Data analysis is the most important practice for any successful business. Companies now understand the value of data analysis for their business development.
However, the analysis of the data requires time, specialised staff and the right technology.
Choosing the right data analysis tool is the most difficult and profitable change for your business.
What’s data analysis?
Data analysis is a method of extracting useful information from the data provided in order to make more convincing decisions.
The main purpose of data analysis is to make decisions that benefit the organisation. With the right tools and training in data analysis, you can improve your business and take it to new heights.
Data analysis tools for modern times
There are many data analysis tools to be found in 2020. However, you cannot expect comparable results from all these instruments.
There are paid tools for data analysis, while others are free and open-source software. Surprisingly, some free tools can be used for a fee.
It is always best to be familiar with the various data analysis tools before using them to analyze your valuable data.
The following list contains the most important data analysis tools available so far:
Python is an open source object oriented programming language that can be used for data analysis. It is one of the fastest growing and most reliable data analysis tools. The reason for 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 what you want on Peton. Python can perform various analyses independently of each other.
Tableau is another powerful open source data analysis tool that makes it possible to visualize and compare data. The best thing about Tablo is its simplicity.
The reports on the table can be shared online via social networks or another platform. It enables real-time presentations on the internet. One of the disadvantages of Tableau is that it does not support advanced SQL queries.
R is a programming language mainly used for the analysis of data. Several other data analysis tools in the sector can dominate performance or data volume.
It offers many useful features and packages that make it ideal for data analysis. You can choose to install the packages you need for your needs. This tool is free.
Excel is used in almost all sectors as a data analysis tool. It is a simple and powerful data collection and analysis tool that can support virtually any standard analysis workflow.
Excel offers many possibilities for statistical analysis of the data. The large number of graphs and charts available in the tool facilitates the analysis of the data.
However, the program Ms Excel is not suitable for extensive data analysis. Microsoft Excel is not free because it comes with the Microsoft Office suite.
Spark is suitable for the analysis and processing of large amounts of data. It was already developed at the University of California in 2009. It processes large amounts of data at a significantly higher speed.
It is made for developers, researchers and data specialists. The spark is easy to study and can work on all major platforms.
Large companies like 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, as well as interactive presentation. It also enables the distribution of live dashboards and reports.
In short, it is the ideal formula for all your data analysis needs. There are free and paid versions of Power BI. The desktop version is free, while the Pro and Premium versions are not free.
SAS is one of the best tools for data analysis.
The tool is easy to use and operate.
SAS can analyse data from any source. It is the first choice of large 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.
The importance of training in data analysis
Companies make almost all important decisions based on data analysis. It shows how many companies rely on data analysis.
However, these tools will only deliver better results if the user is trained in the use of the software. Processing such valuable data requires skills and knowledge. There is a huge demand for data analysts, which will continue to grow in the coming years.
If you are considering training in data analysis, you should start immediately.
Why start training the data analyzer now?
- Demand is high – demand for data analysis has already exploded, and this is just the beginning. Many companies are looking for the best specialists in this field to manage their data.
- This is a very well-paid profession – with high demand, companies are willing to pay high salaries to people who are able to manage and analyse their data properly.
- This is a high-priority profession – most companies consider data analysts to be the most important part of their business. Data analysts are irreplaceable because they manage and analyze important and critical business data.
- No prescriptions. The best part of learning to analyze data is that there are no conditions. You can be an experienced professional or just not a student.
But it takes certain skills to shine as a data analyst.
How do I become a data analyst?
These steps will help you become a data analyst.
- Obtain a degree with a specialisation in mathematics, statistics or computer science. This will serve as a basis for your further training.
- Learn data analysis techniques and get certified.
- Prepare a resume that highlights your talents and achievements. Name any professional training.
- Take a look at the general interview questions with the data analyst and prepare for the interview. Be sure to pay as much attention to practical, instrumental questions as to theoretical questions.
- Apply for a position as a data analyst, wait for the results and refine your knowledge.
Data analysis is the basis of all research in any organisation. This helps the company to find and overcome shortages. However, you must use the right tools that serve the purpose of your organization.
It is therefore always best to look around and find the tool that best suits your needs.
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