The first step is to define what data will be collected and how it will be organized to be useful.
for decision making. It is important to be clear about the objectives of the data analysis and
identify which data are relevant to achieving these objectives. The collection of this data should
be automated where possible and be in line with the company's privacy policies and
the data protection laws in force.

The data collected must be relevant to your business, that is, it must be directly
related to the company's processes and activities. They must be organized into a template.
structured data, with well-defined fields and consistent values. This will facilitate analysis and
creation of reports and dashboards.

The choice of the ideal data analysis software or tool will depend on the needs and
company-specific goals. It is important to evaluate each option based on features, costs,
ease of use and integration with other tools used by the company.

To ensure data security throughout the process, it is important to follow some good
practices such as Encryption, Access Control, Authentication and Authorization,
access, Backup and recovery, Privacy policies, Compliance with data protection laws
data. 

It is important that data security is considered at all stages of the data process.
Analytics, from collection to analysis and sharing of results. ensure privacy
of data is critical to maintaining customer confidence and avoiding potential legal penalties.

To ensure that the team is prepared to use the Data Analytics solution in a
efficient and make the most of the insights generated, it is important to follow some practices such as:

● Appropriate Training
● Data Culture
● Easy Data Access
● Ongoing Support
● Knowledge Sharing
● Performance Metrics