Irrelevant data removed this includes outliers

A healthy data architecture is one in which the data collected is working for you—you know what you have and how you are going to use it. Having a healthy data architecture also means that you are protecting your customer’s privacy:
Only collecting the information needed
Securely storying it
Limiting access to the data to those who need to work with it.
This may sound overwhelming, but there are many different solutions available to this. Spending time reviewing your company’s goals and pain points will pay off! You will want to adopt a software solution that scales according to your needs. Here are some common options.

Customer relationship management systems crm

Track all your customer data so that you can retain, build, and develop strong customer relationships.
Data management platform (dmp): used in advertising to store and activate third party data.
Customer data platform (cdp): used to telemarketing list providers route data sources into one central location.
Step 3: clean your data
To get the most out of your data, you need to be sure that it is clean. This is like the importance of having plaque-free arteries to supply the heart with blood. Clean data includes several components:

The data has been de-duplicated.
The data stored in a consistent format (think of phone numbers: what are you using to separate the numbers? The formatting should be consistent for every phone number you are storing!)
Missing data filled in where possible.

Data validated (this step involves checking the stored data for accuracy).

Find the pulse of your data

Now you’re ready to put your data to work! The challenging CU Lists work mapping, centralizing, and cleaning your data pays off when you can start analyzing and leveraging it. This step will look a little different for every company, it revolves around what you collected and the questions you want to be able to answer. You might leverage your data to answer questions related to customer behavior and buying patterns, tracking, and predicting sales, streamlining processes and operations, or budgeting and forecasting.
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