How to Improve Data Quality by Using Feedback Loops

Dataversity

In this blog, we will take a look at: The impact poor Data Quality has on organizations and practical advice for how to overcome this challenge through the use of feedback loops. Poor Data Quality can cost organizations millions each year.

Why Data Quality Matters

The Data Administration Newsletter

Quality is never an accident. ” John Ruskin, prominent Victorian era social thinker Data-driven decision-making is fast becoming a critical business strategy for organizations in every sector. It is always the result of intelligent effort.”

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Being Data-Driven Means Embracing Data Quality and Consistency Through Data Governance

Dataversity

Organizations are constantly coming to us wanting help in becoming more “data-driven.” The post Being Data-Driven Means Embracing Data Quality and Consistency Through Data Governance appeared first on DATAVERSITY. Click to learn more about author Terence Siganakis.

Good AI in 2021 Starts with Great Data Quality

Dataversity

The post Good AI in 2021 Starts with Great Data Quality appeared first on DATAVERSITY. Click here to learn more about Heine Krog Iversen. More and more companies want to use artificial intelligence (AI) in their organization to improve operations and performance.

What Is Data Quality?

Cprime

Data is often the most valuable asset for a company because it’s possible to use it in so many ways. You can use data to improve processes, gather insights, or predict trends through data analysis. What Is Data Quality? Why Does Data Quality Matter?

Expanding Role of Data Governance, Metadata Management, and Data Quality

The Data Administration Newsletter

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.

Balance Data Quality with Data Agility!

ElegantJ BI

Data Quality vs. Data Agility – A Balanced Approach! When it comes to analytical quality versus analytical agility, we might see the issue in the same light. Original Post: Data Quality and Data Agility are Both Important to Success!

Data Agility and Popularity vs Data Quality in Self-Serve BI and Analytics!

ElegantJ BI

One of the most valuable aspects of self-serve business intelligence is the opportunity it provides for data and analytical sharing among business users within the organization. So, there is definitely a need to provide both approaches in data analysis.

Data Agility and ‘Popularity’? vs. Data Quality in Self-Serve BI and Analytics!

ElegantJ BI

One of the most valuable aspects of self-serve business intelligence is the opportunity it provides for data and analytical sharing among business users within the organization. So, there is definitely a need to provide both approaches in data analysis.

Lean Governance: The Next Machine to Change the World

Dataversity

Lean GovernanceTM is the next machine to change the world of Data Governance and Enterprise Data Management. As proponents of lean thinking, we view corporations as data factories that produce information for operations, reporting, and financial modeling.

New in Tableau Catalog: Improved search and monitoring for data quality warnings

Tableau

Data discovery and trust have been core principles of Tableau Catalog (part of Tableau Data Management ) since its introduction with Tableau 2019.3. With every release, we continue to add features that help users find and use trusted data with confidence. Kate Grinevskaja.

How to Diagnose Your Organization’s Data Assets

Dataversity

Before relying on analytics for all or part of your strategic decision-making, it’s critical to implement suitable processes to ensure that data flows smoothly through all business departments while preserving its quality, accessibility, usability, and security using these tips.

Multidomain vs. Multiple-Domain MDM: The Difference Is More Than You Think

Dataversity

In my eight years as a Gartner analyst covering Master Data Management (MDM) and two years advising clients and prospects at a leading vendor, I have seen first-hand the importance of taking a multidomain approach to MDM. Click to learn more about author Bill O’Kane.

Speeders, Cheaters, Bots and Repeaters: How to design your research study with data quality in mind

Userzoom

Responses from these participants can wreck your data by artificially influencing success rates, task times, and overall ratings. Not only do they sully your data, but also increase the amount of time spent on data cleaning and re-fielding.

Three Reasons to Take a More Holistic Approach to Data Management

Dataversity

Taking a holistic approach to data requires considering the entire data lifecycle – from gathering, integrating, and organizing data to analyzing and maintaining it. Companies must create a standard for their data that fits their business needs and processes.

Why Use Interactive Financial Dashboards for Reporting? A Complete Guide

Dataversity

Humans process visual data far more quickly and effectively than other ways of presenting information. The need for visual data, which speaks for thousands of words, has sparked the emergence of interactive dashboards. Click to learn more about author Ashok Sharma.

Speed Up AI Development by Hiring a Chief Data Officer

Dataversity

The role of the chief data officer (CDO) has evolved more over the last decade than any of the C-suite. The post Speed Up AI Development by Hiring a Chief Data Officer appeared first on DATAVERSITY. Click to learn more about author Jitesh Ghai.

The Dos and Don’ts of Navigating the Multi-Billion-Dollar Big Data Industry

Dataversity

Analysts predict the big data market will grow by over $100 billion by 2025 due to more and more companies investing in technology to drive more business decisions from big data collection.

Can You Trust Your Data?

Dataversity

In order to be successful in today’s ultra-competitive business environment, companies must be committed to data. Data needs to truly be at the heart of every decision an organization makes, but this is easier said than done. The post Can You Trust Your Data?

Why Effective Data Management Is Key in a Connected World

Dataversity

The smart factory and plant now incorporate an array of connected technologies, all generating a vast volume of data. As a result, data will continue its exponential growth, […]. The post Why Effective Data Management Is Key in a Connected World appeared first on DATAVERSITY.

The Three Pillars of Trusted AI

Dataversity

Click to learn more about author Jett Oristaglio. As AI becomes ubiquitous across dozens of industries, the initial hype of new technology is beginning to be replaced by the challenge of building trustworthy AI systems.

Maximizing the Value of Data for Your Health Care Organization

Dataversity

The data value chain goes all the way from data capture and collection to reporting and sharing of information and actionable insights. As data doesn’t differentiate between industries, different sectors go through the same stages to gain value from it.

Pillars of Data Integrity: The New Business Imperative

Dataversity

Innovations in data-driven intelligence continue to power transformation initiatives for modern businesses. While these innovations improve how we collect, store, manipulate, and analyze data, that is not enough to fully leverage data.

New in Tableau Catalog: Improved search and monitoring for data quality warnings

Tableau

Data discovery and trust have been core principles of Tableau Catalog (part of Tableau Data Management ) since its introduction with Tableau 2019.3. With every release, we continue to add features that help users find and use trusted data with confidence. Kate Grinevskaja.

Five Data Governance Trends for Digital-Driven Business Outcomes in 2021

Dataversity

To date, many organizations have focused on formalizing data consumption practices through distribution technology, access-based delivery mechanisms for analytics, and AI functions. The post Five Data Governance Trends for Digital-Driven Business Outcomes in 2021 appeared first on DATAVERSITY.

Increasing the Business Impact of Data Management Using Force-Field Analysis

Dataversity

This article introduces Force-Field Analysis (FFA) [1], a tool that one of us (Tom) has used for many years to help understand and summarize the impacts of multiple factors in the data space. Click to learn more about co-author John Ladley. Click to learn more about co-author Thomas Redman.

Dear Laura: Agile Data Governance

Dataversity

As I’ve been working to challenge the status quo on Data Governance, I get a lot of questions about how it will “really” work. The post Dear Laura: Agile Data Governance appeared first on DATAVERSITY. Click to learn more about author Laura Madsen. Welcome to the Dear Laura blog series!

Avoid These Mistakes on Your Data Warehouse and BI Projects: Part 3

Dataversity

In Part 1 and Part 2 of this series, we described how data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations. The post Avoid These Mistakes on Your Data Warehouse and BI Projects: Part 3 appeared first on DATAVERSITY.

A Bridge Between Data Lakes and Data Warehouses

Dataversity

It has been ten years since Pentaho Chief Technology Officer James Dixon coined the term “data lake.” While data warehouse (DWH) systems have had longer existence and recognition, the data industry has embraced the more […].

How a Data Catalog Enables Remote Collaboration

Dataversity

The post How a Data Catalog Enables Remote Collaboration appeared first on DATAVERSITY. Click to learn more about author Emily Washington. Forty-two percent of the U.S.

An Introduction to Metadata Management

Dataversity

According to IDC, the size of the global datasphere is projected to reach 163 ZB by 2025, leading to the disparate data sources in legacy systems, new system deployments, and the creation of data lakes and data warehouses. Click to learn more about author Sowmya Tejha Kandregula.

How to Ensure Data Integrity in Your Organization

Dataversity

We are living in an era of data and analytics. It is the time when organizations are consuming, generating, modifying, and exchanging an insane amount of data. The post How to Ensure Data Integrity in Your Organization appeared first on DATAVERSITY.

Data Governance Can Create “Data Trusts” for Consumers in Organizations

Dataversity

This has been possible by integrating and aggregating Multi-sources as well as taming the ‘Data Swamps’ to deliver quality data. The post Data Governance Can Create “Data Trusts” for Consumers in Organizations appeared first on DATAVERSITY.

The Third Pillar of Trusted AI: Ethics

Dataversity

Building an accurate, fast, and performant model founded upon strong Data Quality standards is no easy task. Click to learn more about author Scott Reed. Taking the model into production with governance workflows and monitoring for sustainability is even more challenging.

Guide to Digital Transformation: Data-first Architecture

Dataversity

The goal of digital transformation remains the same as ever – to become more data-driven. We have learned how to gain a competitive advantage by capturing business events in data. The post Guide to Digital Transformation: Data-first Architecture appeared first on DATAVERSITY.

Data Mesh in Practice: Learnings from a Customer Journey

Dataversity

In my last blog post, I introduced the data mesh concept and explored the link between data democratization and data mesh. The post Data Mesh in Practice: Learnings from a Customer Journey appeared first on DATAVERSITY. Click to learn more about author Mathias Golombek.

Where Is the Data Technology Industry Headed?

Dataversity

This announcement is interesting and causes some of us in the tech industry to step back and consider many of the factors involved in providing data technology […]. The post Where Is the Data Technology Industry Headed? Click here to learn more about Heine Krog Iversen.