perform better when data is structured.

Metadata 52

Metadata Data Quality Sales Modeling 52

CIO Business Intelligence

NOVEMBER 20, 2024

At its Microsoft Ignite 2024 show in Chicago this week, Microsoft and industry partner experts showed off the power of small language models (SLMs) with a new set of fine-tuned, pre-trained AI models using industry-specific data. Rockwell Automation is adding FT Optix Food & Beverage to the Azure AI catalog as well.

Manufacturing 122

Manufacturing Marketing Finance Modeling 122

Timo Elliott

JANUARY 6, 2022

Like the proverbial man looking for his keys under the streetlight , when it comes to enterprise data, if you only look at where the light is already shining, you can end up missing a lot. Remember that dark data is the data you have but don’t understand. So how do you find your dark data? Create a catalog.

IT 135

IT Metadata Data-driven Data Governance 135

AWS Big Data

AUGUST 8, 2024

Thousands of organizations build data integration pipelines to extract and transform data. They establish data quality rules to ensure the extracted data is of high quality for accurate business decisions. These rules commonly assess the data based on fixed criteria reflecting the current business state.

Data Quality 115

Data Quality Statistics Visualization Metrics 115

Alation

MARCH 24, 2021

The third installment of the quarterly Alation State of Data Culture Report was recently released, highlighting the data challenges enterprises face as they continue investing in artificial intelligence (AI). AI fails when it’s fed bad data, resulting in inaccurate or unfair results.

Reporting 105

Reporting Data Quality Business Driver Enterprise 105

IBM Big Data Hub

MARCH 25, 2022

To simplify data access and empower users to leverage trusted information, organizations need a better approach that provides better insights and business outcomes faster, without sacrificing data access controls. There are many different approaches, but you’ll want an architecture that can be used regardless of your data estate.

Metadata 104

Metadata Data Quality Data Governance Data Integration 104

erwin

JANUARY 23, 2025

Companies are leaning into delivering on data intelligence and governance initiatives in 2025 according to our recent State of Data Intelligence research. Data intelligence software is continuously evolving to enable organizations to efficiently and effectively advance new data initiatives.

Metadata 52

Metadata Data Quality Data Governance Software 52

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

IBM Big Data Hub

MAY 9, 2023

We stand on the frontier of an AI revolution. Over the past decade, deep learning arose from a seismic collision of data availability and sheer compute power, enabling a host of impressive AI capabilities. It sounds like a joke, but it’s not, as anyone who has tried to solve business problems with AI may know.

Enterprise 128

Enterprise Technology Modeling Cost-Benefit 128

Alation

NOVEMBER 4, 2021

This week I was talking to a data practitioner at a global systems integrator. 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 Governance 94

Data Governance Metadata Data Quality Enterprise 94

AWS Big Data

AUGUST 19, 2024

In today’s data-driven world, the ability to seamlessly integrate and utilize diverse data sources is critical for gaining actionable insights and driving innovation. Use case Consider a large ecommerce company that relies heavily on data-driven insights to optimize its operations, marketing strategies, and customer experiences.

Analytics 118

Analytics Data-driven Data Integration Data Lake 118

AWS Big Data

OCTOBER 9, 2024

Today, customers are embarking on data modernization programs by migrating on-premises data warehouses and data lakes to the AWS Cloud to take advantage of the scale and advanced analytical capabilities of the cloud. Data parity can help build confidence and trust with business users on the quality of migrated data.

Data Quality 114

Data Quality Data Lake Data Warehouse Metrics 114

erwin

MAY 22, 2025

As SAP PowerDesigner approaches its end of life (EOL), you could soon find yourself plunged into data modeling darkness. Limited connectivity PowerDesigners restrictions on data-platform integration will hinder your ability to adapt and scale. Because data modeling is more crucial than ever to keep up in the AI race.

Modeling 52

Modeling Uncertainty Metadata Data Integration 52

Alation

JULY 19, 2021

Metadata is information about data. A clothing catalog or dictionary are both examples of metadata repositories. Indeed, a popular online catalog, like Amazon, offers rich metadata around products to guide shoppers: ratings, reviews, and product details are all examples of metadata. What Is Metadata? Why Is Metadata Important?

Metadata 105

Metadata Management Data Governance Machine Learning 105

Alation

MAY 27, 2021

For data-driven enterprises, data governance is no longer an option; it’s a necessity. Businesses are growing more dependent on data governance to manage data policies, compliance, and quality. For these reasons, a business’ data governance approach is essential. Data Democratization.

Data Governance 98

Data Governance Data Quality Enterprise Machine Learning 98

DataKitchen

JUNE 7, 2021

This is a common question that we hear from our conversations with data scientists, engineers and analysts. Hopefully, with metrics in place, you can show measured improvements in productivity and quality that will win converts. We view the steps in analytics creation and data operations as a manufacturing process.

Testing 130

Testing IT Data-driven Measurement 130

AWS Big Data

JULY 25, 2024

This blog post is co-written with Raj Samineni from ATPCO. In today’s data-driven world, companies across industries recognize the immense value of data in making decisions, driving innovation, and building new products to serve their customers.

Data Lake 115

Data Lake Metadata Sales Publishing 115

Alation

JUNE 14, 2021

The Role of Catalog in Data Security. Recently, I dug in with CIOs on the topic of data security. Recently, I dug in with CIOs on the topic of data security. What came as no surprise was the importance CIOs place on taking a broader approach to data protection. The Role of the CISO in Data Governance and Security.

Data Governance 97

Data Governance Recreation/Entertainment Data Lake Metadata 97

Octopai

APRIL 19, 2021

Aptly named, metadata management is the process in which BI and Analytics teams manage metadata, which is the data that describes other data. In other words, data is the context and metadata is the content. Without metadata, BI teams are unable to understand the data’s full story. TDWI – David Loshin.

Metadata 59

Metadata Management Business Intelligence Data Governance 59

Alation

FEBRUARY 3, 2022

The goal of DataOps is to create predictable delivery and change management of data and all data-related artifacts. 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 98

Data Governance Measurement Metadata Testing 98

AWS Big Data

AUGUST 13, 2024

In today’s data-driven world, seamless integration and transformation of data across diverse sources into actionable insights is paramount. With AWS Glue, you can discover and connect to hundreds of diverse data sources and manage your data in a centralized data catalog.

Data Processing 114

Data Processing Visualization Data Lake Data Processing 114

Cloudera

APRIL 1, 2024

This recognition underscores Cloudera’s commitment to continuous customer innovation and validates our ability to foresee future data and AI trends, and our strategy in shaping the future of data management. Cloudera, a leader in big data analytics, provides a unified Data Platform for data management, AI, and analytics.

Unstructured Data 105

Unstructured Data Cost-Benefit Metadata Machine Learning 105

erwin

NOVEMBER 6, 2020

Prashant Parikh, erwin’s Senior Vice President of Software Engineering, talks about erwin’s vision to automate every aspect of the data governance journey to increase speed to insights. The clear benefit is that data stewards spend less time building and populating the data governance framework and more time realizing value and ROI from it.

Data Governance 97

Data Governance Metadata Data-driven Visualization 97

Alation

FEBRUARY 13, 2020

Data catalogs have quickly become a core component of modern data management. Organizations with successful data catalog implementations see remarkable changes in the speed and quality of data analysis, and in the engagement and enthusiasm of people who need to perform data analysis.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

IBM Big Data Hub

NOVEMBER 4, 2022

Data is the new oil and organizations of all stripes are tapping this resource to fuel growth. However, data quality and consistency are one of the top barriers faced by organizations in their quest to become more data-driven. Unlock quality data with IBM. and its leading data observability offerings.

Data Quality 56

Data Quality Metadata Data Governance Data-driven 56

Cloudera

AUGUST 6, 2024

Over the past several years, data leaders asked many questions about where they should keep their data and what architecture they should implement to serve an incredible breadth of analytic use cases. The future for most data teams will be multi-cloud and hybrid. It no longer matters where the data is.

Metadata 82

Metadata Cost-Benefit Management Enterprise 82

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

Management 79

Management Metadata Data Architecture Data Lake 79

erwin

NOVEMBER 14, 2019

Data governance tools used to occupy a niche in an organization’s tech stack, but those days are gone. The rise of data-driven business and the complexities that come with it ushered in a soft mandate for data governance and data governance tools. It is also used to make data more easily understood and secure.

Data Governance 105

Data Governance Data-driven Cost-Benefit Metadata 105

IBM Big Data Hub

NOVEMBER 14, 2023

Data monetization is a business capability where an organization can create and realize value from data and artificial intelligence (AI) assets. A value exchange system built on data products can drive business growth for your organization and gain competitive advantage.

Strategy 103

Strategy Data-driven Cost-Benefit Measurement 103

Cloudera

MARCH 22, 2023

Cloudera Data Platform (CDP) is no different: it’s a hybrid data platform that meets organizations’ needs to get to grips with complex data anywhere, turning it into actionable insight quickly and easily. And, crucial for a hybrid data platform, it does so across hybrid cloud. That’s where observability comes in.

Metrics 88

Metrics Data Governance Cost-Benefit Dashboards 88

Cloudera

MAY 3, 2024

One of the worst-kept secrets among data scientists and AI engineers is that no one starts a new project from scratch. As a result, data scientists will often begin a project by developing an understanding of the data and the problem space and will then go out and find an example that is closest to what they are trying to accomplish.

Data Processing 71

Data Processing Machine Learning Enterprise Risk 71

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

IBM Big Data Hub

JUNE 12, 2023

Companies rely heavily on data and analytics to find and retain talent, drive engagement, improve productivity and more across enterprise talent management. However, analytics are only as good as the quality of the data, which must be error-free, trustworthy and transparent. What is data quality? million each year.

Data Quality 63

Data Quality Data Governance People Analytics Data-driven 63

erwin

MAY 13, 2020

The role of data modeling (DM) has expanded to support enterprise data management, including data governance and intelligence efforts. Metadata management is the key to managing and governing your data and drawing intelligence from it. Types of Data Models: Conceptual, Logical and Physical.

Data Governance 93

Data Governance Enterprise Modeling Management 93

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? Common data governance challenges.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

IBM Big Data Hub

AUGUST 2, 2023

Companies rely heavily on data and analytics to find and retain talent, drive engagement, and improve productivity. However, analytics are only as good as the quality of the data, which aims to be error-free, trustworthy, and transparent. What is data quality? Data quality is critical for data governance.

Data Quality 60

Data Quality Snapshot Data Governance Data-driven 60