Data analysis is an important process in making business-related decisions. This process is defined as transforming, cleaning, and modeling data to find useful information for business decision making. For the smooth running of the data analysis process, you need data analysis tools. Data analysis tools are tools that will help you read, process and manage data. In 2023, there are some of the best data analysis tools you can use. Anything?
WHAT ARE DATA ANALYSIS TOOLS?
Data analysis tools are tools that will help you process data to make business decisions. This tool can be in the form of applications and software used by a data analyst to develop and carry out the analysis process. As mentioned earlier, the results of data analysis play an important role in making business decisions. The decision, of course, must be the best and most efficient in order to reduce costs while maximizing profits.
TOP 7 BEST DATA ANALYSIS TOOLS
In 2023, there are a number of popular data analysis tools used by data analysts to process data. Here are recommendations for the best data analysis tools that you can use.
1. APACHE PARK
Apache Park includes data analysis tools designed for researchers, developers, and data scientists who deal with big data on a daily basis . Apache Park is perfect for streaming and batch data .
This one data analysis tool can access multiple data sources and runs on multiple platforms , including Apache Mesos, Hadoop, or in the cloud. Large companies that already use Apache Park as their data analysis tool are Uber, Slack, and Shopify.
2. DATAPINE
If you are a beginner in data analysis, then Datapine is one of the best recommendations for data processing tools. The features of this data analysis tool are quite simple, yet powerful for both novice and advanced users. Datapine is equipped with an advanced SQL mode which helps advanced users create their own queries . Datapine's hallmarks are simplicity and speed.
3. POWER BI
Available in three versions, namely Desktop, Pro, and Premium, Power BI enables data analysts to visualize data connected to multiple sources and share the results with all members of the organization. With Power BI, you can bring your data to life with live dashboards and reports. Integrated with other applications, including Microsoft Excel, data analysis with Power BI is faster and without significant obstacles.
4. LOOKER
Cloud- based , Looker's data analysis tools provide an easy-to-use, intuitive drag-and-drop interface. This data analysis tool's multi -cloud strategy supports the use of multiple data sources and deployment methods. Looker that easily connects to multiple databases also offers data analytics and management, advanced visualization capabilities, and business intelligence.
5. SAS
Next is SAS which is used for business intelligence, data management, to predictive analysis . This data analysis tool is already used by large companies such as Netflix, Twitter, Google and Facebook in their daily operations. Visual Analytics SAS software is a powerful tool for interactive dashboards, business intelligence, reports, self-serve analytics, intelligent visualization, and text analytics.
6. R
R is a data analysis tool that has been used by large and well-known companies, from Facebook to Google to Twitter. One of these data analysis tools is indeed more often used for statistical analysis, big data, and machine learning. R is a good language in terms of syntax and consistency although using this tool means you need some coding knowledge.
7. PYTHON
Python is the fastest growing data analysis tool today. Originally designed as an object-oriented programming language for software and web development, Python is now a data analysis tool with a collection of friendly libraries for all aspects of scientific computing. This data analysis tool is free and easy to learn. With Python, you can perform advanced data manipulation and numerical analysis using data frames.
CONCLUSION
Those were some recommendations for data analysis tools that you can use to process and analyze data. Each data analysis tool certainly has its own advantages and disadvantages that you can adapt to your business needs.
To be able to use data analysis tools, of course you have to understand how these tools work and how to process data. Interested in data processing? You can take data science classes at Algorithm Data Science School . There are also training and business consulting services related to data science for you!
Reference
- Simplilearn, Top 10 Data Analysis Tools for 2023
- Hackr, 7 Top Data Analytics Tools to Use in 2023
- Guru99, What is Data Analysis?