Imagine if you owned a restaurant, and you found out that about 10% of customer checks didn’t match up with orders placed through the kitchen. You’d quickly ask tough questions: Is someone stealing money?  Are customers being cheated? What’s causing the errors? After a quick assessment you would take quick action to correct the problem and make sure it never happens again.

Strangely, that kind of awareness of data quality doesn’t seem to scale up to large organizations.  When data management teams contact CapTech for help, they routinely recount challenges in funding data quality work. They ask for simple, direct examples showing tangible business benefit from improving data quality. 

Here are three of our favorites:

Interestingly enough, this thought comes to me as I'm devouring my dinner at a local buffet-style restaurant establishment.  Maybe it's due to the influence of the Food Network, but it seems as if I have recently trended towards explaining technical concepts with food analogies.

Quality data fulfills the business' needs. Where as, mass quantity of data may satisfy the end-user's wants.  Of course there are trade-offs!

Sure, while standing in the buffet line, if I'm asked what I want, I'll ask to have food items piled on to my plate overflowing onto my tray.  However, when I sit to consume the food (read: querying data), it takes longer to load it all off of my plate and into my mouth (read: generating report), to the extent that I'm becoming groggy and sluggish (read: lag in rendering output).

Let’s play a word association game. When I say “Architect” you say, what? “Buildings… Cities… Sky scrapers…?” How about “Data”?

More and more professionals who work with data are starting to see themselves as architects.  A quick look in the dictionary shows that the title ‘architect’ is aligned with the design of physical structures. However, a closer look into what it takes to ‘design’ highlights the similar processes involved whether the medium is bricks and mortar or data.

This is the second in a two-part series on populating Combo Boxes using Advanced Filter and VBA in Excel.  Click here to read the first part, Populating Combo Boxes Part1 – Advanced Filter. We will start with the Excel file that you modified in Part 1.

The Excel file includes the data set, and some code that we wrote in the first part of the series.  In this part, we’ll learn how to use the Advanced Filter code to populate combo boxes.

The terms data and information are often used interchangeably.  However, in the data warehousing world they are quite different from each other.  Remembering the difference is as simple as the difference between Charlie and Raymond Babbitt.  You may remember these two characters from the movie Rainman.  Charlie is the younger brother of austitic savant Raymond.