In an era full of data, data analysis allows us to discover the most useful information and make more scientific decisions for business operations. Data analysis tools are widely used by data analysts as well as non-professional business people to achieve better performance and higher efficiency. 

There exists a variety of data analysis tools for you to choose from. To assist you in selecting the one that best fits your company’s needs, let’s examine several best data analytics tools that are popular in 2023.

How to Choose Data Analysis Tools

Before you start to evaluate the tools, there are several things you need to take into consideration.

Firstly, you need to figure out the user’s level of professional knowledge. Some data analysis software demands high-level coding knowledge, while others are almost zero-code tools. So you’d better choose the tool that matches the user’s level to ensure a friendly user experience.

Secondly, having a clear understanding of the features you require will also make your choice wiser. The features you or your company need are core factors influencing your selection of the data analytics tool. For example, if you want the features of data visualization, such as stunning dashboards and rich charts, business intelligence tools are more suitable for you than pure programming tools.

Finally, the budget can not be ignored. It is recommended to choose the most cost-effective data analysis tool within your budget. 

15 Best Data Analysis Tools

After identifying the above factors, we can start to take a look at the popular data analysis software. Here I list 15 excellent tools for data analysis, among which there must be the one that fits you best.

1. FineReport

FineReport is a business intelligence reporting and dashboard software that helps enterprises transform data into value. Its typical users are IT staff with basic SQL knowledge.

Key features:

It supports connecting to almost all mainstream data sources so that you can analyze data from different sources in just one single report or dashboard.

It is also professional in data visualization with multiple pre-defined dashboard templates and various types of charts, such as dynamic report charts and maps. The interactive effects created by FineReport, such as data drilling, and components linkage, also enable you to do multi-dimensional data analysis.

Data entry is the function that differentiates FineReport from other data analysis software. It allows users to add, delete, or modify data in the databases to achieve the goal of automatically updating the data displayed in the reports or dashboards. 

Price:

FineReport has a free version for personal use without limitations of time and features. It also has a commercial version for enterprises. The price is flexible, based on the features, users, and services.

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2. FineBI

FineBI is a business intelligence tool for self-service big data analysis and data visualization. It is developed mainly for business personnel or data analysts with basic business logic and data knowledge to design their dashboards independently and analyze the data they need, leading to wiser business decisions for long-term development.

Key features:

As a professional data analysis tool, FineBI successfully meets business people’s flexible and changeable data processing requirements through self-service datasets. It provides you with functions like adding columns, grouping statistics, filtering, sorting, merging up and down, right and left, and so on so that you can process data based on your own needs.

FineBI is supported by a high-performance Spider engine to extract, calculate, and analyze a large volume of data with lightweight architecture.

FineBI also allows you to create highly interactive and intuitive dashboards with numerous charts, graphs, and maps, displaying multi-dimensional results.

Price:

FineBI is priced according to different license types. The price of FineBI Developer is $70/month, and the price of FineBI Viewer is $12/month. For other details, you can contact sales for consultation.

3. Microsoft Excel

Excel, a member of the Microsoft Office family, is a spreadsheet software widely used around the globe. Most data analysts are very familiar with Excel because of its simple operation and powerful data collection, storage, and analysis.

Key features:

Excel has basic features such as data calculation which is suitable for simple data analysis. Except for the rows and columns, you can also display your data through graphs and charts. 

For more advanced data analysis, Excel provides you with pivot tables, enabling you to analyze structured data through multiple dimensions quickly and effectively. 

However, it has limitations on rows and columns, making it not suitable for analyzing a large amount of data.

Price:

Excel is not a free tool. It is contained in Microsoft 365, which needs a monthly or yearly subscription. 

4. Power BI

Power BI, also developed by Microsoft, is a popular business intelligence tool among users familiar with Excel. It is friendly to general users without high-level analytics knowledge. Power BI enables your company to gain insights from data and then make informed decisions. 

Features:

As a Microsoft software, Power BI can integrate well with other Microsoft products such as Excel. If you are a heavy user of Excel, you will find a sense of familiarity in the process of using Power BI. 

Power BI offers you some charts to help you visualize your data and ease the process of data analysis. And you can also organize your dashboards by dragging and dropping components. 

Power BI is equipped with Microsoft AI, enabling you to find answers quickly even if you are using conversational language.

Price:

Power BI has a free version with limited features. For complete features, there are several subscription options for you to choose, ranging from $9.99/user/month to $4,995/capacity/month.

5. Tableau

Tableau is another famous data analysis tool specializing in data visualization. It is not a totally zero-coding software, so experienced data analysts will have a better learning and user experience than those with no basic code knowledge. 

Key features: 

Tableau supports connection to abundant databases. 

You can unleash your creativity in Tableau’s dashboards by using the programming language, such as C++, Java, Python, and R, and create impressive and intuitive charts to display your data for better data analysis. 

Also, it has excellent performance when handling massive data.

Price:

Compared to its competitor Power BI, Tableau has a higher price. It is more affordable for a large company than for a small or medium one.

6. Qlik

Qlik is a self-service data analysis platform that meets the modern business intelligence needs of people at all skill levels. 

Key features:

Qlik supports both cloud and on-premise deployment. Its core product Qlik Sense can connect data from numerous data sources. And it is equipped with AI and machine learning to provide AI-generated insight suggestions for you to analyze your data with higher efficiency. Another distinctive advantage is its hybrid cloud architecture, which supports combinations of public cloud, private cloud, and on-premise sites.

Price:

Qlik Sense Business offers you a 30-days free trial. Then, it costs $30/user/ month. And Qlik Sense Enterprise is a version for larger enterprises. You can contact sales to know the price of this version. 

7. Python

Python is a popular open-source programming language, firstly created for developing software or web pages, and now widely utilized in the field of data analysis. Python has a large group of users, ranging from beginners to experienced developers, because it is easy to learn and use.

Key features:

Data analysts use Python to realize the functions like data crawling, data cleaning, data modeling, data visualization, data mining, etc. 

Python enjoys strong portability. You don’t need to modify any code when you shift from one operating system to another. 

Price:

As for price, Python is free to use.

8. R

R language is also an excellent programming language focusing on statistical analysis and graphics. Due to its steep learning curve, it is more suitable for an analyst with programming experience.

Key features:

R is a very powerful and practical data analysis tool, especially for statistical analysis. It can realize most of the functions used in general data analysis and academic data analysis. In addition to the functions that Python can achieve above, R also supports statistical hypothesis testing, statistical modeling, data analysis report output, etc.

Price:

R is also an open-source programming language that provides you with a software environment for free.

9. RapidMiner

RapidMiner is a data science platform that supports the entire analytics lifecycle. It is designed for both no-coding domain experts and experienced data scientists in an enterprise, regardless of their skill level.

Key features:

RapidMiner covers nearly all the functions in a unified data science lifecycle, from initial data preparation to advanced predictive analytics.

Besides its own functions, RapidMiner can also be integrated with Python and R, or use multiple third-party packages in the RapidMiner Marketplace to extend its features to satisfy more analytics needs.

Price:

RapidMiner Studio is a free part of the RapidMiner platform but is limited to 10,000 rows and only one Logical Processor. 

The commercial version has three pricing options, ranging from $7,500/user/month to $54,000/user/month.

10. SAS Forecasting

SAS Forecast Server is an advanced data analytics tool that empowers your company with numerous reliable forecasts to make better plans for the future. You can easily utilize this software even though you have no code knowledge. But it doesn’t mean its functions are too simple. You can also access more advanced features through the SAS programming language.

Key features:

SAS Forecast Server offers various forecasting features, including scalability and modeling, hierarchical forecast reconciliation, automatic forecasting, etc. The forecasting procedure is highly automatic without requiring manual operations. It will choose or generate the most appropriate forecasting models for your data and offer you a large volume of trustworthy forecasts.

Price:

SAS Forecast Server is a relatively expensive in the eye of data analysts. As for the detailed price, you need to sent a price inquiry in its official website.

11. KNIME

KNIME is short for the Konstanz Information Miner that offers an open-source data analytics platform for building data science workflows. Its graphical user interface allows you to create visual data analytics workflows even though you don’t have too many programming skills.

Key features:

Its integration capability is a noticeable feature that enables you to blend data from different sources into one single platform. With KNIME, you can build machine learning models for different usages through advanced algorithms. In addition, you can choose to use charts provided by KNIME or customize the charts according to your own needs to visualize your data.

Price: 

KNIME Analytics Platform is an analytics tool free of cost. 

12. Talend

Talend is a data integration tool that helps your company to make decisions based on healthy data. Although it is a java-based ETL tool, you don’t have to be a java expert to operate it because it has drag-and-drop operations unless you intend to customize the features.

Key features: 

Talend provides software and services in the field of data integration, data integrity and governance, Big data, and cloud storage. You can use Talend to effectively and accurately integrate data from diverse data sources. Also, its capability of data integrity and governance automatically checks the data quality to ensure the data health on your cloud as well as on-premise systems.

Price:

Talend has a free, open-source version and a charged commercial version.

13. Apache Spark

Apache Spark is an open-source data analytics tool that is professional in the large-scale data processing. If you have some basic knowledge about common programming languages such as Python and R, Apache Spark is not difficult to learn.

Key features:

Apache Spark has several libraries, including Mlib for machine learning, Spark Streaming for streaming analysis, Spark SQL for working with structured and semi-structured data, and Spark GrapX for graph processing. Apache Spark also supports access to multiple sources. In addition, it can run much faster than Hadoop because it utilizes random access memory(RAM), which improves the efficiency of dealing with large-scale data.

Price:

Apache Spark is free to use.

14. Google Data Studio

Google data studio is a popular data analysis tool used for data visualization. It is especially suitable for those who intend to better understand and analyze Google data because of its seamless integration with other Google products, including Google Analytics, Google Ads, Google Sheets, etc.

Key features:

In addition to the Google applications, Google Data Studio also supports connecting to database platforms such as Amazon Redshift and MySQL. Another powerful feature that you can not miss is the data dashboarding and visualization capability. You can create interactive dashboards and detailed reports to analyze your data better.

Price:

Google Data Studio is an entirely free tool.

15. Sisense

Sisense is a business intelligence tool that enables you to analyze big data and get AI-driven insights. 

Key features:

Sisense has more than 100 data connectors, such as Apache Spark mentioned above and Azure products, to ensure that you can take full advantage of your data. 

Sisense also offers you a drag-and-drop user interface, allowing you to create customized dashboards easily and quickly. Its interactive visualizations enable you to analyze your data more intuitively and deeply. 

It also has other features like forecasting and natural language query with the help of Actionable Intelligence. 

Price:

Sisense offers you a free trial with full functions. It also has customized solutions based on your company’s needs and budget.

Conclusion

We have introduced 15 popular data analysis tools so far. If you have read this entire introduction, I believe you have a certain understanding of these data analysis software, including their product positioning, target users, main functions, and prices.

Then it is your turn to choose the most suitable one based on the features you want and the price you expect. Personally, I am more accustomed to using FineReport because I can use all the functions I need for free.

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