This content originally appeared on DEV Community and was authored by Kihoro Codes
Introduction
Before explaining the techniques and tools that are involved in data analytics, first we need to understand what data analytics is all about. A data analyst is the person that conducts the data analytics of a company.
What is data analytics?
This is the process that involves collecting data from a specific field or subject, cleaning and transforming the data to visualizations that can be used to come up with solutions to problems within the given field.
The process involves identifying trends and patterns within the data for example if analyzing data for an ecommerce site, one can derive the time when most customers are on the site.
Who is a data analyst?
This is the professional who conducts the collection of data, cleans the data and finally transforms the data using a number of techniques and tools.
Tools used in data analytics
There are a number of tools that a data analyst has to master. They include:
- Spreadsheets i.e Excel or Google Sheet
- Visualization tools such as Tableau and Power BI
- Querying tools such as Python, SQL and R
- Big data processing tools such as Hive and Hadoop
- Access and extraction tools such as Data Lakes, Data Pipelines _and _Data Warehouses.
It is important to master at least one tool for a specific task instead of learning all the tools that conduct the same task. For example, under the spreadsheets, master only one either Excel or Google Sheets. This is because the principles found under one tool are likely the same for the other tool.
Fundamental skills of a data analyst
- Statistical skills. Analysis involves finding relationship between data, therefore mean, correlation and mode of data is calculated.
- Analytical skills. An analyst should have the ability to look at a dataset and figure out possible queries to create that are relevant to it.
- Data visualization skills. While presenting their findings, an analyst should know the best type of graph to use in order to present the data in the most appealing format
- Problem solving skills. After analyzing results from data, and analyst should have the ability to figure out the problems that can be solved using its findings.
- Project management skills. An analyst should be organized in the whole process of gathering data to the point of presentation. Every step should be well documented to reveal the accuracy of the data.
This content originally appeared on DEV Community and was authored by Kihoro Codes
Kihoro Codes | Sciencx (2024-10-17T03:56:48+00:00) MASTERING DATA ANALYTICS: The Ultimate Guide To Data Analytics. Retrieved from https://www.scien.cx/2024/10/17/mastering-data-analytics-the-ultimate-guide-to-data-analytics-3/
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