The finance team analyzes expenses and looks for opportunities to save money.

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The marketing team monitors potential customer activity and looks for ways to increase conversion through a free trial of the product.
The engineering team needs to understand how many customers were affected by a recent system outage, so they look at product usage data.
The product development team must prioritize the development of new features and bug fixes, so it analyzes the latest support requests and prioritizes the most important ones.
Your goals will influence what data you collect, what analysis tools you use, and what useful information you get as a result.

Clear data and remove unnecessary things
Your data analysis is only as good as the data you norway telegram database collect. If the information you collect is fragmented, inaccurate, or inconsistent, your conclusions will be incomplete or misleading. So after collecting your data, be sure to clean it up and make sure it is consistent and free of duplicate information.

If you're working with a small amount of data, you may find it easier to manually clean it up in a spreadsheet. Here are some simple things you can do to clean up your data :

Add header rows to your spreadsheet to make the information easier to understand.
Remove duplicate rows or columns if you have multiple copies of the same record.
If you exported data, remove rows or columns that you don't want to use. For example, many tools add an "ID" column or timestamps that you don't need.
Standardize data so that numeric values ​​such as numbers, dates, or currency are expressed in a consistent format.