This is a guest post for Integrate.io written by Bill Inmon, an American computer scientist recognized as the "father of the data warehouse." Inmon wrote the first book and first magazine column about data warehousing, held the first conference about this topic, and was the first person to teach data warehousing classes.
Five things you should know about this topic:
- End users typically don't know much about computers for various reasons. For example, computers are difficult to build and require a specific mindset.
- That's why it’s important to manage end-user expectations when incorporating a new system into your organization.
- Bill Inmon outlines five expectations for end users when learning about a new system: Automation, access, speed of access, integration, and integrity. End users have these expectations whether or not they have seen a computer system before.
- You can compare end-user expectations with popular data architecture types such as data mesh and the data warehouse.
- Inmon argues that only the data warehouse architecture fulfills user expectations, making it a good choice for your organization.
End users don’t know much about computers for a lot of reasons:
- Computers are complex to build and use
- Computer courses have been taught in many schools for a while now
- Computers require a certain mindset
- Students invested in other disciplines don’t have much time to study computers
As a result, end users end up in accounting, marketing, sales, or finance with only a scant or limited knowledge of computers.
So what happens if you start talking about building a new computer system with your end user? What is going on in their mind? What are their assumptions and expectations?
Learn more about managing end-user expectations below.
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Presumptive End User Expectations for a System
Assume your end user knows little or nothing about technology (which is a typical state of mind). Then, start talking with your end user and their expectations for the system being discussed.
The following chart shows presumptive end-user expectations for a system being built:
The first thing your end user expects is an automated system. It doesn’t do the end user much good to expect anything else. This is the most basic of the end user’s assumptions.
The second basic thing the end user expects is to be able to access whatever data is being presented. Again, a computerized system would be worthless without meeting this expectation.
Speed of Access
The third basic thing the end user expects is to be able to access data in a reasonable amount of time. This issue can be complex because the waiting time for access is very different for different kinds of data. If you are at an ATM machine, you expect a sub-second response time. But if the IRS is auditing you, it may take you a week to find checks you wrote ten years ago. So speed of access to data is a very relative thing.
Another thing the end user expects is integrated data across their enterprise. When the end user refers to monthly revenue, they mean corporate revenue, not sales forecasts or marketing revenue.
Finally, the end user expects requested data to be accurate and have integrity. Data from a spreadsheet that someone has concocted half an hour ago is not what the end user expects. The spreadsheet could say anything and have no basis to reality in any case.
The end-user has these expectations whether or not they have ever seen a computer before. They assume data and all automated systems have these characteristics.
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End User Expectations and Popular Data Architectures
The following chart matches up end user expectations with some of the popular architectures out there: Data mesh architecture and data warehouse architecture.
Data mesh meets some of the basic issues of end-user expectations. When it comes to automation, access, and speed of access, data mesh is a good fit. However, data mesh doesn’t meet integration and integrity at all. Or is it just an accident if those qualities are found in a data mesh architecture?
Now compare the end user’s expectations with data warehousing. Data warehousing fulfills ALL expectations.
It is true that a data warehouse architecture takes a lot more effort to build than a data mesh architecture. But the data warehouse fulfills ALL of what the end user simply expects to be in a system. The data mesh architecture does not.
So why does a data warehouse architecture take more effort to build than a data mesh architecture? The answer is simple. In order to build a data warehouse, you have to integrate data. With data mesh, there is no need to integrate data. And, however you do it, integration takes time and work.
When you start to compare data mesh and data warehouse architectures, you have to ask yourself the questions: Do I want something that is cheap and fast to build but fulfills only some of my end users’ expectations? Or do I want something that is more difficult to build that will fulfill all of my end users’ expectations?
The choice is yours.
The data warehouse architecture can help you meet all user expectations. Move data to a supported warehouse with Integrate.io’s out-of-the-box connectors and reduce the time it takes to build complex big data pipelines. No data engineering experience is required! Schedule a demo now.
Bill Inmon, the father of the data warehouse, has authored 65 books. Computerworld named him one of the ten most influential people in the history of computing. Inmon's Castle Rock, Colorado-based company Forest Rim Technology helps companies hear the voice of their customers. See more at www.forestrimtech.com.