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.

Data Quality Problems Everywhere You Look

The Data Administration Newsletter

Data is everywhere! But can you find the data you need? What can be done to ensure the quality of the data? How can you show the value of investing in data? Can you trust it when you get it?

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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.

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.”

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?

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 Quality Management: Growing Role in Big Data Initiatives [Updated] | Simplilearn

Simplilearn

Data is at the heart of everything important for businesses these days. Whether it’s customer data, sales forecasts, supply chain scheduling, or any other critical process, data drives most business operations.

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.

Excessive Bureaucracy Is Killing Data Governance

Dataversity

Despite the best-in-class Data Governance policies and programs, failure rates are still too high. Current efforts often fall short of delivering trusted data, despite huge investments of time and money. Click to learn more about author Steve Zagoudis.

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.

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.

4 Risks of Storing Large Amounts of Unstructured Data

Dataversity

In 2013, the big data headline was the incredible statistic that 90% of all data in the history of the entire human race had been created in the previous two years. The amount of structured and unstructured data we’ve created was so mind-boggling that we deemed it […].

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.

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.

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.

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.

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.

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?

The State of NLP: 5 Trends Shaping the Industry

Dataversity

Data Blogs | Information From Enterprise Leaders Data Education Data Governance & Data Quality | News & Articles Data Governance Blogs Smart Data Blogs Smart Data News, Articles, & Education

DataOps Highlights the Need for Automated ETL Testing (Part 2)

Dataversity

DataOps, which focuses on automated tools throughout the ETL development cycle, responds to a huge challenge for data integration and ETL projects in general. Click to learn more about author Wayne Yaddow.

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.

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.

A New Approach to Integrate Metadata and Ease Daily Data Operations

Dataversity

With the ever-increasing variety of tool stacks, managing data has become more complex. The tool-stack needs to be managed along with the data that is either stored or processed by them. As we manage this disparate data actively, self-service business intelligence is possible.

Data is Risky Business: Return to Sender

The Data Administration Newsletter

A recent experience brought home to me the critical importance of good quality data in even the simplest of processes, particularly as processes become more automated and data driven.

5 Critical Factors to Consider When Choosing a Data Warehouse Solution

Dataversity

We have seen an unprecedented increase in modern data warehouse solutions among enterprises in recent years. Experts believe that this trend will continue: The global data warehousing market is projected to reach $51.18 Click to learn more about author Ammar Ali.

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.

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.

Three Tips for Safeguarding Against Data Breaches

Dataversity

The post Three Tips for Safeguarding Against Data Breaches appeared first on DATAVERSITY. Click to learn more about author Balaji Ganesan.

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.

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.

Data Professional Introspective: What Good Data Looks Like – Part 4

The Data Administration Newsletter

This column is next in the series of how organizations achieve and sustain significant improvements in fundamental data management disciplines, in their journey to Great Data.

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.

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.

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.