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

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

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

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. In short, yes.

Data Quality 63

Data Quality Data Integration Metadata Cost-Benefit 63

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

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 111

IoT Machine Learning Metadata Data-driven 111

CIO Business Intelligence

FEBRUARY 26, 2025

The problem is that, before AI agents can be integrated into a companys infrastructure, that infrastructure must be brought up to modern standards. In addition, because they require access to multiple data sources, there are data integration hurdles and added complexities of ensuring security and compliance.

IT 141

IT Enterprise Interactive Data Quality 141

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. Points of integration. Sources, like IoT.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

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

BI-Survey

FEBRUARY 17, 2020

Data and data management processes are everywhere in the organization so there is a growing need for a comprehensive view of business objects and data. It is therefore vital that data is subject to some form of overarching control, which should be guided by a data strategy. This is where data governance comes in.

Data Governance 89

Data Governance Data Warehouse Data Quality Data Strategy 89

Octopai

AUGUST 3, 2022

It’s also a critical trait for the data assets of your dreams. What is data with integrity? Data integrity is the extent to which you can rely on a given set of data for use in decision-making. Where can data integrity fall short? Too much or too little access to data systems.

Data Integration 98

Data Integration Manufacturing Data Quality Data Governance 98

erwin

FEBRUARY 6, 2020

As organizations deal with managing ever more data, the need to automate data management becomes clear. Last week erwin issued its 2020 State of Data Governance and Automation (DGA) Report. One piece of the research that stuck with me is that 70% of respondents spend 10 or more hours per week on data-related activities.

Management 144

Management Data Governance Cost-Benefit Metadata 144

TDAN

SEPTEMBER 19, 2023

Information technology (IT) plays a vital role in data governance by implementing and maintaining strategies to manage, protect, and responsibly utilize data. Through advanced technologies and tools, IT ensures that data is securely stored, backed up, and accessible to authorized personnel.

Data Governance 81

Data Governance IT Strategy Management 81

Jim Harris

DECEMBER 24, 2015

Have you ever experienced that sinking feeling, where you sense if you don’t find data quality, then data quality will find you? I hope that you enjoy reading this blog post, but most important, I hope you always remember: “Data are friends, not food.” Data Silos. You, Data-Dude, takin’ on the defects.

Data Quality 56

Data Quality Enterprise Business Intelligence Data Governance 56

DataKitchen

AUGUST 16, 2024

At DataKitchen, we think of this is a ‘meta-orchestration’ of the code and tools acting upon the data. Data Pipeline Observability: Optimizes pipelines by monitoring data quality, detecting issues, tracing data lineage, and identifying anomalies using live and historical metadata.

Marketing 133

Marketing Data Quality Testing Metadata 133

erwin

APRIL 29, 2020

Many large organizations, in their desire to modernize with technology, have acquired several different systems with various data entry points and transformation rules for data as it moves into and across the organization. Data lineage offers proof that the data provided is reflected accurately. Data Governance.

Key Performance Indicator 111

Key Performance Indicator Data Governance Metadata Data Quality 111

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

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

IBM Big Data Hub

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

Data Architecture 52

Data Architecture Data Quality Strategy Data Lake 52

erwin

FEBRUARY 19, 2021

It involves establishing policies and processes to ensure information can be integrated, accessed, shared, linked, analyzed and maintained across an organization. Better data quality. It harvests metadata from various data sources and maps any data element from source to target and harmonize data integration across platforms.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

Alation

AUGUST 5, 2021

What is Data Quality? Data quality is defined as: the degree to which data meets a company’s expectations of accuracy, validity, completeness, and consistency. By tracking data quality , a business can pinpoint potential issues harming quality, and ensure that shared data is fit to be used for a given purpose.

Data Quality 52

Data Quality IT Data Governance Sales 52

CIO Business Intelligence

JUNE 24, 2024

These 10 strategies cover every critical aspect, from data integrity and development speed, to team expertise and executive buy-in. Data done right Neglect data quality and you’re doomed. It’s simple: your AI is only as good as the data it learns from. Invest heavily in data governance.

Data Quality 124

Data Quality ROI Data Integration Metrics 124

CIO Business Intelligence

JANUARY 24, 2024

They also need to establish clear privacy, regulatory compliance, and data governance policies. Many industries and regions have strict regulations governing data privacy and security,” Miller says. This type of environment can also be deeply rewarding for data and analytics professionals.”

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

IBM Big Data Hub

MARCH 25, 2022

A data fabric is an architectural approach that enables organizations to simplify data access and data governance across a hybrid multicloud landscape for better 360-degree views of the customer and enhanced MLOps and trustworthy AI. Protection is applied on each data pipeline.

Metadata 104

Metadata Data Quality Data Governance Data Integration 104

Alation

MAY 24, 2022

In a sea of questionable data, how do you know what to trust? Data quality tells you the answer. It signals what data is trustworthy, reliable, and safe to use. It empowers engineers to oversee data pipelines that deliver trusted data to the wider organization. Today, as part of its 2022.2

Data Quality 52

Data Quality Metadata Reporting Metrics 52

IBM Big Data Hub

AUGUST 23, 2023

Because of this, when we look to manage and govern the deployment of AI models, we must first focus on governing the data that the AI models are trained on. This data governance requires us to understand the origin, sensitivity, and lifecycle of all the data that we use. and watsonx.data.

Data Governance 52

Data Governance Enterprise Modeling Risk 52

CIO Business Intelligence

APRIL 1, 2024

Ensure that data is cleansed, consistent, and centrally stored, ideally in a data lake. Data preparation, including anonymizing, labeling, and normalizing data across sources, is key. You’ll also institute guardrails for data governance, data quality, data integrity, and data security.

Uncertainty 142

Uncertainty Data Lake Consulting Risk 142

CIO Business Intelligence

FEBRUARY 2, 2024

Developer, Professional Certification Mastering Data Management and Technology SAP Certified Application Associate – SAP Master Data Governance The Art of Service Master Data Management Certification The Art of Service Master Data Management Complete Certification Kit validates the candidate’s knowledge of specific methods, models, and tools in MDM.

Management 116

Management Data Governance Cost-Benefit Testing 116

Alation

OCTOBER 28, 2021

This data is also a lucrative target for cyber criminals. Healthcare leaders face a quandary: how to use data to support innovation in a way that’s secure and compliant? Data governance in healthcare has emerged as a solution to these challenges. Uncover intelligence from data. Protect data at the source.

Data Governance 52

Data Governance Measurement Data Quality Metrics 52

erwin

DECEMBER 9, 2024

And if it isnt changing, its likely not being used within our organizations, so why would we use stagnant data to facilitate our use of AI? The key is understanding not IF, but HOW, our data fluctuates, and data observability can help us do just that. And lets not forget about the controls.

Metadata 52

Metadata Data Quality Sales Modeling 52

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

CIO Business Intelligence

NOVEMBER 29, 2022

Here, I’ll highlight the where and why of these important “data integration points” that are key determinants of success in an organization’s data and analytics strategy. Layering technology on the overall data architecture introduces more complexity. For data warehouses, it can be a wide column analytical table.

Data Architecture 111

Data Architecture Data Integration IoT Data-driven 111

AWS Big Data

JULY 29, 2024

This ensures that each change is tracked and reversible, enhancing data governance and auditability. History and versioning : Iceberg’s versioning feature captures every change in table metadata as immutable snapshots, facilitating data integrity, historical views, and rollbacks.

Metadata 126

Metadata Snapshot Data Lake Metrics 126

erwin

MAY 27, 2020

They should automatically generate data models , providing a simple, graphical display to visualize a wide range of enterprise data sources based on a common repository of standard data assets through a single interface. Data siloes, of course, are the enemies of data governance.

Modeling 98

Modeling Metadata Data Governance Visualization 98

CIO Business Intelligence

MARCH 22, 2022

Then virtualize your data to allow business users to conduct aggregated searches and analyses using the business intelligence or data analytics tools of their choice. . Set up unified data governance rules and processes. With data integration comes a requirement for centralized, unified data governance and security.

Analytics 115

Analytics Key Performance Indicator Data Warehouse Data-driven 115

AWS Big Data

JULY 13, 2023

Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices. Goals – Lay the foundation for a data platform that can be used in the future by internal and external stakeholders.

Optimization 98

Optimization B2B Data Quality Sales 98

erwin

JANUARY 17, 2019

Data governance is more important to the enterprise than ever before. It ensures everyone in the organization can discover and analyze high-quality data to quickly deliver business value. A mature and sustainable data governance initiative must include data integration.

Metadata 63

Metadata Data Governance Data Quality Data-driven 63