First off, my apologies to Paul Simon regarding the title of this blog post — but I simply couldn’t resist 😉
When architecting and building solutions for customers, I tend to make heavy use of typed DataSets.
I believe I used them on my very first .NET project almost ten years ago, because I still clearly remember Mike Pizzo (one of the original architects on the ADO.NET team) explaining to us how we should think of DataSets as a “scratch pad” for disconnected data (as opposed to the old DAO, RDO, and ADO objects — which thankfully are a thing of the past for most organizations). [Okay, I suppose that, technically, you could disconnect an ADO Recordset from the underlying database, but that’s not how it was frequently used.]
The tooling for typed DataSets has always been very good (at least in my opinion). You can create a typed DataSet very quickly using the designer in Visual Studio and restructure an existing typed DataSet with ease. In my opinion, this is almost always faster than writing the equivalent C# code directly.
I also love the way typed DataSets can be somewhat complex — in terms of the business rules that are encapsulated by them — yet at the same time very easy to understand for developers that are not familiar with your solution (e.g. new team members or developers responsible for maintaining the solution).
For example, consider the typed DataSet shown below.
What can you tell just by looking at the diagram? What are the business rules that are enforced simply by the structure of the tables, relationships, and columns?
- First, you can see that ScorecardData (the name of the typed DataSet) contains information about scorecards for client sites (i.e. locations). Note that the term “scorecard” in this scenario refers to a collection of key performance indicators (KPIs) displayed on a dashboard.
- Each scorecard is simply a collection of items (essentially the KPIs) — with each item corresponding to a particular client site.
- Each scorecard item may have one or more instances of a KPI status (i.e. the measure of the KPI for a particular period). The status — i.e. “Exceeds”, “Meets”, or “Does Not Meet” (a.k.a. “Green”, “Yellow”, or “Red”) is determined by a corresponding set of thresholds.
Why about the primary keys on the various tables?
- The primary key on the Scorecard table is obvioulsy ScorecardId.
- The primary key on the ScorecardItem table is ScorecardItemId — although not quite as obvious as the Scorecard table, since there are multiple key icons shown on that table in the designer. However, you can infer this from the relationship between ScorecardItem and KpiStatus — and the fact that only the ScorecardItemId column appears in the KpiStatus table. [Wouldn’t it be nice if the DataSet designer in Visual Studio showed a different icon for the primary key from for other unique keys?]
- The primary key on the ClientSite table is ClientSiteId — which again, can be inferred from the relationship between the ClientSite and ScorecardItem tables.
- The primary key on the KpiStatus table is (ScorecardItemId, Period) — thus allowing each scorecard item to specify one or more KPI status values (for different time periods).
If you were to right-click on the ScorecardId column in the ScorecardItem table in Visual Studio and then click Edit key…, you would see that there is a unique constraint on (ScorecardId, ClientSiteId, KpiName). In other words, each scorecard can only specify one scorecard item for given site and KPI (e.g. we don’t want to allow “Site1” to have two scorecard items that refer to “KeyPerformanceIndicator1”).
Also note that since a primary key on a table must be unique, the constraint on the KpiStatus table ensures that a scorecard item (i.e. a KPI) is only allowed to specify one KPI status for a particular time period. It just doesn’t make sense that “KeyPerformanceIndicator1” could be both “Green” and “Red” for, say, the “2010 Q1” time period — it has to be one or other (or “Yellow”, I suppose).
We can also see that there is a unique constraint on the ClientSiteName column in the ClientSite table. Here’s where things get slightly more complicated. Suppose that we wanted to retrieve data from this DataSet by filtering on the ClientSiteName. In other words, we want to only show KPI information for a particular site. Seems reasonable, right?
What if two completely different clients each had a site named “Headquarters”? That could definitely be a problem, because we certainly wouldn’t want to show one client’s data to a different client.
However, in order for that to actually occur, we would first have to populate the DataSet with information from two different clients. Since that wasn’t how I intended this DataSet to be used, I chose to add a unique constraint on the ClientSiteName column. If, at some later point in time, new scenarios were added and I needed to use this typed DataSet to store data from multiple clients, then I would probably add a Client table and adjust the relationships and constraints accordingly.
Okay, so where exactly are we — after all this verbiage?
The point I was hoping to make so far is that — without looking at a single line of code or any documentation (which many developers don’t like to read anyway) — we know quite a bit about the solution, including some of the business rules, just by looking at the typed DataSet.
In my next post, I’ll discuss some smart ways we can interact with a typed DataSet when actually building a solution.
[I know the content of this post is very elementary, but bear with me, I promise things will get more interesting in subsequent posts 😉 ]