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7 Leading Data Analysis Tools For Businesses Today

TOP 7 LEADING DATA ANALYTICS TOOLS TODAY: 

Python  

SAS 

Microsoft Excel  

Microsoft Power BI 

Tableau 

Apache Spark 

Python

  • Python was originally designed as an object-oriented programming language for software and web development and later advanced for data science. Python is one of the fastest growing programming languages available today. 
  • It is a powerful data analysis tool and has a friendly library for any aspect of scientific computing. 
  • Python has a vast developer community to support and is the most widely used language. 
  • The top companies using python are: Spotify, Netflix, NASA, Google and CERN and many others. 
TOP 7 LEADING DATA ANALYTICS TOOLS. source nois.vn

R

  • R is the leading programming language for statistical modeling, visualization and data analysis. It is used mainly by statisticians for statistical analysis, big data and machine learning. 
  • R is a free, open-source programming language and there are many improvements to it in the form of user text packages. 
  • R is used by Facebook (behavior analysis), Google (ad efficiency, economic forecasting), Twitter, Uber. 
TOP 7 LEADING DATA ANALYTICS TOOLS. source nois.vn
TOP 7 LEADING DATA ANALYTICS TOOLS. source nois.vn

SAS

  • SAS is a widely used statistical software suite for BI (Business Intelligence), data management and predictive analytics. 
  • SAS is proprietary software, and companies need to pay for it and need to have programming knowledge.  
  • SAS’s Visual Analytics software is a powerful tool for interactive dashboards, reports, BI, self-service analysis, text analysis and intelligent visualization. 
  • SAS is widely used in the pharmaceutical, BI and weather forecasting industries. Companies using SAS are: Google, Facebook, Netflix, Twitter,… 
TOP 7 LEADING DATA ANALYTICS TOOLS. source nois.vn
TOP 7 LEADING DATA ANALYTICS TOOLS. source nois.vn

Microsoft Excel

  • Excel is a spreadsheet and a simple yet powerful tool for data collection and analysis. 
  • Excel is not free; it’s part of the Microsoft Office suite of programs. 
  • Excel does not need a user interface to import data; you can get started right away. It is available, widely used and easy to learn and start data analysis. 
  • Excel provides a variety of tools for performing statistical analysis of data. Charts and graphs in Excel allow for clear interpretation and visualization of your data, making decision making easy to understand. 
  • Excel is used by over 750 million users worldwide. 
TOP 7 LEADING DATA ANALYTICS TOOLS. source nois.vn
TOP 7 LEADING DATA ANALYTICS TOOLS. source nois.vn

Microsoft Power BI

  • Power BI is another powerful Microsoft business analytics solution. 
  • Power BI comes in three versions – Desktop, Pro and Premium. Desktop versions are free for users; however, Pro and Premium are priced versions. 
  • You can access data from multiple data sources and share results across the organization. 
  • With Power BI, data is visually appealing, and easily interacted with dashboards and live reports. 
  • Power BI integrates with other tools, including Microsoft Excel, so you can accelerate quickly and work seamlessly with your existing solutions. 
  • Power BI has recently introduced solutions such as Azure + Power BI and Office 365 + Power BI to help businesses use data analytics, data connectivity, and data protection across different Office platforms. 
  • Leading companies using Power BI are Nestle, Tenneco, Ecolab and many others. 
TOP 7 LEADING DATA ANALYTICS TOOLS. source nois.vn
TOP 7 LEADING DATA ANALYTICS TOOLS. source nois.vn

Tableau

  • Tableau is a BI (Business Intelligence) tool developed for data analysts where people can visualize, analyze and understand their data. 
  • Tableau is not free and prices vary depending on different data needs. 
  • Tableau offers a fast analysis system; it can access any type of data from spreadsheets, databases, Hadoop, and data stored in the cloud. 
  • Leading companies using Tableau are Amazon, Citibank, Barclays, LinkedIn and more. 
TOP 7 LEADING DATA ANALYTICS TOOLS. source nois.vn
TOP 7 LEADING DATA ANALYTICS TOOLS. source nois.vn

Apache Spark

  • Spark is an integrated analytics tool for big data processing designed for developers, researchers and data scientists. 
  • Open-source and a high-performance and well-functioning tool for batch and streaming data. 
  • Learning Spark is easy and you can also use it interactively from the Scala, Python, R, and SQL classes. 
  • Spark can run on any platform such as Hadoop, Apache Mesos, standalone or in the cloud. It can access diverse data sources. 
  • Uber, Slack, Shopify, and more use Apache Spark to analyze data. 
TOP 7 LEADING DATA ANALYTICS TOOLS. source nois.vn
TOP 7 LEADING DATA ANALYTICS TOOLS. source nois.vn

WHICH DATA ANALYSIS TOOLS FITS THE SIZE OF YOUR BUSINESS?

After all, if your business has rich human resources or a team dedicated to data, the use of programming languages brings many benefits to the business. However, if your company is not qualified for human resources as well as expertise, tools that need background knowledge of programming languages such as Python, R or SAS, Spark can be time-consuming as well as costly to use. Excel is the most accessible and popular tool; however, as the database grows larger, managing data in excel might cause lots of difficulties: difficult to control, difficult to hand over and share, as well as low security. If your company is moderate in size, analytics tools like Tableau or Power BI are probably the most affordable option that can optimize your business’ data analysis. Although Tableau could possess powerful analytical capabilities and analyze huge amount of data, the cost is relatively expensive. With the same powerful analytics capabilities as Tableau, being consistently improved by Microsoft and, above all, at a more affordable cost, Power BI seems to be the first choice of business analysts today.  

CONCLUSION

Data analysis tools play an important role in supporting decision-making progress. The tools listed above have unique features with both advantages and disadvantages. Depending on the size and needs of the business, you can choose the most suitable solution for the business.  

When choosing, you may consider the following questions: 

  • How many functions does your business need? 
  • Is the amount of data to be processed small, moderate, or large? 
  • What is the budget of your business for analyzing the data? 

Choosing the right data analysis tool for your business requires time researching and understanding the size and needs of your business. Although these tools all bring value and many benefits to data analysis, many enterprises still do not know where to start or they need quick solutions, saving time and manpower, cooperating with a third party having technical expertise and technical consulting is an option worth considering. Highly data-specialized companies can help businesses find the most suitable data analysis tools and personalize them as well as combine them with your pre-existing business systems.  

  • Python  
  • SAS 
  • Microsoft Excel  
  • Microsoft Power BI 
  • Tableau 
  • Apache Spark 
  • Andy Tran

    Managing Director @ NOIS Co., Ltd. | Software Development, Smart Factory Solutions, Azure Cloud and Generative AI

    View all posts
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