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Jill Dyché

There you are! What took you so long? This is my blog and it's about YOU.

Yes, you. Or at least it's about your company. Or people you work with in your company. Or people at other companies that are a lot like you. Or people at other companies that you'd rather not resemble at all. Or it's about your competitors and what they're doing, and whether you're doing it better. You get the idea. There's a swarm of swamis, shrinks, and gurus out there already, but I'm just a consultant who works with lots of clients, and the dirty little secret - shhh! - is my clients share a lot of the same challenges around data management, data governance, and data integration. Many of their stories are universal, and that's where you come in.

I'm hoping you'll pour a cup of tea (if this were another Web site, it would be a tumbler of single-malt, but never mind), open the blog, read a little bit and go, "Jeez, that sounds just like me." Or not. Either way, welcome on in. It really is all about you.

About the author >

Jill is a partner co-founder of Baseline Consulting, a technology and management consulting firm specializing in data integration and business analytics. Jill is the author of three acclaimed business books, the latest of which is Customer Data Integration: Reaching a Single Version of the Truth, co-authored with Evan Levy. Her blog, Inside the Biz, focuses on the business value of IT.

Editor's Note: More articles and resources are available in Jill's BeyeNETWORK Expert Channel. Be sure to visit today!

By Stephen Putman, Senior Consultant

Stairs_robinfensom
Recently, a friend of mine posted a link on Facebook that reinforced a philosophy that I have had for a long time that applies to all activities in life that are not duty-bound:

The Dreaded Stairs (part of  The Fun Theory project)

I have long felt that humans do things for two reasons:

A) They're fun

B) They're lucrative

This applies to the field of Data Governance and Quality as it does everything else. One of the reasons data governance and quality initiatives are not more widely adopted and followed is that the work is not terribly fun - data owners must be identified, policies and processes must be adopted, and the entire process must be monitored and attended once it is in place. It's also not seen as lucrative in a direct sense - the act of cleansing the data in a transaction usually doesn't provide immediate financial reward, and while the implementation of governance and quality initiatives can affect the company's bottom line, the benefits are very difficult to quantify in a traditional sense.

Phil Simon  has produced a terrific  series  for The Data Roundtable on incentive ideas for data quality programs, so I will not address these here - he says it much better than I can. I am concerned with "fun." The video above demonstrated an innovative idea to make a mundane but healthy activity (climbing stairs) into a joyful experience. What sort of innovative programs can be created to make managing high-quality data fun?

"Fun" is a difficult concept because it means something different to everyone. One way to find out what is "fun" to your employees is by conducting surveys or workshops to ask them directly. Another possibility could be to have a "company carnival" in your parking lot, and award employees who identify quality issues with raffle tickets or a "boss' dunk tank." The White House holds a  yearly contest  with government employees for the best quality improvement or cost-savings idea (this is more of an incentive, but some people also consider contests like this fun).

These are just a few ideas off the top of the head - do you have creative people who can come up with other ideas? If it is indeed true that fun makes unpleasant activities more palatable, this would be time well spent to reinforce data governance and quality in your organization.

photo by Robin Fensom via Flickr (Creative Commons license)


StevePutman_bw_100Stephen Putman has over 20 years experience supporting client/server and internet-based operations from small offices to major corporations.   He has extensive experience in a variety of front-end development tools, as well as relational database design and administration, and is extremely effective in project management and leadership roles. He is the co-author of The Data Governance eBook, available at baseline-consulting.com/ebooks.



Posted February 22, 2011 6:00 AM
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By Stephen Putman, Senior Consultant

Spock-chess
I recently read Rob Gonzalez' blog post  I've Got a Federated Bridge to Sell You (A Defense of the Warehouse)  with great interest - a Semantic Web professional who is defending a technology that could be displaced by semantics! I agree with Mr. Gonzalez that semantically federated databases are not the answer in all business cases. However, traditional data warehouses and data marts are not the best answer in all cases either, and there are also cases where neither technology is the appropriate solution.

The appropriate technological solution for a given business case depends on a great many factors, which I like to call "Three-Dimensional Chess."

An organization needs to consider many factors in choosing the right technology to solve an analytical requirement, including:

  • Efficiency/speed of query return - Is the right data stored or accessed in an efficient manner, and can it be accessed quickly and accurately?  
  • Currency of data - How current is the data that is available?  
  • Flexibility of model - Can the system accept new data inputs of differing structures with a minimum of remodeling and recoding?  
  • Implementation cost, including maintenance - How much does it cost to implement and maintain the system?  
  • Ease of use by end users - Can the data be accessed and manipulated by end users in familiar tools without damage to the underlying data set?  
  • Relative fit to industry and organizational standards - This deals with long-term maintainability of the system, which I addressed in a recent posting –  Making It Fit.
  • Current staff skillsets/scarcity of resources to implement and maintain - Can your staff implement and maintain the system, or alternately, can you find the necessary resources in the market to do so at a reasonable cost?

Fortunately, new tools and methodologies are constantly being developed that can optimize one or more of these factors, but balancing all of these sometimes mutually exclusive factors is a very difficult job. There are very few system architects who are well versed in many of the applicable systems, so architects tend to advocate the types of systems they are familiar with, bending requirements to fit the characteristics of the system. This causes the undesirable tendency that is represented in the saying, "When all you have is a hammer, everything looks like a nail."

Make sure that your organization is taking all factors into account when deciding how to solve an analytical requirement by developing or attracting people who are skilled at playing ”three-dimensional chess.”

  


StevePutman_bw_100Stephen Putman has over 20 years experience supporting client/server and internet-based operations from small offices to major corporations.   He has extensive experience in a variety of front-end development tools, as well as relational database design and administration, and is extremely effective in project management and leadership roles. He is the co-author of The Data Governance eBook, available at baseline-consulting.com/ebooks.



Posted February 16, 2011 6:00 AM
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By Stephen Putman, Senior Consultant

Chainlink_steve_lodefink

I begin today with an invitation to a headache...click this link:  The Linking Open Data Cloud Diagram

Ouch! That is a really complicated diagram. I believe that the  Semantic Web  suffers from the same difficulty that many worthy technologies do - the relative impossibility to describe the concept in simple terms, using concepts familiar to the vast majority of the audience. When this happens, the technology gets buried under well-meaning but hopelessly complex diagrams like this one. If you take the time to understand it, the concept is very powerful, but all the circles and lines immediately turn off most people.

Fortunately, there are simple things that you can do in your organization today that will introduce the concept of  linked data  to your staff and begin to leverage the great power that the concept holds. It will take a little bit of transition, but once the idea takes hold you can take it in several more powerful directions.

Many companies treat their applications as islands unto themselves in their basic operations, regardless of any external feeds or reporting that occurs. One result of this is that basic, seldom-changing concepts such as Country, State, and Date/Time are replicated in each system throughout the company. A basic tenet of data management states that managing data in one place is preferable to managing it in several - every time something changes, it must be maintained in however many systems use it.

One of the basic concepts of linked data is that applications will use a common repository for data like State, for example, and publish  Uniform Resource Identifiers  (URIs), or standardized location values that act much like Web-based URLs, for each value in the repository. Applications will then link to the URI for the lookup value instead of proprietary codes in use today. There are efforts to make global shared repositories for this type of data, but it is not necessary to place your trust in these data stores right away - all of this can occur within your company's firewall.

The transition to linked data does not need to be sudden or comprehensive, but can be accomplished in an incremental fashion to mitigate disruption to existing systems. Here are actions that you can begin right now to start the transition:

  • If you are coding an application that uses these common lookups, store the URI in the parent table instead of the proprietary code.
  • If you are using "shrink wrap" applications, construct views that reconcile the URIs and the proprietary codes, and encourage their use by end users.
  • Investigate usage of common repositories in all future development and packaged software acquisition.
  • Begin investigation of linking company-specific common data concepts, such as department, location, etc.

  Once the transition to a common data store is under way, your organization will have lower administration costs and more consistent data throughout the company. You will also be leading your company into the future of linked data processing that is coming soon.

photo by steve_lodefink via Flickr (Creative Commons License)


StevePutman_bw_100Stephen Putman has over 20 years experience supporting client/server and internet-based operations from small offices to major corporations.   He has extensive experience in a variety of front-end development tools, as well as relational database design and administration, and is extremely effective in project management and leadership roles. He is the co-author of The Data Governance eBook, available at information-management.com.



Posted February 1, 2011 6:00 AM
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By Stephen Putman, Senior Consultant

Netflix_PseudoGil
I just finished reading a post on the Netflix blog - 5 Lessons We've Learned Using Amazon Web Services (AWS). Even though this article is specific to a high-traffic cloud-based technology platform, I think that it holds a great lesson for the optimization of any computer system, and especially a system that relies on outside sources such as a business intelligence system.  

Netflix develops their systems with the attitude that anything can fail at any point in the technology stack, and their systems should respond in as graceful a way as possible. This is a wonderful attitude to have for any system, and their lessons can be applied to a BI system just as easily:

1. You must unlearn what you have learned. Many people who develop and maintain BI systems come from the transactional application world, and apply their experience to a BI system, which is fundamentally different in several ways - for example, the optimization goal of a transactional system is the individual transaction, while the optimization point of a BI system is the retrieval and manipulation of often huge data sets. Managers and developers that do not realize these differences are doomed to failure with their systems, while people who  successfully  make the transition meet organizational goals much more easily.

2. Co-tenancy is hard. The BI system must manage many different types of loads and requests on a daily basis while simultaneously appearing to be as responsive to the user as all other software used. The system administrator must balance data loads, operational reporting requests, and the construction and manipulation of analysis data sets, often at the same time. This is the same sort of paradigm shift as in lesson 1 - people who do not realize the complications of this environment are doomed to failure since the success of a BI system is directly proportional to the frequency of use, and an inefficient system quickly becomes unused.

3. The best way to avoid failure is to fail constantly. This lesson seems counter-intuitive, but I've seen a lot of failed systems that always assumed that things would work perfectly - source feeds would always have valid data, in the same place, at the same time, always - that this philosophy gains more credence daily. Systems should always be tested for outages at any step of the process, and coded so that the response is graceful and as invisible to end-users as possible. If you don't rehearse this in development, you will fail in production - take that to the bank.

4. Learn with real scale, not toy models. It would seem that proper performance testing on systems equivalent to production hardware and networking with full data sets would be self-evident, but many development shops look at this as an unnecessary expense that adds little to the finished product. But, as in lesson 3 above, if you do not rehearse the operation of your system on the same size of system as your production environment, you have no way of knowing how the system will respond in real-world situations, and are effectively gambling with your career. The smart manager avoids this sort of gamble.

5. Commit yourself. This message surfaces in many different discussions, but it should be re-emphasized frequently - a system as important as your enterprise business intelligence system should have strong and unwavering commitment from all levels of your organization to survive the inevitable struggles that occur in the implementation of such a large computer system.

It is sometimes surprising to realize that even though technology continues to become more complex and distributed, the same simple lessons can be learned from every system and applied to new systems. These lessons should be reviewed frequently in your quest to implement successful data processing systems.

photo by PseudoGil via Flickr (Creative Commons License)


StevePutman_bw_100Stephen Putman has over 20 years experience supporting client/server and internet-based operations from small offices to major corporations.   He has extensive experience in a variety of front-end development tools, as well as relational database design and administration, and is extremely effective in project management and leadership roles. He is the co-author of The Data Governance eBook, available at information-management.com.



Posted January 18, 2011 6:00 AM
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By Dick Voorhees, Senior Consultant

Champagne
The New Year is upon us. And for many, the coming of the New Year involves making new resolutions, or reaffirming old ones. This resolution-making process includes corporations and organizations, not just individuals. In terms of personal resolutions, some undertake this process in earnest, but many seem to deal with resolutions superficially, or at least not very effectively. The same is frequently true for organizations as well.

So how then should an organization go about deciding which ”resolutions” to pursue in the New Year, which goals and objectives are both worthy and achievable? Often there are no "good" or "bad" opportunities, a priori, but some are more likely to result in a successful outcome and/or have more significant payoff than others.

  1. Take stock of the opportunities, and develop a list of key potential initiatives (or review the existing list, if one exists). Consider recent or imminent changes in the marketplace, competitors’ actions, and governmental regulations. Which of these initiatives offers the possibility of consolidating/increasing market share, improving customer service, or represents necessary future investment (in the case of regulations)? And which best supports the existing goals and objectives of the organization?
  2. Assess the capabilities and readiness of the organization to act on these initiatives. An opportunity might be a significant one, but if the organization can’t respond effectively and in a timely manner, then the opportunity will be lost, and the organization might better focus its attention and resources on another opportunity with lesser potential payback, but that has a much greater chance of success.
  3. Develop a roadmap, a tactical plan, for addressing the opportunity. Determine which resources are required – hardware, software, capital, and most importantly people – what policies and procedures must be defined or changed, etc...

Then be prepared to act! Sometimes the best intentions for the New Year fail not for lack of thought or foresight, but for lack of effective follow through. Develop the proper oversight/governance mechanisms, put the plan into action, and then make sure to monitor progress on a regular basis.

These are not difficult steps to follow, but organizations sometimes need help doing so. We’ve found that clients who call us have learned the hard way – either directly or through stories they’ve heard in their industries – that some careful planning, deliberate program design, and – if necessary – some skill assessment and training can take them a long way in their resolutions for success in 2011. Good luck!

photo by L.C.Nøttaasen via Flickr (Creative Commons)

  


DVoorhees_50_bw Dick Voorhees is a seasoned technology professional with more than 25 years of experience in information technology, data integration, and business analytic systems. He is highly skilled at working with and leading mixed teams of business stakeholders and technologists on data enabling projects.


Posted January 11, 2011 6:00 AM
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