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Purpose of Data Analytics projects is very diverse. From process optimization up to new revenue streams. Today we are sharing which are main 6 project steps and key examples of each. Remember that failing in 1 of the steps can led to a complete project failure.  All are important and typically initial steps are the ones taking 80% of the effort (despite the last ones are more trendy nowadays) 1. Data collection The first step in any data analytics project is to collect the relevant data. This can be done from a variety of sources, such as databases, surveys, social media, and customer relationship management (CRM) systems. The type of data collected will depend on the specific goals of the project. For example, if a company is trying to improve its customer experience, they might collect data on customer satisfaction, website usage, and product reviews. 2. Data cleaning Once the data has been collected, it needs to be cleaned. This means identifying and correcting errors and inconsiste

  Data visualization is the process of using visual representations to communicate data. This can include charts, graphs, maps, and other types of visuals. Data visualization can be used to make complex data easier to understand and to identify patterns and trends. Data storytelling is the process of using data to tell a story. This involves using data to support a particular claim or argument, or to illustrate a particular point. Data storytelling can be used to persuade others, to educate them, or to simply entertain them. The importance of data visualization Data visualization is important because it can help us to: Make better decisions: By visualizing data, we can more easily identify patterns and trends. This information can then be used to make better decisions. Communicate data more effectively: Visual representations of data are often easier to understand than raw data. This makes data visualization an effective way to communicate data to others. Engage our audience: Visuals