Data analysis is a crucial practice for any successful business. Companies now understand the value of data analysis for growing their business.
However, data analysis takes time, a dedicated staff, and proper technology.
Choosing the right data analysis tool is the most daunting and the most rewarding change for your company.
What is Data Analysis?
Data analysis is a method of getting out useful information from provided data to make more conclusive decisions.
The main objective of data analysis is making decisions that are going to be profitable for the organization. With the right tools and proper data analyst training, you can improve and lead your company to reach great heights.
Data Analysis Tools of the Modern Age
There are a lot of data analysis tools that you can find in 2021. However, you cannot expect similar results from all of these tools.
There are some paid data analysis tools, while some are free, open-source software. Surprisingly, some free tools can stand toe to toe with paid ones.
It is always better to know different data analysis tools before implementing it for analyzing your valuable data.
The list below details the top data analysis tools of the present day:
Python
Python is an open-source, object-oriented programming language that can be used for data analysis. It is one of the fastest-growing and robust data analysis tools. The reason behind its growing popularity is that it is easy to learn.
Python supports many third-party packages for machine learning and data visualization. With these third party packages, you can do anything that you want on python. Python can handle various analysis on its own.
Tableau
Tableau is another powerful open-source data analysis tool that helps to visualize data and make comparisons. The best thing about Tableau is its simplicity.
The reports created on Tableau can be shared on the internet through social media or any other platform. It allows real-time presentation over the web. One drawback of Tableau is that it doesn’t support advanced SQL queries.
R Programming
R is a programming language that is mostly used for data analysis. It can dominate several other data analysis tools in the industry regarding performance or data capacity.
It provides many useful features and packages, which makes it a perfect suite for data analysis. You can choose to install packages that you require for your purpose. This tool is free of cost.
Microsoft Excel
Excel is widely used across almost all kinds of industries as a data analysis tool. It is a simple and powerful tool for data collection and analysis and can support almost any standard analytics workflow.
Excel offers many options to perform statistical analysis of data. With varieties of charts and graphs available on the tool, data analysis becomes more straightforward.
However, Ms-Excel isn’t suitable for analyzing extensive data. Microsoft Excel is not free as it comes with the Microsoft Office Suite.
Apache Spark
Spark is suitable for analyzing and processing big data. It was developed back in 2009 at the University of California. It processes big data at a significantly faster speed.
It was built for developers, researchers, and data scientists. Spark is easy to learn and can operate across all major platforms.
Big companies such as Uber and Shopify use Apache for data analysis. It is an open-source tool.
Microsoft Power BI
Power BI is another powerful and popular data analysis tool. Power BI offers a wide range of options for data management, analysis, and visualization, and interactively presents them. It also allows live reporting of dashboards and reports.
In short, it is the ultimate package for all your data analysis requirements. There are both free and paid versions of Power BI. The desktop version is the free version, while the pro and premium versions require payment.
SAS
SAS is one of the top tools out there when it comes to data analysis.
The tool is straightforward to use and manage.
SAS can analyze data from any source. It is the first choice for top companies such as Google, Facebook, and Netflix and is also used for predictive analysis.
SAS is a paid tool, but there is also a free version for students to learn.
Importance of Data analysis Training
Companies take almost every major decision based on data analysis. It shows how much companies rely on data analysis.
However, these tools will only provide better results if the user is skilled in the software. It requires skills and knowledge to work with such valuable data. There is a massive demand for data analysts, and it will keep increasing in the coming years.
If you are thinking of taking data analysis training, you must begin immediately.
Why You Should Begin Data Analyst Training Right Away
- It is highly in demand – The demand for a data analyst is already over the roof, and it is just the beginning. Many companies are searching for the best professionals in the domain to manage their data.
- It is a highly paid profession– As the demand is high, companies are willing to pay high salaries to individuals who can adequately manage and analyze their data.
- It is a top priority profession– A majority of companies consider data analysts a crucial part of their business. Data analysts aren’t replaceable as they will be managing and analyzing big data that are critical for the business.
- No prerequisites– The best thing about data analysis training is that it doesn’t ask for any prerequisites. You can be an experienced professional or just out of college.
However, you will need to master some skills to shine as a Data Analyst.
How to Become a Data Analyst?
These steps can help you become a Data Analyst.
- Get a degree focused on maths, statistics, or computer science. It will serve as your basis for further training.
- Learn data analytics skills, and get a certification.
- Prepare your resume highlighting your talents and achievements. Mention any vocational training.
- Go through common data analyst interview questions, and prepare yourself for the interview. Make sure that you pay equal importance to tool based practical questions as theory questions.
- Apply for a job as a Data Analyst, wait for the results, and keep sharpening your knowledge.
Conclusion
Data analysis is the core of all research in any organization. It helps the company find flaws and overcome them. However, you must use the right tools that serve the purpose of your organization.
Hence, it is always best to look around and find the best tool for your needs.
