In my last blog post we started discussing the topic of data. We discussed how to identify data, and one of the tools (Business Glossary) you can leverage to ensure everyone is speaking the same language.
In this blog post I will take you through the 3 other techniques that may be leveraged to document the data as well as a few helpful hints on how to best analyze data. To be clear, these are not the only techniques, just the last 3 of the 4 I wanted to discuss so let’s jump in.
The purpose of the data dictionary is to identify and define the:
There may be other attributes that can be captured based on the organizational needs, but these are a great started.
So, building upon our example from Part 1 for interacting with a financial institution, you may have data elements defined as below that relate back to specific data that would be captured.
An entity relationship diagram describes entity types and specifies the relationships that can exist between them.
Again, building upon our example from Part 1, three entities that may exist in the financial data structures are “Account”, “Customer”, and “Product”. In Figure 2 we see that within the “Account” entity you may have data elements such as “Account ID”, “Account Name”, “Account Description” and “Account Open Date”. Within the “Customer” entity you may have data elements such as “ID”, “Name”, “Address”, “Phone”, “Email”, “Account Number” and Type”. Now the relation between the “Account” entity and the “Customer” entity for this example is as follows:
To be considered a customer you must have an account with the financial institution. For this example and account and product are different. The account is either a checking or savings account. A product may be a credit card or personal loan.
A system context diagram demonstrates the external components that may interact with the system. I like to define a core system and then show the other systems, applications, or other external components that interact with the core system. In Figure 3 we see the core system named the “System of Record” and the other systems or application that interact with that core system, as well as the data that is passed between those systems.
Now that we have completed reviewing the last 3 techniques, I wanted to focus on let us move into how to analyze data.
There are many ways to slice and dice data, and it can be fun doing so. I like to pursue analyzing data in 6 steps:
In my next and last post on this topic, I will give a brief introduction to data analytics, including the various types and how to leverage various techniques to analyze data.
Until next time, signing off,
The BA Martial Artist ?