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Showing posts from June, 2025

Your Data Strategy: How to get it moving

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  Building and executing a data strategy is hard, and if anyone tells you they can do it for you in 3 easy steps, they are lying.  The fact is, there are quite a few steps involved that can seem overwhelming.  Some of these steps can take an organization years to cultivate, like building a culture that not only relies on the data but demands to have it to make any decision.  A key thing to remember, however, is that a data strategy does not need to be fully baked when you start down the road of implementing it.  When you build using strong data principles, you will be able to move forward providing business value, and your data strategy can flex as you fill in the details.  The Main Parts of Your Data Strategy: So what are the parts of a data strategy, which ones do you need right away, and how can your data principles help fill in the gaps?  Below are 10 core parts of a data strategy that you will need to at least consider before starting. ...

Data Principles: Using Nothing to get the job done

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  At first glance, the value of nothing is not significant.   In the world around us, we literally walk past “nothing” all the time and don’t even notice it.      But at times, “nothing” is just as important as something.   For example, if you were walking on a city street and someone removed a manhole cover.   That “nothing” would certainly have a huge impact if you fell into the manhole. Another way “nothing” can impact you is that it allows others to make assumptions.     Have you ever been in a conversation with a friend when they asked you a question you did not want to answer?   Instead of telling them, “I would prefer not to comment,” did you just leave your comment unsaid, just hanging there in the air?   You were hoping they would infer that you did not want to comment, but is that what happened?   You see, when you did not specifically answer the question, you allowed your friend to answer for you, and that is whe...

Data Principles: Building Bridges with Auxiliary Keys

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When designing your data model, especially in data warehousing or analytical systems, you might opt for identity columns as primary keys. This is a common and often advantageous practice due to the inherent benefits of identity columns. However, relying solely on these generated keys can create a disconnect with how the business views and interacts with data. This is where the data principle of utilizing auxiliary keys becomes crucial. Identity Columns: The Physical Key to Optimization Before we dive into how the principle of using auxiliary keys works, we have to define what we would use as a primary key.  In the world of data warehousing, it is common practice to use identity columns as the primary key of every table.  These auto-incrementing integer columns offer several advantages in database design, but as we will see, they do have flaws.  Some advantages are: Compact Storage: Identity columns are generally small, fixed-size data types (like integers), which makes t...

Data Principles: Consequences of Foreign Keys

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As a child, did you enjoy doing your chores, or did you think your parents were just being mean?  As a parent, even though you know your child is not happy with you when you enforce the chore list, why do you do it?  Certainly, in the current moment, enforcing chores is not easy.  Making your child comply takes effort and consistent oversight.   Who has time for that, right? But after 18 years of that effort, what do you end up with?  Isn't it true that these chores build a solid foundation for your child to stand on as they enter the adult world?  Didn't all of that constant oversight and hard work pay off as you proudly watch your very capable child move on to the next challenge, knowing they would be able to conquer it?  When implementing a data strategy, you are faced with a similar question.  Where do you put your time, effort, and energy?  Do you go quickly, bypassing things you know will be problems in the future for the quick win...

Data Principles: Sharing Knowledge with Column Metadata

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Did you have a sibling growing up?  Maybe an older brother or sister who did not like sharing?  Or maybe there was a neighborhood kid who was not good about being a team player?  Do you remember that frustration when all you wanted to have was a chance with the football, but because it was not yours, you could never touch it? Do you still get that angry, anxious feeling when you open your data exploration tool of choice, knowing that there are secrets hidden in that data that you have no idea about?  Does the customer on the sales order always have to be the party that pays the invoice?  Should the bill-to address be the ship-to address?  What impact do the shipping terms have when we consider a late payment? Wouldn't it be nice if that type of information were kept somewhere, besides in the head of the person who has worked with the data the longest?  How mad would you be if I told you there has been a place for this data for years, but it just was no...

Data Principles: The Power of Naming Standards

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In my last blog, I highlighted five data principles that I have used in the past to create a solid data strategy.  The idea behind a principle is that it is flexible to adjust to changing needs but rigid enough to maintain order.   A good example of this is the golden rule, "do unto others as you would have them do to you".  When you apply this principle, you are free to do whatever you want, as long as it is something you want done to yourself.  It is a very flexible principle that can have serious consequences if broken.   One crucial principle that forms a solid foundation for your data initiatives is  naming standards . It might seem like a simple concept, but consistent naming conventions throughout your data environment can significantly impact efficiency, governance, and understanding for everyone involved.  With the right naming standards, looking into the data environment as a DBA, developer, or user, there will be no question about ...

Data Strategy: Guiding Principles

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  It has been a long time since my last post, and a lot of things have changed.  I have a new job, I have moved to the other side of the state, and I even have a new dog.  But one thing that has stayed with me is my focus on data and how much potential it has.  All of this change has also solidified my understanding of why a data strategy is critical to any success in the data world.  Without a strategy, your effort will be as useless as trying to strike the wind.  You have to be able to aim your blows if you intend to hit anything.  In our case, we want to "hit" that business objective, the one thing that the business must have to progress to the next phase in its development.   The thing I have come to understand is that when the term "Data Strategy" is used, most people in management jump right to the end and focus on things like cost or "vendor lock-in".  Some people in management focus so much on what they perceive the outcome will ...