Open Source Business Intelligence

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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.

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

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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.

Cloud Computing for Midsize Businesses

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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.

Social Media for Midsize Businesses

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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.

Demystifying Master Data Management

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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 John Owens and I attempt to demystify master data management (MDM) by explaining the three types of data (Transaction, Domain, Master) and the four master data entities (Party, Product, Location, Asset), as well as, and perhaps the most important concept of all, 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).

John Owens is a thought leader, consultant, mentor, and writer in the worlds of business and data modelling, data quality, and master data management (MDM).  He has built an international reputation as a highly innovative specialist in these areas and has worked in and led multi-million dollar projects in a wide range of industries around the world.

John Owens has a gift for identifying the underlying simplicity in any enterprise, even when shrouded in complexity, and bringing it to the surface.  He is the creator of the Integrated Modelling Method (IMM), which is used by business and data analysts around the world.  Later this year, John Owens will be formally launching the IMM Academy, which will provide high quality resources, training, and mentoring for business and data analysts at all levels.

You can also follow John Owens on Twitter and connect with John Owens on Linkedin.  And if you’re looking for a MDM course, consider the online course from John Owens, which you can find by clicking on this link: MDM Online Course (Affiliate Link)

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.
  • 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.
  • 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.

Saving Private Data

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

This episode is an edited rebroadcast of a segment from the OCDQ Radio 2011 Year in Review, during which Daragh O Brien and I discuss the data privacy and data protection implications of social media, cloud computing, and big data.

Daragh O Brien is one of Ireland’s leading Information Quality and Governance practitioners.  After being born at a young age, Daragh has amassed a wealth of experience in quality information driven business change, from CRM Single View of Customer to Regulatory Compliance, to Governance and the taming of information assets to benefit the bottom line, manage risk, and ensure customer satisfaction.  Daragh O Brien is the Managing Director of Castlebridge Associates, one of Ireland’s leading consulting and training companies in the information quality and information governance space.

Daragh O Brien is a founding member and former Director of Publicity for the IAIDQ, which he is still actively involved with.  He was a member of the team that helped develop the Information Quality Certified Professional (IQCP) certification and he recently became the first person in Ireland to achieve this prestigious certification.

In 2008, Daragh O Brien was awarded a Fellowship of the Irish Computer Society for his work in developing and promoting standards of professionalism in Information Management and Governance.

Daragh O Brien is a regular conference presenter, trainer, blogger, and author with two industry reports published by Ark Group, the most recent of which is The Data Strategy and Governance Toolkit.

You can also follow Daragh O Brien on Twitter and connect with Daragh O Brien on LinkedIn.

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.

  • 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.

  • Social Media Strategy — Guest Crysta Anderson of IBM Initiate explains social media strategy and content marketing, including three recommended practices: (1) Listen intently, (2) Communicate succinctly, and (3) Have fun.

  • The Fall Back Recap Show — A look back at the Best of OCDQ Radio, including discussions about Data, Information, Business-IT Collaboration, Change Management, Big Analytics, Data Governance, and the Data Revolution.

Solvency II and Data Quality

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

During this episode, Ken O’Connor and I discuss the Solvency II standards for data quality, and how its European insurance regulatory requirement of “complete, appropriate, and accurate” data represents common sense standards for all businesses.

Ken O’Connor is an independent data consultant with over 30 years of hands-on experience in the field, specializing in helping organizations meet the data quality management challenges presented by data-intensive programs such as data conversions, data migrations, data population, and regulatory compliance such as Solvency II, Basel II / III, Anti-Money Laundering, the Foreign Account Tax Compliance Act (FATCA), and the Dodd–Frank Wall Street Reform and Consumer Protection Act.

Ken O’Connor also provides practical data quality and data governance advice on his popular blog at: kenoconnordata.com

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.
  • 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 Data Governance Imperative

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

During this episode, Steve Sarsfield and I discuss how data governance is about changing the hearts and minds of your company to see the value of data quality, the characteristics of a data champion, and creating effective data quality scorecards.

Steve Sarsfield is a leading author and expert in data quality and data governance.  His book The Data Governance Imperative is a comprehensive exploration of data governance focusing on the business perspectives that are important to data champions, front-office employees, and executives.  He runs the Data Governance and Data Quality Insider, which is an award-winning and world-recognized blog.  Steve Sarsfield is the Product Marketing Manager for Data Governance and Data Quality at Talend.

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.
  • 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.

Data Quality and Big Data

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

This is Part 2 of 2 from my recent discussion with Tom Redman.  In this episode, Tom and I discuss data quality and big data, including if data quality matters less in larger data sets, if statistical outliers represent business insights or data quality issues, statistical sampling errors versus measurement calibration errors, mistaking signal for noise (i.e., good data for bad data), and whether or not the principles and practices of true “data scientists” will truly be embraced by an organization’s business leaders.

Dr. Thomas C. Redman (the “Data Doc”) is an innovator, advisor, and teacher.  He was first to extend quality principles to data and information in the late 80s.  Since then he has crystallized a body of tools, techniques, roadmaps and organizational insights that help organizations make order-of-magnitude improvements.

More recently Tom has developed keen insights into the nature of data and formulated the first comprehensive approach to “putting data to work.”  Taken together, these enable organizations to treat data as assets of virtually unlimited potential.

Tom has personally helped dozens of leaders and organizations better understand data and data quality and start their data programs.  He is a sought-after lecturer and the author of dozens of papers and four books.  The most recent, Data Driven: Profiting from Your Most Important Business Asset (Harvard Business Press, 2008) was a Library Journal best buy of 2008.

Prior to forming Navesink Consulting Group in 1996, Tom conceived the Data Quality Lab at AT&T Bell Laboratories in 1987 and led it until 1995.  Tom holds a Ph.D. in statistics from Florida State University. He holds two patents.

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.
  • 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.
  • 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.

Data Driven

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

This is Part 1 of 2 from my recent discussion with Tom Redman.  In this episode, Tom and I discuss concepts from one of my favorite data quality books, which is his most recent book: Data Driven: Profiting from Your Most Important Business Asset.

Our discussion includes viewing data as an asset, an organization’s hierarchy of data needs, a simple model for culture change, and attempting to achieve the “single version of the truth” being marketed as a goal of master data management (MDM).

Dr. Thomas C. Redman (the “Data Doc”) is an innovator, advisor, and teacher.  He was first to extend quality principles to data and information in the late 80s.  Since then he has crystallized a body of tools, techniques, roadmaps and organizational insights that help organizations make order-of-magnitude improvements.

More recently Tom has developed keen insights into the nature of data and formulated the first comprehensive approach to “putting data to work.”  Taken together, these enable organizations to treat data as assets of virtually unlimited potential.

Tom has personally helped dozens of leaders and organizations better understand data and data quality and start their data programs.  He is a sought-after lecturer and the author of dozens of papers and four books.

Prior to forming Navesink Consulting Group in 1996, Tom conceived the Data Quality Lab at AT&T Bell Laboratories in 1987 and led it until 1995. Tom holds a Ph.D. in statistics from Florida State University.  He holds two patents.

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.
  • 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.

Decision Management Systems

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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 decision management with James Taylor, author of the new book Decision Management Systems: A Practical Guide to Using Business Rules and Predictive Analytics.

James Taylor is the CEO of Decision Management Solutions, and the leading expert in Decision Management Systems, which are active participants in improving business results by applying business rules, predictive analytics, and optimization technologies to address the toughest issues facing businesses today, and changing the way organizations are doing business.

James Taylor has led Decision Management efforts for leading companies in insurance, banking, health management, and telecommunications.  Decision Management Solutions works with clients to improve their business by applying analytics and business rules technology to automate and improve decisions.  Clients range from start-ups and software companies to major North American insurers, a travel company, the health management division of a major healthcare company, one of Europe’s largest banks, and several major decision management technology vendors.

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.
  • 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 Johari Window of Data Quality

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

The Johari Window is a term from psychology for a technique used to help people better understand their personality and behavior by combining a self assessment with assessments from their peers.  In relation to data, the Johari Window is a metaphor for 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.

During this episode, I discuss the Johari Window of Data Quality with Martin Doyle.  Our discussion, inspired by our blog comment banter on my post There is No Such Thing as a Root Cause, includes root cause analysis, the pursuit of data perfection, metadata, communication, Business-IT collaboration, change management, defect prevention, and continuous improvement.

Martin Doyle is a Data Quality Improvement Evangelist and the CEO of DQ Global, which is a UK-based data quality software and services vendor providing data cleansing, international address and email verification, data deduplication, and data matching solutions for Customer Relationship Management, Single Customer View, and Master Data Management.  DQ Global has worked with over 500 businesses worldwide on a variety of projects, providing their clients with improved data quality, making their data fit for business use, and enabling them to trust their data and make decisions based on a foundation of fact.

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.
  • 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.

Scary Calendar Effects

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

During this episode, recorded on the first of three occurrences of Friday the 13th in 2012, I discuss scary calendar effects.

In other words, I discuss how schedules, deadlines, and other date-related aspects can negatively affect enterprise initiatives such as data quality, master data management, and data governance.

Please Beware: This episode concludes with the OCDQ Radio Theater production of Data Quality and Friday the 13th.

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.
  • 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.

So Long 2011, and Thanks for All the . . .

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

Don’t Panic!  Welcome to the mostly harmless OCDQ Radio 2011 Year in Review episode.  During this approximately 42 minute episode, I recap the data-related highlights of 2011 in a series of sometimes serious, sometimes funny, segments, as well as make wacky and wildly inaccurate data-related predictions about 2012.

Special thanks to my guests Jarrett Goldfedder, who discusses Big Data, Nicola Askham, who discusses Data Governance, and Daragh O Brien, who discusses Data Privacy.  Additional thanks to Rich Murnane and Dylan Jones.  And Deep Thanks to that frood Douglas Adams, who always knew where his towel was, and who wrote The Hitchhiker’s Guide to the Galaxy.

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.
  • 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.

Redefining Data Quality

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

During this episode, I have an occasionally spirited discussion about data quality with Peter Perera, partially precipitated by his provocative post from this past summer, The End of Data Quality...as we know it, which included his proposed redefinition of data quality, as well as his perspective on the relationship of data quality to master data management and data governance.

Peter Perera is a recognized consultant and thought leader with significant experience in Master Data Management, Customer Relationship Management, Data Quality, and Customer Data Integration.  For over 20 years, he has been advising and working with Global 5000 organizations and mid-size enterprises to increase the usability and value of their customer information.

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.
  • 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.