What is Data Analysis?
Data analysis is the process of analyzing, processing, and analyzing these data sets from many different data sources in order to interpret and come up with conclusions and recommendations. The increase in data types and sources has created a complex data ecosystem, thus the need for revolutionary data analysis tools. This article will delve into some of the necessary tools and techniques that are crucial in tackling data queries and challenges.
Crucial tools:
To start with, the first crucial basic tool that should be a staple for any data analyst is to have a basic understanding of how technical programs work. One of the juggernaut that is Python. Python is a programming language used for writing code and scraping data from databases and websites. Secondly, a data analyst should have access to text editors like VSCode and scriptwriting and database programs such as SQL and DBeaver and have a proper understanding of data storage software such as Microsoft Excel and data presentation software such as Power BI. All these software's and tools enable ease of processing data in any data analyst's career.
As I continue with my learning experience, I have also come across several analytical techniques that I still need to further delve to in order to be proficient in this field. Some of these skills include:
i. Descriptive analysis
ii. Cluster analysis
iii. Regression analysis
iv. predictive analysis
All these skills paired well with critical thinking and base knowledge in the field of research makes a good data analyst.
Conclusion
To conclude, data analysis is the door that opens opportunities for solving real life problems. It is therefore crucial for data analysts to have high expertise in the tools used in this field and be flexible to adapt to any changes within this fast-evolving industry.
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