Total Information Risk Management

OCDQ Radio is an audio podcast about data quality and its related disciplines, produced and hosted by Jim Harris.

During this episode, I am joined by special guest Dr. Alexander Borek, the inventor of Total Information Risk Management (TIRM) and the leading expert on how to apply risk management principles to data management.  Dr. Borek is a frequent speaker at international information management conferences and author of many research articles covering a range of topics, including EIM, data quality, crowd sourcing, and IT business value.  In his current role at IBM, Dr. Borek applies data analytics to drive IBM’s worldwide corporate strategy.  Previously, he led a team at the University of Cambridge to develop the TIRM process and test it in a number of different industries.  He holds a PhD in engineering from the University of Cambridge.

This podcast discusses his book Total Information Risk Management: Maximizing the Value of Data and Information Assets, which is now available world-wide and is a must read for all data and information managers who want to understand and measure the implications of low quality data and information assets.  The book provides step by step instructions, along with illustrative examples from studies in many different industries, on how to implement total information risk management, which will help your organization:

  • Learn how to manage data and information for business value.
  • Create powerful and convincing business cases for all your data and information management, data governance, big data, data warehousing, business intelligence, and business analytics initiatives, projects, and programs.
  • Protect your organization from risks that arise through poor data and information assets.
  • Quantify the impact of having poor data and information.

 

Additional Listening Options:

 

Popular OCDQ Radio Episodes

Clicking on the link will take you to the episode’s blog post:

  • Demystifying Data Science — Guest Melinda Thielbar, a Ph.D. Statistician, discusses what a data scientist does and provides a straightforward explanation of key concepts such as signal-to-noise ratio, uncertainty, and correlation.
  • Data Quality and Big Data — Guest Tom Redman (aka the “Data Doc”) discusses Data Quality and Big Data, including if data quality matters less in larger data sets, and if statistical outliers represent business insights or data quality issues.
  • Demystifying Master Data Management — Guest John Owens explains the three types of data (Transaction, Domain, Master), the four master data entities (Party, Product, Location, Asset), and the Party-Role Relationship, which is where we find many of the terms commonly used to describe the Party master data entity (e.g., Customer, Supplier, Employee).
  • Data Governance Star Wars — Special Guests Rob Karel and Gwen Thomas joined this extended, and Star Wars themed, discussion about how to balance bureaucracy and business agility during the execution of data governance programs.
  • The Johari Window of Data Quality — Guest Martin Doyle discusses helping people better understand their data and assess its business impacts, not just the negative impacts of bad data quality, but also the positive impacts of good data quality.
  • Data Profiling Early and Often — Guest James Standen discusses data profiling concepts and practices, and how bad data is often misunderstood and can be coaxed away from the dark side if you know how to approach it.
  • Studying Data Quality — Guest Gordon Hamilton discusses the key concepts from recommended data quality books, including those which he has implemented in his career as a data quality practitioner.

Measuring Data Quality for Ongoing Improvement

OCDQ Radio is an audio podcast about data quality and its related disciplines, produced and hosted by Jim Harris.

Listen to Laura Sebastian-Coleman, author of the book Measuring Data Quality for Ongoing Improvement: A Data Quality Assessment Framework, and I discuss bringing together a better understanding of what is represented in data, and how it is represented, with the expectations for use in order to improve the overall quality of data.  Our discussion also includes avoiding two common mistakes made when starting a data quality project, and defining five dimensions of data quality.

Laura Sebastian-Coleman has worked on data quality in large health care data warehouses since 2003.  She has implemented data quality metrics and reporting, launched and facilitated a data quality community, contributed to data consumer training programs, and has led efforts to establish data standards and to manage metadata.  In 2009, she led a group of analysts in developing the original Data Quality Assessment Framework (DQAF), which is the basis for her book.

Laura Sebastian-Coleman has delivered papers at MIT’s Information Quality Conferences and at conferences sponsored by the International Association for Information and Data Quality (IAIDQ) and the Data Governance Organization (DGO).  She holds IQCP (Information Quality Certified Professional) designation from IAIDQ, a Certificate in Information Quality from MIT, a B.A. in English and History from Franklin & Marshall College, and a Ph.D. in English Literature from the University of Rochester.

 

Additional Listening Options:

 

Popular OCDQ Radio Episodes

Clicking on the link will take you to the episode’s blog post:

  • Demystifying Data Science — Guest Melinda Thielbar, a Ph.D. Statistician, discusses what a data scientist does and provides a straightforward explanation of key concepts such as signal-to-noise ratio, uncertainty, and correlation.
  • Data Quality and Big Data — Guest Tom Redman (aka the “Data Doc”) discusses Data Quality and Big Data, including if data quality matters less in larger data sets, and if statistical outliers represent business insights or data quality issues.
  • Demystifying Master Data Management — Guest John Owens explains the three types of data (Transaction, Domain, Master), the four master data entities (Party, Product, Location, Asset), and the Party-Role Relationship, which is where we find many of the terms commonly used to describe the Party master data entity (e.g., Customer, Supplier, Employee).
  • Data Governance Star Wars — Special Guests Rob Karel and Gwen Thomas joined this extended, and Star Wars themed, discussion about how to balance bureaucracy and business agility during the execution of data governance programs.
  • The Johari Window of Data Quality — Guest Martin Doyle discusses helping people better understand their data and assess its business impacts, not just the negative impacts of bad data quality, but also the positive impacts of good data quality.
  • Data Profiling Early and Often — Guest James Standen discusses data profiling concepts and practices, and how bad data is often misunderstood and can be coaxed away from the dark side if you know how to approach it.
  • Studying Data Quality — Guest Gordon Hamilton discusses the key concepts from recommended data quality books, including those which he has implemented in his career as a data quality practitioner.

Too Big to Ignore

OCDQ Radio is an audio podcast about data quality and its related disciplines, produced and hosted by Jim Harris.

During this episode, Phil Simon shares his sage advice for getting started with big data, including the importance of having a data-oriented mindset, that ambitious long-term goals should give way to more reasonable and attainable short-term objectives, and always remembering that big data is just another means toward solving business problems.

Phil Simon is a sought-after speaker and the author of five management books, most recently Too Big to Ignore: The Business Case for Big Data.  A recognized technology expert, he consults companies on how to optimize their use of technology.  His contributions have been featured on NBC, CNBC, ABC News, Inc. magazine, BusinessWeek, Huffington Post, Globe and Mail, Fast Company, Forbes, the New York Times, ReadWriteWeb, and many other sites.

 

Additional Listening Options:

 

Popular OCDQ Radio Episodes

Clicking on the link will take you to the episode’s blog post:

  • Demystifying Data Science — Guest Melinda Thielbar, a Ph.D. Statistician, discusses what a data scientist does and provides a straightforward explanation of key concepts such as signal-to-noise ratio, uncertainty, and correlation.
  • Data Quality and Big Data — Guest Tom Redman (aka the “Data Doc”) discusses Data Quality and Big Data, including if data quality matters less in larger data sets, and if statistical outliers represent business insights or data quality issues.
  • Demystifying Master Data Management — Guest John Owens explains the three types of data (Transaction, Domain, Master), the four master data entities (Party, Product, Location, Asset), and the Party-Role Relationship, which is where we find many of the terms commonly used to describe the Party master data entity (e.g., Customer, Supplier, Employee).
  • Data Governance Star Wars — Special Guests Rob Karel and Gwen Thomas joined this extended, and Star Wars themed, discussion about how to balance bureaucracy and business agility during the execution of data governance programs.
  • The Johari Window of Data Quality — Guest Martin Doyle discusses helping people better understand their data and assess its business impacts, not just the negative impacts of bad data quality, but also the positive impacts of good data quality.
  • Data Profiling Early and Often — Guest James Standen discusses data profiling concepts and practices, and how bad data is often misunderstood and can be coaxed away from the dark side if you know how to approach it.
  • Studying Data Quality — Guest Gordon Hamilton discusses the key concepts from recommended data quality books, including those which he has implemented in his career as a data quality practitioner.

Doing Data Governance

OCDQ Radio is an audio podcast about data quality and its related disciplines, produced and hosted by Jim Harris.

During this episode, I discuss the practical aspects of doing data governance with John Ladley, the author of the excellent book Data Governance: How to Design, Deploy and Sustain an Effective Data Governance Program.  Our discussion includes understanding the difference and relationship between data governance and information management, the importance of establishing principles before creating policies, data stewardship, and three critical success factors for data governance.

John Ladley is a business technology thought leader with 30 years of experience in improving organizations through the successful implementation of information systems.  He is a recognized authority in the use and implementation of business intelligence and enterprise information management (EIM).

John Ladley is the author of Making EIM Work for Business, and frequently writes and speaks on a variety of technology and enterprise information management topics.  His information management experience is balanced between strategic technology planning, project management, and, most important, the practical application of technology to business problems.

 

Additional Listening Options:

 

Popular OCDQ Radio Episodes

Clicking on the link will take you to the episode’s blog post:

  • Demystifying Data Science — Guest Melinda Thielbar, a Ph.D. Statistician, discusses what a data scientist does and provides a straightforward explanation of key concepts such as signal-to-noise ratio, uncertainty, and correlation.
  • Data Quality and Big Data — Guest Tom Redman (aka the “Data Doc”) discusses Data Quality and Big Data, including if data quality matters less in larger data sets, and if statistical outliers represent business insights or data quality issues.
  • Demystifying Master Data Management — Guest John Owens explains the three types of data (Transaction, Domain, Master), the four master data entities (Party, Product, Location, Asset), and the Party-Role Relationship, which is where we find many of the terms commonly used to describe the Party master data entity (e.g., Customer, Supplier, Employee).
  • Data Governance Star Wars — Special Guests Rob Karel and Gwen Thomas joined this extended, and Star Wars themed, discussion about how to balance bureaucracy and business agility during the execution of data governance programs.
  • The Johari Window of Data Quality — Guest Martin Doyle discusses helping people better understand their data and assess its business impacts, not just the negative impacts of bad data quality, but also the positive impacts of good data quality.
  • Data Profiling Early and Often — Guest James Standen discusses data profiling concepts and practices, and how bad data is often misunderstood and can be coaxed away from the dark side if you know how to approach it.
  • Studying Data Quality — Guest Gordon Hamilton discusses the key concepts from recommended data quality books, including those which he has implemented in his career as a data quality practitioner.

Demystifying Data Science

OCDQ Radio is a vendor-neutral podcast about data quality and its related disciplines, produced and hosted by Jim Harris.

During this episode, special guest, and actual data scientist, Dr. Melinda Thielbar, a Ph.D. Statistician, and I attempt to demystify data science by explaining what a data scientist does, including the requisite skills involved, bridging the communication gap between data scientists and business leaders, delivering data products business users can use on their own, and providing a straightforward explanation of key concepts such as signal-to-noise ratio, uncertainty, experimentation, and correlation.

Melinda Thielbar is the Senior Mathematician for IAVO Research and Scientific.  Her work there focuses on power system optimization using real-time prediction models.  She has worked as a software developer, an analytic lead for big data implementations, and a statistics and programming teacher.

Melinda Thielbar is a co-founder of Research Triangle Analysts, a professional group for analysts and data scientists located in the Research Triangle of North Carolina.

While Melinda Thielbar doesn’t specialize in a single field, she is particularly interested in power systems because, as she puts it, “A power systems optimizer has to work every time.”

 

Demystifying Data Science

Additional listening options:

 

Related OCDQ Radio Episodes

Clicking on the link will take you to the episode’s blog post:

  • Data Quality and Big Data — Guest Tom Redman (aka the “Data Doc”) discusses Data Quality and Big Data, including if data quality matters less in larger data sets, and if statistical outliers represent business insights or data quality issues.

 

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Open Source Business Intelligence

OCDQ Radio is a vendor-neutral podcast about data quality and its related disciplines, produced and hosted by Jim Harris.

During this episode, I discuss open source business intelligence (OSBI) with Lyndsay Wise, author of the insightful new book Using Open Source Platforms for Business Intelligence: Avoid Pitfalls and Maximize ROI.

Lyndsay Wise is the President and Founder of WiseAnalytics, an independent analyst firm and consultancy specializing in business intelligence for small and mid-sized organizations.  For more than ten years, Lyndsay Wise has assisted clients in business systems analysis, software selection, and implementation of enterprise applications.

Lyndsay Wise conducts regular research studies, consults, writes articles, and speaks about how to implement a successful business intelligence approach and improving the value of business intelligence within organizations.

 

Open Source Business Intelligence

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Win a copy of the Book

Lyndsay Wise wants to give one OCDQ Radio listener a free copy of Using Open Source Platforms for Business Intelligence.

 

Here is how the book contest will work:

(1) Book Contest Question — Name one of the considerations for evaluating whether OSBI is the right choice for your organization that Lyndsay Wise discussed during this OCDQ Radio episode.

 

(2) Book Contest Deadline — By or before January 31, 2013, Email Jim Harris with your answer to the book contest question.

 

(3) Book Contest Winner — In February 2013, one winner will be randomly selected from the emails containing the answer to the contest question, and Lyndsay Wise will email the winner requesting a postal address for sending a free copy of the book.

 

Related Lyndsay Wise Articles

What You Need to Know about Open Source BI

Open Source BI Considerations and Implications

Do Self-Service and Open Source Co-Exist?

Everything Executives Need to Know about Open Source BI

The Importance of Data Management for Business People

 

Related OCDQ Radio Episodes

Clicking on the link will take you to the episode’s blog post:

  • Studying Data Quality — Guest Gordon Hamilton discusses the key concepts from recommended data quality books, including those which he has implemented in his career as a data quality practitioner.

The Evolution of Enterprise Security

This podcast episode is sponsored by the Enterprise CIO Forum and HP.

OCDQ Radio is a vendor-neutral podcast about data quality and its related disciplines, produced and hosted by Jim Harris.

During this episode, Bill Laberis and I discuss the necessary evolution of enterprise security in the era of cloud computing and mobile devices.  Our discussion includes public, private, and hybrid clouds, leveraging existing security best practices, defining BYOD (Bring Your Own Device) policies, mobile device management, and striking a balance between convenience and security.

Bill Laberis is the Editorial Director of the Enterprise CIO Forum, in which capacity he oversees the content of both its US and international websites.  He is also Editorial Director and Social Media Manager in the IDG Custom Solutions Group, working closely with clients to create highly individualized custom content programs that leverage the wide range of media capabilities, including print, online, multimedia, and custom events.

Bill Laberis was editor-in-chief of Computerworld from 1986-1996, has been a frequent speaker and keynoter, and has written for various business publications including The Wall Street Journal.  He has been closely following the IT sector for 30 years.

 

The Evolution of Enterprise Security

Additional listening options:

This podcast episode is sponsored by the Enterprise CIO Forum and HP.

 

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Cloud Computing for Midsize Businesses

OCDQ Radio is a vendor-neutral podcast about data quality and its related disciplines, produced and hosted by Jim Harris.

During this episode, Ed Abrams and I discuss cloud computing for midsize businesses, and, more specifically, we discuss aspects of the recently launched IBM global initiatives to help Managed Service Providers (MSP) deliver cloud-based service offerings.

Ed Abrams is the Vice President of Marketing, IBM Midmarket.  In this role, Ed is responsible for leading a diverse team that supports IBM’s business objectives with small and midsize businesses by developing, planning, and executing offerings and go-to-market strategies designed to help midsize businesses grow.  In this role Ed works closely and collaboratively with sales and channels teams, and agency partners to deliver high-quality and effective marketing strategies, offerings, and campaigns.

 

Cloud Computing for Midsize Businesses

Additional listening options:

 

This podcast was sponsored by the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet.

 

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The Partly Cloudy CIO

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Sometimes all you Need is a Hammer

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Social Media for Midsize Businesses

OCDQ Radio is a vendor-neutral podcast about data quality and its related disciplines, produced and hosted by Jim Harris.

During this episode, Paul Gillin and I discuss social media for midsize businesses, including how the less marketing you do, the more effective you will be with social media marketing, the war of generosity, where the more you give, the more you get, and the importance of the trust equation, which means the more people trust you, the more they will want to do business with you.

Paul Gillin is a veteran technology journalist and a thought leader in new media.  Since 2005, he has advised marketers and business executives on strategies to optimize their use of social media and online channels to reach buyers cost-effectively.  He is a popular speaker who is known for his ability to simplify complex concepts using plain talk, anecdotes, and humor.

Paul Gillin is the author of four books about social marketing: The New Influencers (2007), Secrets of Social Media Marketing (2008), Social Marketing to the Business Customer (2011), co-authored with Eric Schwartzman, and the forthcoming book Attack of the Customers (2012), co-authored with Greg Gianforte.

Paul Gillin was previously the founding editor of TechTarget and editor-in-chief of Computerworld.  He writes a monthly column for BtoB magazine and is an active blogger and media commentator.  He has appeared as an expert commentator on CNN, PBS, Fox News, MSNBC, and other television outlets.  He has also been quoted or interviewed for hundreds of news and radio reports in outlets such as The Wall Street Journal, The New York Times, NPR, and the BBC.  Paul Gillin is a Senior Research Fellow and member of the board of directors at the Society for New Communications Research.

 

Social Media for Midsize Businesses

Additional listening options:

 

This podcast was sponsored by the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet.

 

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