examples of behaviors that you could follow that  apply each of the four principles as they relate to data

  • Provide specific examples of behaviors that you could follow that  apply each of the four principles as they relate to data that you would  need to collect for the development of the project scenario app.

Provide specific examples of behaviors that you could follow that  apply each of the four principles as they relate to data that you would  need to collect for the development of the project scenario app.


We’ve all heard it: “Data is the new oil.” It’s a pretty bold statement, but it’s true. If you’re in business today, data is a strategic resource that you can’t afford to waste. Data management and retrieval are critical to any project scenario app–and they’re also one of the four principles of good practice that we’ll be discussing today.

Principle 1: Data Storing and Retrieval

In order to make it accessible, you must store data in a way that is easy for the user to understand and use. The user should be able to access their own information without having any issues with the interface or app itself.

  • The designer will want their work products displayed on a screen in an understandable manner so they can easily measure progress towards a goal or objective. This helps them keep track of where they are at in terms of their design development goals as well as provide feedback on what needs improvement when necessary.*

Principle 2: Reliability

Reliability is the degree to which a system or process produces the same results or outcomes each time it is performed. Reliability can be broken down into three subcategories:

  • Random variation: The chance that a variable will take on different values from its mean (average) value. For example, if you had 100 students in your class and gave them all a test, there would be no way for any student’s score to be exactly equal to their average score. This would be due to random variation—there are many factors affecting how individual students perform on tests such as moods and distractions during testing sessions, which means that no two scores will ever be exactly alike because they’re not controlled by any one factor alone but rather influenced by all those other variables at once!
  • Systematic error: An error related specifically toward producing certain outcomes within our system’s operation; this could include things like mistakes made while entering data into an excel spreadsheet or accidentally clicking on something instead of typing out what we wanted originally into our computer keyboard when we meant something else entirely…and so forth…

Principle 3: Verification and Validation of Data

While it is important to verify and validate data, you need to understand that there are no right or wrong ways of doing so. The only thing that matters is whether you can prove that the data is valid.

There are several different ways in which you can verify data:

  • You could send out surveys and ask people if they agree with certain statements regarding their views on a specific topic. For example, if I wanted to find out what people thought about using an app for grocery shopping as opposed to using Amazon Prime Now delivery service, I would send out a survey asking them which option they preferred and why (e.g., “I prefer using my phone because it’s easier”). This type of question would help establish whether or not most people in your target demographic agree with each statement about their preference for one service over another (in our case). If more than 50% disagree with any given statement made within your survey responses then this means there might be room for improvement when developing scenarios based on existing trends among current users’ behavior patterns who share similar interests as those who will use these apps once they become available again after being discontinued due both threats posed by hackers trying steal personal information such as credit card numbers stored under secure conditions kept offline until needed later on down road.”

Principle 4: Consistency

Consistency is important for data to be useful and usable.

Consistent data can be trusted, reliable, and accurate. For example: if you have a list of customers with their contact information (like names, email addresses and phone numbers), then it’s easy for your customer service team to answer questions about them from customers who call into the company’s call center. But if these are all different lists stored on different servers in different locations—say one list is stored on the cloud while another is stored locally but not backed up regularly—then when someone calls that server looking for information about one customer’s account or another account they may get answers from both sources instead of just one source which would make sense because there are two versions of everything: one file version where everything looks exactly like how it looked before being moved around; another file version containing only what has been added since then (and therefore missing some things).

If consistency isn’t maintained throughout all aspects of an organization then there could be issues down stream such as incomplete information being provided by employees who don’t know how much detail should be included when responding back after receiving queries through email.”

Provide examples of good practices for data management and retrieval

You should have a good understanding of the importance of data management and retrieval. Good practices for data management and retrieval include:

  • Data should be stored in a way that allows for quick access to it, without having to recreate it. For example, if you need to find information about someone who has been in your life recently, but can’t remember their name or how they look, then this would not be useful because there is no way for you to access their information quickly enough (without having to spend hours searching through old files). Instead, consider storing this information in an organized database like Microsoft Excel or Access where it’s easier for everyone involved (including yourself) when looking at past events during our lives together!


This is a great way to start building your project management tool! If you find yourself getting stuck on finding the right data, remember that there are many more resources out there than just these four principles. The internet has a wealth of information on everything from how best to keep track of your data to what tools are available for managing it. You can also ask your team members for their thoughts and suggestions about what works best for them when working with this type of information.


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