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Ten Steps to Data Quality


Testimonials

The course has helped me put into perspective and break down the areas of data quality that should fall under investigation in any project - the steps methodology ensures you have captured all the areas that affect data quality completely."

Eirini Basta, Local Data Steward, Business Systems, HEINEKEN UK Limitedan

"What an excellent class and instructor. I know I will be using the methodology that was taught in this class. This was the best data quality related class I've attended."

 

"Excellent content; Excellent Instructor; Great Presentation; Tons of usable information. All-around Excellent class."

 

"The class was great and could really help me with some of the challenges that we are currently facing."

 

"Effective class that I will be able to use on my job."

 

"I'm impressed with everything about this workshop, especially the way Danette involved her audience in the presentation."

 

"Great course - should be required … as we move toward implementing on-going data quality efforts."

 

"Good instructor. Kept things relevant and at the right pace."

 

"Danette challenged me to think of things from the perspective of others."

 

 

2 Day Seminar & Workshop

Ten Steps to Data Quality

Register On-line:
4-5 December 2014, London

2-3 June 2015, London

PDF File IRM UK Seminars 2014-2015 Brochure

Click here for an in-house quote request or for further information regarding in-house training.

Overview
Simply put, information quality is providing the correct set of accurate information, at the correct time and place, to the correct people. However, ensuring quality information is far from simple. Whether you are just starting a project or are already in production, it is not unusual to find that data quality issues prevent organizations from realizing the full benefit of their investment in new business processes and systems.

Join us to learn the Ten Steps to Quality Data and Trusted Information™ – a practical approach to creating, improving, and managing the quality of information critical to running your business, satisfying customers, and achieving company goals. If you working on real data quality-related projects that need real results, this is the seminar for you.   What you learn here applies to all kinds of data and every type of organization – for-profit businesses of all sizes, education, government, healthcare, and nonprofit – because all depend on trusted information to succeed.

Key topics include:

  • The Ten Steps™ process
  • The Framework for Information Quality
  • The Information Life Cycle
  • Analyzing the information environment
  • Assessing data quality and business impact 
  • Conducting root cause analysis and implementing controls
  • Essential communication to meet information quality needs
  • Real-life application of the framework and methodology

Come with your particular needs in mind, learn how these topics apply to your situation and leave with realistic methods for improving information quality. Be prepared to participate as discussion, individual and group exercises, and applying what is learned to a course project are an integral part of the seminar.  Both foundational data quality concepts and practical application are included. 

This course is based on the extensive experience of the trainer/author/consultant and the book Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information(Morgan Kaufmann Publishers, 2008) by Danette McGilvray.

Learning Objectives

  • Turn data quality challenges into actionable projects with clear objectives.
  • Connect data quality issues to business priorities.
  • Understand concepts that are fundamental to data quality management, such as the Framework for Information Quality, information life cycle, data quality dimensions, business impact techniques, root cause analysis techniques, etc.
  • Choose the appropriate steps/activities from the Ten Steps process to address business needs.
  • Apply many of the steps and techniques to a course project during the seminar.
  • Obtain templates and examples to use in the attendees’ own situations.

Seminar and Workshop Outline

The Data and Information Quality Challenge

  • Information and data quality defined
  • Approaches to data quality in projects
  • Your data quality challenges

 Key Concepts – A necessary foundation for understanding information quality

  • Framework for Information Quality (FIQ) - Components that impact information quality:
    • Business Goals/Strategy/Issues/Opportunities
    • Information Life Cycle (POSMAD – Plan, Obtain, Store and Share, Maintain, Apply, Dispose)
    • Key Components that affect information quality (Data, Processes, People/Organizations, Technology)
    • Interaction between the Information Life Cycle and the Key Components
    • Location (Where) and Time (When and How Long)
    • Broad-Impact Components (RRISC – Requirements and Constraints, Responsibility, Improvement and Prevention, Structure and Meaning, Communication, Change)
  • Information and Data Quality Improvement Cycle (Assess, Analyze, Action)
  • Data Governance, Stewardship, and Data Quality
  • The Ten Steps™ methodology – key concepts plus the Ten Steps™ process

Step-by-Step:  The Ten Steps™ Process

  • Each of the Ten Steps is covered in the seminar with instructions, techniques, examples, templates and best practices.  The Ten Steps are the concepts in action.
  • Data quality tools will also be discussed in the applicable steps. 
  • Exercises and working on a course project with a team give attendees the opportunity to practice what is learned.

Step 1   Determine Business Need and Approach

  • “Connecting-the-dots” between the data quality issue and business needs
  • Define and agree on the issue, the opportunity, or the goal to guide all work done throughout the project. (Refer to this step throughout the other steps in order to keep the goal at the forefront of all activities.)

Step 2   Analyze Information Environment

  • Gather, compile, and analyze information about the current situation and the information environment.
  • Document and verify the information life cycle, which provides a basis for future steps, ensures that relevant data are being assessed, and helps discover root causes
  • Design the data capture and assessment plan

Step 3   Assess Data Quality

  • Evaluate data quality for the data quality dimensions applicable to the issue
  • The assessment results provide a basis for future steps, such as identifying root causes and needed improvements and data corrections.

Step 4   Assess Business Impact

  • Using a variety of techniques, determine the impact of poor-quality data on the business.
  • This step provides input to establish the business case for improvement, to gain support for information quality, and to determine appropriate investments in your information resource

Step 5   Identify Root Causes

  • Identify and prioritize the true causes of the data quality problems.
  • Develop specific recommendations for addressing the problems.

Step 6   Develop Improvement Plans

  • Finalize specific recommendations for action.
  • Develop improvement plans based on the recommendations.
  • Establish ownership for implementation.

Step 7   Prevent Future Data Errors

  • Implement solutions that address the root causes of the data quality problems.

Step 8   Correct Current Data Errors

  • Implement steps to make appropriate data corrections.

Step 9   Implement Controls

  • Monitor and verify the improvements that were implemented
  • Maintain improved results by standardizing, documenting, and monitoring appropriate improvements

Step 10   Communicate Actions and Results

  • Document and communicate the outcome of quality tests, improvements made, and results of those improvements.
  • Communication is the first step to the many human factors that impact data quality success and are vital to address.  Communication is so important that it is part of every step.

Special Features

Executing Data Quality Projects Along with the seminar materials, delegates will receive a copy of the book “Executing Data Quality Projects:  Ten Steps to Quality Data and Trusted Information™” by Danette McGilvray.  This is an excellent reference for future projects and situations encountered.   

Audience
Individual contributors and team members responsible for or interested in the quality of data in their business processes, systems, or databases, in roles such as:

  • Data analysts
  • Data quality analysts
  • Business analysts
  • Data designers/modelers
  • Data stewards (business and technical)
  • Application developers

This class has also proven helpful for:

  • Managers of the individual contributors
  • Project managers and leads of the team members listed above

These leaders need to understand what is involved in data quality as they are the ones who hire those responsible for the work, prioritize budgets and people’s time, and remove roadblocks to data quality work.

Speaker Biography

Danette McGilvray

Danette McGilvray is president and principal of Granite Falls Consulting, Inc., a firm that helps organizations increase their success by addressing the information quality and data governance aspects of their business efforts. Focusing on bottom-line results, Danette helps organizations enhance the value of their information assets by incorporating information quality management into the business. She also emphasizes communication and the human aspect of data quality and governance.

Danette is the author of Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information (Morgan Kaufmann, 2008).  An internationally respected expert, her Ten Steps™ approach to information quality has been embraced as a proven method for creating, improving, and managing information and data quality in the enterprise. Her trademarked approach, in which she has trained Fortune 500 clients and thousands of workshop attendees, applies to all types of data and all organizations. Her book is used as a textbook in university graduate programs.  The Chinese translation was the first data quality book available in Chinese.

Danette helps clients solve specific data quality problems through data quality projects or incorporating data quality activities into other projects or methodologies.  In addition to projects, Danette helps companies set up data quality and governance programs - formal on-going initiatives that address business needs by providing a foundation and services to sustain data quality.  Her approach is outlined in her chapter on Data Quality Projects and Programs, in: S. Sadiq (ed.), Handbook of Data Quality  Research and Practice (Springer-Verlag Berlin Heidelberg, 2013).

Danette is an invited speaker at conferences around the world and received IAIDQ's Distinguished Member Award in recognition of her outstanding contributions to the field of information and data quality.

Seminar Fee
£1,145 + VAT (£229) = £1,374

Register On-line:
4-5 December 2014, London

2-3 June 2015, London

Group Booking Discount

  • 2-3 Delegates - 10%
  • 4-5 Delegates - 20%
  • 6+ Delegates - 25%

Multiple Seminar Booking Discount

Attend more than one of our seminars and you will be entitled to the following discounts:

  • 2nd course 10%
  • 3rd course 15%
  • 4th course 20%
  • 5th+ course 25%

Please note, only one discount can be applied at any one time.

Hotel Venue
4-5 December 2014
VENUE:  etc.venues Paddington
57 North Wharf Rd
Paddington Basin, London, W2 1LA
Sales: 020 7989 0590
Switchboard: 020 7989 0590
Email: paddington@etcvenues.co.uk
http://www.etcvenues.co.uk/venues/paddington

2-3 June 2015
VENUE:  etc.venues Paddington
57 North Wharf Rd
Paddington Basin, London, W2 1LA
Sales: 020 7989 0590
Switchboard: 020 7989 0590
Email: paddington@etcvenues.co.uk
http://www.etcvenues.co.uk/venues/paddington

In-House Training
If you require a quote for running this course in-house, please contact us with the following details:

  • Subject matter and/or speaker required
  • Estimated number of delegates
  • Location (town, country)
  • Number of days required (if different from the public course)
  • Preferred date

Please contact:
Jeanette Hall
E-mail: jeanette.hall@irmuk.co.uk
Telephone: +44 (0)20 8866 8366
Fax: +44 (0) 2036 277202

Speaker: Danette McGilvray
Danette McGilvray


Data Management Series
Business Intelligence, Big Data, and Data Warehousing: New Technologies and Developments Explained
 
Data Modelling Fundamentals
 
Data Modelling Masterclass
 
Defining and Executing Your Information Strategy
 
Ten Steps to Data Quality

Multiple Seminar Booking Discount
Attend more than one of our seminars and you will be entitled to the following discounts:

  • 2nd course 10%
  • 3rd course 15%
  • 4th course 20%
  • 5th+ course 25%

Group Booking Discount

  • 2-3 Delegates - 10%
  • 4-5 Delegates - 20%
  • 6+ Delegates - 25%

We regret that this offer cannot be used in conjunction with the Multiple Seminar Discount or any other discount.

IRM UK Conferences

Enterprise Data and BI Conference Europe 2014
3-5 November 2014, London

2 co-located conferences
MDM Summit Europe 2015
Data Governance Conference Europe 2015
18-21 May 2015, London

2 co-located conferences
Enterprise Architecture Conference Europe 2015
BPM Conference Europe 2015
15-18 June 2015, London

Business Analysis Conference Europe 2015
21-23 September 2015, London

Click here to purchase past conference documentation.