Clean and Analyze Data

Clean and Analyze Data

Data Cleaning:

The first step in cleaning and analyzing data is to remove any errors, inconsistencies, or duplications. This involves identifying and addressing missing or incomplete data, correcting data entry errors, and ensuring that the data is in a consistent format. Data cleaning also involves identifying outliers or anomalies that might skew the analysis and addressing them appropriately.

Some common data cleaning techniques include:

Collect and Store Data

Collect and Store Data

Before you can collect and store data, you need to identify the key performance indicators (KPIs) that are relevant to your organization. KPIs are specific metrics that help you measure the success or progress of a particular business process. KPIs can vary depending on the industry, organization, or department. For example, a marketing department might measure KPIs such as website traffic, conversion rates, or customer acquisition costs.