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

MARCH 19, 2025

Many companies today are struggling to manage their data, overwhelmed by data volumes, velocity, and variety. On top of that, they are storing data in IT environments that are increasingly complex, including in the cloud and on mainframes, sometimes simultaneously, all while needing to ensure proper security and compliance.

Data Integration 52

Data Integration Data Quality Visualization Risk 52

CIO Business Intelligence

MAY 8, 2024

In the age of big data, where information is generated at an unprecedented rate, the ability to integrate and manage diverse data sources has become a critical business imperative. Traditional data integration methods are often cumbersome, time-consuming, and unable to keep up with the rapidly evolving data landscape.

Data Integration 102

Data Integration IoT Cost-Benefit Machine Learning 102

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. After a few months, daily sales surpassed 2 million dollars, rendering the threshold obsolete.

Data Quality 116

Data Quality Statistics Visualization Metrics 116

DataKitchen

APRIL 13, 2021

Testing and Data Observability. Sandbox Creation and Management. 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. . OwlDQ — Predictive data quality.

Testing 304

Testing Machine Learning Consulting Data Science 304

AWS Big Data

DECEMBER 4, 2024

Ask questions in plain English to find the right datasets, automatically generate SQL queries, or create data pipelines without writing code. Data teams struggle to find a unified approach that enables effortless discovery, understanding, and assurance of data quality and security across various sources.

Data Analytics 104

Data Analytics Analytics Data Lake Data Quality 104

O'Reilly on Data

JUNE 18, 2019

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI AI starts with ‘good’ data” is a statement that receives wide agreement from data scientists, analysts, and business owners. Data integration and cleaning. Data unification and integration.

Machine Learning 279

Machine Learning Data Quality Statistics Modeling 279

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. It takes days for data engineers to identify and implement data quality rules.

Data Quality 98

Data Quality Statistics Data Lake Visualization 98

AWS Big Data

MAY 23, 2024

Hundreds of 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. We also show how to take action based on the data quality results.

Data Quality 120

Data Quality Metrics Data Lake Sales 120

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

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. Searching for data was the biggest time-sinking culprit followed by managing, analyzing and preparing data.

Management 144

Management Data Governance Cost-Benefit Metadata 144

Smart Data Collective

APRIL 30, 2021

However, your data integrity practices are just as vital. But what exactly is data integrity? How can data integrity be damaged? And why does data integrity matter? What is data integrity? Indeed, without data integrity, decision-making can be as good as guesswork.

Data Integration 122

Data Integration Strategy Software Management 122

Sisense

AUGUST 28, 2020

Uncomfortable truth incoming: Most people in your organization don’t think about the quality of their data from intake to production of insights. However, as a data team member, you know how important data integrity (and a whole host of other aspects of data management) is. What is data integrity?

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

Smart Data Collective

SEPTEMBER 21, 2021

With the increased adoption of cloud and emerging technologies like the Internet of Things, data is no longer confined to the boundaries of organizations. The increased amounts and types of data, stored in various locations eventually made the management of data more challenging. Challenges in maintaining data.

Management 131

Management Internet of Things Data Quality Data Integration 131

CIO Business Intelligence

MARCH 24, 2023

It encompasses the people, processes, and technologies required to manage and protect data assets. The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

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

DataKitchen

JANUARY 25, 2022

When internal resources fall short, companies outsource data engineering and analytics. There’s no shortage of consultants who will promise to manage the end-to-end lifecycle of data from integration to transformation to visualization. . The challenge is that data engineering and analytics are incredibly complex.

Consulting 244

Consulting Testing Data Lake Data Quality 244

erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. Harvest data. Govern data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

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

AWS Big Data

JUNE 6, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning (ML), and application development. Hundreds of thousands of customers use data lakes for analytics and ML to make data-driven business decisions.

Data Quality 98

Data Quality Data-driven Data Lake Metrics 98

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

Data Virtualization

OCTOBER 31, 2024

Reading Time: 2 minutes When making decisions that are critical to national security, governments rely on data, and those that leverage the cutting edge technology of generative AI foundation models will have a distinct advantage over their adversaries. Pros and Cons of generative AI.

Management 52

Management Modeling Data Integration Technology 52

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

AWS Big Data

JANUARY 15, 2025

Their terminal operations rely heavily on seamless data flows and the management of vast volumes of data. With the addition of these technologies alongside existing systems like terminal operating systems (TOS) and SAP, the number of data producers has grown substantially.

IoT 111

IoT Machine Learning Metadata Data-driven 111

Data Virtualization

JANUARY 21, 2025

However, companies are still struggling to manage data effectively, to implement GenAI applications that deliver proven business value. Gartner predicts that by the end of this year, 30%.

Management 52

Management Data Integration Technology Data Warehouse 52

CIO Business Intelligence

FEBRUARY 2, 2024

As data and analytics become the beating heart of the enterprise, it’s increasingly critical for the business to have access to consistent, high-quality data assets. Master data management (MDM) is required to ensure the enterprise’s data is consistent, accurate, and controlled. for 180 days access.

Management 116

Management Data Governance Cost-Benefit Testing 116

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. Data Profiling. “I Defect Prevention.

Data Quality 56

Data Quality Enterprise Business Intelligence Data Governance 56

Alation

AUGUST 9, 2022

On top of this, we’re living through the age of big data , where more information is being processed and stored by organisations that also have to manage regulations. But in the four years since it came into force, have companies reached their full potential for data integrity? What is data integrity?

Data Integration 52

Data Integration Data Quality Measurement Data-driven 52

DataKitchen

AUGUST 16, 2024

As the pioneer in the DataOps category, we are proud to have laid the groundwork for what has become an essential approach to managing data operations in today’s fast-paced business environment. It handles connector management and workflow impact analysis and maintains audit logs.

Marketing 126

Marketing Data Quality Testing Metadata 126

DataKitchen

SEPTEMBER 21, 2023

These layers help teams delineate different stages of data processing, storage, and access, offering a structured approach to data management. In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets.

Testing 173

Testing Data Quality Predictive Modeling Metrics 173

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

DataKitchen

MAY 10, 2024

The Second of Five Use Cases in Data Observability Data Evaluation: This involves evaluating and cleansing new datasets before being added to production. This process is critical as it ensures data quality from the onset. Examples include regular loading of CRM data and anomaly detection.

Data Quality 133

Data Quality Testing Software Dashboards 133

DataKitchen

MAY 10, 2021

The data factory transforms raw materials (source data) into finished goods (analytics) using a series of processing steps (Figure 1). As such, applying manufacturing methods, such as lean manufacturing, to data analytics produces tremendous quality and efficiency improvements. It’s not about data quality .

Testing 214

Testing Manufacturing Data Quality Statistics 214

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

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?

Data Quality 63

Data Quality Data Governance People Analytics Data-driven 63

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. Assemble the A-team Don’t settle for mediocrity.

Data Quality 124

Data Quality ROI Data Integration Metrics 124

CIO Business Intelligence

NOVEMBER 13, 2024

Manual data extraction, validation, and transformation are tedious and error-prone, often leading to project delays, high costs, and disruptions in daily operations. This no-code SAP data management platform handles the nitty-gritty of data migration.

Cost-Benefit 64

Cost-Benefit Data-driven Data Integration Data Quality 64