It is clear to me from the statistics on the number of unique visitors that there are a lot of you who find the details of matching as interesting as I do. For those of you waiting patiently for my next matching algorithm post fear not, I've not abandoned the series. I've been delayed by other assignments and some interesting new projects. I apologize for the delay to those of you who are eager to read more about the matching algorithms available in Informatica's Data Quality Workbench. I hate to disappoint you and promise to pick the series back up shortly.
In the meantime, I thought I'd write-up a quick post about one of my most valuable data quality tools; my data quality network!
The Light Bulb Moment!
The idea for this post occurred to me this week during the Informatica Analyst Conference. I wasn't there but I was able, with the help of several attendees, to keep up-to-date on what was going on in the room through their Twitter updates, or tweets. This type of information exchange, in my opinion, is what the internet is all about!
There must have been half-dozen tweets that sparked my interest and I intend on pursuing these in the coming months. In the spirit of the exchange, I'll pass what I learn on to those of you who follow my blog and Twitter account.
Among the tools I use to build my data quality network are Twitter, LinkedIn, The International Association for Information and Data Quality and the blogs of those I follow on Twitter and LinkedIn. I hope this "directory" of resources is useful to you in your pursuit of data quality knowledge.
Twitter Resources
I'm starting with Twitter because it is my favorite resource for new information. In a way, it serves as a directory of fresh content. Typically Twitter users, or Tweeters, include a little summary of their content so you can make a quick decision on whether you want to investigate the material further. In this way, Twitter is an efficient use of time. An inherent feature of Twitter is that tweeters "push" content to you. This is particularly useful in the discovery of new information and learning. It does help to follow those "in-the-know". For instance, I had no idea there was an Informatica Analyst Conference yesterday until I read some tweets from @bitterer, @NeilRaden, @merv, @rbkarel and @jilldyche. Between them, I was so up-to-date I almost went to the next room expecting to see chocolate cake and wine during intermission!
It was this event that inspired me to share with you some of the interesting people that I follow on Twitter that have expanded my knowledge of data quality, master data management, identity resolution, data matching and information technology consulting over the past year.
- @jilldyche -- Follow Jill of @BaselineConsult for all things data quality & MDM with a fresh twist at http://www.jilldyche.com/
- @ocdqblog -- Follow Jim for data quality insight from the theoretical to the practical, you'll find it on his blog here http://www.ocdqblog.com/
- @hlsdk -- Follow Henrik for data matching perspectives that are right on target. You can learn how to hit the mark with his blog http://liliendahl.wordpress.com/
- @KenOConnorData -- Follow Ken for great info on data quality such as anti-money laundering & MDM insight at http://kenoconnordata.wordpress.com/
- @stevesarsfield -- Follow Steve for expert insight into MDM & data governance at http://data-governance.blogspot.com/
- @philsimon -- Follow Phil for updates from the intersection of business & technology at http://www.philsimonsystems.com/
- @daraghobrien -- Follow Daragh for content on information quality and its application to business at http://obriend.info/
I follow over 150 Tweeters so it was not practical to get them all included this first go around. I'll continue to update this list and send out notice via Twitter when I do.
LinkedIn Resources
Another one of my data quality resources is LinkedIn. I use LinkedIn groups to join discussions on data quality topics and exchange ideas with other data professionals. LinkedIn is a little different from Twitter in that you go out and find content rather than it being streamed to you. However, you can set up your group membership to email you of updates to discussions you've participated in making it somewhat proactive.
Here is a quick list of some of the data quality groups I belong to that have proven to be quite useful in the past year:
- CDI-MDM (Customer Data Integration & Master Data Management)
- Data Cleansing User Group
- Data Matching
- Data Quality Pro.com
- IAIDQ Information/Data Quality Professional Open Community
I belong to fifty LinkedIn groups, so these five are by no means a comprehensive list. I wanted to start with those that are geared specifically toward data quality.
Professional Association
I received great advice many years ago from a senior member of a consulting firm where I worked. To paraphrase it went something like this, "If you want to learn more about your chosen profession, join an association in your area of desired expertise." I don't know that I have ever received better advice? Joining an association in your chosen area of study is a great idea for professionals and students alike. It leads you down paths to which you may have never otherwise been exposed.
In keeping with that advice, I highly recommend that those of you interested in the data quality become a member of The International Association for Information and Data Quality, or IAIDQ. At IAIDQ's website you will find great information on events in the industry, as well as services and products regarding various aspects of information quality. Some of the foremost experts in the information quality industry contribute content to IAIDQ's website.
Trunk of the Tree
This post by no means contains every element of my learning network, but it is certainly the core. It is my intention to better organize this content and give it a permanent place as a stand-alone page on my blog.
My sincere apologies to those valuable resources that I may have inadvertently omitted. In time, I hope to post a link in this directory to all who've helped me on my learning journey.
I hope this post helped someone find a new resource, convinced someone else to start building their network or maybe even helped others realize that while software tools are useful, it is the spirit of collaboration that is most valuable!
[...] most valuable data quality tool is my data quality network! – Preface It is clear to… http://thedataqualitychronicle.org/… #dataquality 6 seconds [...]
ReplyDeleteGreat point William, this really resonates with me too. Books and courses are important but having the right people around you are vital to career growth.
ReplyDeleteSocial media is not a fad, it's just another way to network, we've been doing it since we came out of the trees and it's critical for careers in things like data quality, MDM and data governance which are still fairly niche in most regions.