The goal of all data analysts is to use data to draw accurate conclusions and make good recommendations. That all starts with having complete, correct, and relevant data. Accurate interpretation of that data is key to data-driven decisions. It is possible to have solid data and still make the wrong choices. Data ethics refers to well-founded standards of right and wrong that dictate how data is collected, shared, and used.

An individual who provides their data has the right to know and understand all of the data-processing activities and algorithms used on that data. We are all entitled to our privacy. It’s all about access, use, and collection of data. It also covers a person’s legal right to their data. This means someone like you or me should have protection from unauthorized access to our private data, freedom from inappropriate use of our data. The right to inspect, update, or correct your own data is part of data privacy.

For companies, it means putting privacy measures in place to protect the individuals’ data.

When looking at the data itself, a data analyst asks who, what, when, where, why, and how in order to put information into context. We need to remove bias. We all have biases and we must strive to be objective before we draw conclusions. The collection and analysis of the data can be bias and lead to incorrect conclusions.

Bias

You never want bias. In data analytics, you may encounter several types of bias.