In this post, we share a short video that gives you and your team some simple rules to follow for achieving greater traction, particularly amongst your senior management.

Did you know that over on LinkedIn we have a popular group called the Data Quality and Data Governance Professionals Forum?

With over 7,500 members, 100’s of topics discussed, and many years of excellent community engagement - it will give you a headstart on some of those thorny data quality or data governance questions you’ve been wrestling with.

Why not check out some of the most popular discussions below, or submit your own question into the group?

Managing change is critical to a data quality project. You need to take the organisation with you and above all, this means getting the business onside.

How do you create a library of data quality rules that can be shared for the common good of your organisation. Read on to find out…

How do you prevent poor levels of supplier data quality impacting your organisation?

The answer? Through the adoption of a Data Quality Firewall and ongoing Data Quality SLA process.

This post creates a blueprint for creating your own Data Quality Firewall and ensuring your data quality SLA provides certified, high quality data throughout your organisation.

Understanding how data flows around your business to deliver value to your internal and external customers is critical to effective data quality management. In this article we take a look at some simple techniques required to deliver effective information chain management.

Data Quality Scorecards are one of the most vital resources for guiding your team and motivating your project sponsors towards the goal of data quality management.

But how do you go about creating a data quality scorecard and what are some of the key points to consider?

Here are 23 pointers to set you in the right direction.

In this article you will learn how to create a data quality business case that convinces sponsors of the benefits of your data quality efforts and the value of supporting your approach.

In this article, data governance expert Mirjam Visscher provides details of how to improve your business definitions using a Definition Quality Indicator process.

This article explores why building a data quality vision that can grow is one of the most critical skills a data quality leader possesses.

To help you kick-start your data quality initiative we’ve highlighted some existing data quality frameworks and data quality methodologies that are available both online and offline.

Creating a Data Quality KPI (Key Performance Indicator) is a critcal step in measuring, monitoring and controlling the impact of poor quality data in any organisation.

In this post, we respond to a request for help from one of our community members struggling to create Data Quality KPI’s:

A poorly designed data model can cause major data quality issues when the final information system is launched. In the second part of his expert modelling series, John Owens provides another detailed tutorial that explains the core techniques of effective data structure modelling as found in his Integrated Modelling Method (IMM).

Our aim with this tutorial series is to help our readers learn some of the key modelling skills that are typically required for data quality improvement.

What is a data quality policy and what are the key sections?

Who should create it and how is it executed?

There are many questions posed when creating a data quality policy for your organisation. Use this article as a guide to getting started and creating a data quality policy that is right for your organisation.

If you’re working as a data analyst perhaps it’s time to shift your focus to data quality analyst roles to help increase your career potential? If that’s something you’ve considered then the next question you’ll pose is what additional skills will I need? Fortunately you’ll find that many of your data analyst skills are exactly what companies are searching for in a data quality analyst.

In this interview, highly experienced Data Quality author and practitioner, Laura Sebastian-Coleman, provides a detailed account of her experiences in launching and growing a Data Quality Centre of Excellence (CoE) in a large organisation.

How do you get started with identifying the true causes of Data Quality Root-Cause issues?

This article examines 10 techniques that are proven to help you get to the heart of your data quality issues and move from a reactive to proactive and longer-term defect elimination.

In this paper, Sundara and Sankara provide a practical guide for implementing data quality as a service via a cloud based architecture.

Easily one of the single biggest causes of data defects in any organisation is poor quality information entered at the start of the information chain via data entry interfaces.

This article provides some simple, practical and cheap techniques to dramatically improve the data quality of human entered information.