Data Analytics involves applying an algorithmic or mechanical process to derive insights. For example, running through a number of data sets to look for meaningful correlations between each other.
It is used in a number of industries to allow the organizations and companies to make better decisions as well as verify and disprove existing theories or models.
The focus of Data Analytics lies in inference, which is the process of deriving conclusions that are solely based on what the researcher already knows.
The Skills you Require To become a good Data Analyst:
Programming skills: Knowing programming languages are R and Python are extremely important for any data analyst.
Statistical skills and mathematics: Descriptive and inferential statistics and experimental designs are a must for data scientists.
Machine learning skills
Data wrangling skills: The ability to map raw data and convert it into another format that allows for a more convenient consumption of the data.
Communication and Data Visualization skills
Data Intuition: it is extremely important for professional to be able to think like a data analyst.