Design a data warehouse that supports many-to-many relationships

-
There are several business scenarios that require modeling many-to-many relationships such as Customers-to-Products and Products-to-Customers. Some of these many-to-many relationship requirements arise from the need to support:

  • Different perspectives for reporting and analysis
  • Complex business processes
  • Relational source system limitations
A data warehouse model that supports many-to-many relationships




















To satisfy the Sales manager’s requirement a SQL query as shown below can be executed to select customers from the Southeast region for example:

SELECT distinct
dcust.Customer
FROM [Fact].[Sale] fs
inner join [Dimension].[Customer] dcust on dcust.[Customer Key] = fs.[Customer Key]
inner join [Dimension].City dc on dc.[City Key] = fs.[City Key]
WHERE dc.[Sales Territory] = 'Southeast'

In the query above, notice that three tables needed to be joined, [Fact].[Sales [Dimension].[Customer] and [Dimension].[City]. The [Fact].[Sales] table in this query acts as a relationship table between the two dimension tables, thus creating a many-to-many relationship.

Comments

Post a Comment

Popular Posts

Install Master Data Services (MDS)

-
Image
The installation of Master Data Services consists of three steps as follows: 1. Install required Windows roles and features 2. Install Master Data Services from the SQL Server installation media 3. Configure Master Data Services from the MDS Configuration Manager Windows roles and features installation To install the Windows roles and features required for MDS, you can use Windows Server Manager  or through a PowerShell script. To start the Windows roles and features installation using  Windows Server Manager follow these steps: 1. Open Server Manager and click on Manage on the menu bar, then click Add Roles and  Features from the drop-down menu options to launch the Add Roles and Features  Wizard. 2. On the Select installation type window, select the “Role-based or feature-based installation”  option as shown and click Next. 3. On the Select destination server window, click the checkbox for the “Select a server  from the server pool” optio
Read more

Non-blocking, semi-blocking, and blocking transforms in SSIS

-
Not all Data Flow transforms are created equal. In fact, some are much faster and require a  lot less memory (non-blocking transforms). Others are slower while consuming much more  memory (blocking transforms), and some are in between (semi-blocking transforms). We don’t  always have a choice if we need to use a certain transform to do a certain specified task, but  it is good to know the differences between these types of transforms so that we can better  understand performance and resource utilization issues. Synchronous and asynchronous There is another related aspect about Data Flow transforms, which is their ability to quickly  process a row as they are coming into the transform, independently of any other rows that  came before or after (synchronous transforms). The other type of transform needs to be  dependent on some or all of the rows that come before and after (asynchronous transforms). On the whole, non-blocking transforms are also synchronous, thus are fast and
Read more

Design an appropriate storage solution, including hardware, disk, and file layout

-
Image
The data warehouse storage’s performance can be measured by  analyzing the time it takes for read and write operations to complete, known as latency , and by  analyzing how much data volume it can read or write in each time frame, known as throughput .  High latency and low throughput can be an indication of an improper selection for the  storage infrastructure or incorrect hardware and software configurations. Performance of a storage subsystem can  be estimated based on several criteria: Volume of data Rate of change and growth of the data Data retention policy Number of concurrent users Typical workloads expected Two important metrics associated with storage are throughput and Input/Output Per  Second (IOPS) . Throughput is a measure of the amount of data that can be transferred in a  period. This is typically measured in megabytes or gigabytes per second. IOPS is the number of  I/O read or write operations that can complete in a second.  It is important
Read more