Data visualization has gained massive popularity in recent years owing to the demand for data. In a business setup, these business intelligence tools can help in analyzing all the data and monitor performance to enhance growth for the firm, and productivity for the employees. With the world switching to digital means all together in the year that went by, data is now considered fuel for every small, medium, or big firm.
In such a scenario, what sounds better- a spreadsheet that mentions the date, time, sales, and profit OR a colorful, descriptive bar chart interactively explaining all the details? Our vote goes to the latter.
Tableau vs Power BI, it’s the clash. But which tool would be the best to create such visually appealing charts? And, which one would provide the required versatility to the user?
These are the questions that would cross anyone’s mind when planning to implement business intelligence in the system. It is well analyzed from the comparison of Tableau vs Power BI vs Python.
Let’s find out which of the top data visualization tools will be best suited to your business requirements.
An essential part of any business strategy, data visualization is the process of collecting data and transforming it into a meaningful visualization to support decision-making. These visualizations could be in the form of bar charts, maps, or anything that is visually appealing and interactive. They convey the information to the viewer by simply looking at them, whereas normally one needs to read spreadsheets or text reports to understand the data.
Talking of the best data visualization tools used by analysts in various industries according to their specifications and applications, they comprise Tableau, Power BI, and Python. All these software programs help businesses make decisions questions faster.
A tool that is used by data analysts, scientists, statisticians, and academicians to visualize data and get a clear opinion based on data analysis. It’s regarded as the best solution to transform the unprocessed set of data into an interactive format and doesn’t require the user to excel in any technical skills or coding.
As soon as Tableau is launched, one can make use of the built-in data connectors to connect to any database. The data can be easily extracted in its raw form and converted into a comprehensive representation to transform the way people use data for problem-solving.
Tableau services have been high in demand ever since its effect has been noticed on the growth of firms. For those firms that do not have an in-house tableau developer, the requirement is outsourced to a data science consulting firm.
Power BI from Microsoft is an exclusive collection of software services, apps, and connectors that are used to convert raw data into visually compelling insights. The tool allows connecting to a wide range of data resources from a basic Excel sheet to databases, and both cloud-based and on-premise apps.
Power BI services are mostly used by business analysts and data scientists, but at the same time allow the user base to vary from a beginner to a pro in handling it.
Power BI tool is widely recommended by industries where the creation of data models and reports for analysis is mandatory. The airline, healthcare, hospitality, and retail are a few to name.
Python is a dynamic, interpretive script programming language. Developed sometime during the early 1990s, this language supports major paradigms of today’s software development methods such as structured programming, OOP (object-oriented programming), and AOP (aspect-oriented programming). Due to the availability of powerful value-added packages for a chosen few applications, one can develop high-performance apps through Python.
Python program code is transparently translated by an interpreter into an intermediate code, the so-called byte code. Python interpreter is available for all common operating systems such as Mac OS, Windows, Linux, and others.
Top tech companies including Google opt for Python as their programming language as their in-house scripting language for the development of web applications.
As far as using it as a data visualization tool is concerned, Python offers multiple libraries in graphics that are packed with different features. Some of its top-notch graphing libraries that help in creating live and highly customized plots are Matplotlib, Ggplot, Seaborn, Plotly, and Pandas Visualization.
Python is preferred for data analysis of the highest levels, which is why it is also the most-sought programming language when developing data visualization software.
Both Power BI and Tableau often use Excel files as a source for raw data. While Tableau offers support for multiple data connectors including cloud platforms, online analytical processing, and big data, Power BI is capable of connecting to external sources including MySQL, third-party databases, Microsoft Azure, and online services like Salesforce and Google Analytics.
As far as Python is concerned, it’s a bit difficult to make visuals in a rapid manner as compared to the other two. However, if you are to deal with streaming data there’s nothing better than Python.
Tableau allows the creation of simple data models such as a single table or multiple tables with different combinations. It is mostly suited for the quick and easy representation of big data which helps in analyzing and resolving issues. Power BI, on the other hand, has its data models focused on ingestion and building relatively complex models.
Python is the best when it comes to handling streaming data. With its big user data, Python can easily help you find a package to parse the data collected by the user, even if it’s an obscure type.
The process of data discovery involves detecting patterns and oddity in data by visually navigating or applying guided advanced analytics. Both Tableau and Power BI allow the user to freely explore data without knowing the answer.
These business intelligence tools give the user the freedom to spot correlations and trends while digging down to understand what caused them to happen.
The core reason for using Python is the versatility it provides as a programming language, while also helping with data visualization and analytics.
Data discovery could be a bit tricky with Python if you do not have good programming skills or an IT team who can work around it. But what cannot be ignored for this tool is that Python has an ecosystem of modules and tools to collect data from multiple sources.
Visualizations are a great way to utilize data that’s indispensable. While working with Power BI users can choose numerous visualizations. In addition to that, you can also create visualization by asking questions in plain language.
Tableau supports the creation of baseline visualizations like heat maps, line charts, or scatter plots. It also allows the user to ask ‘what-if’ questions of the data, as well as the freedom to use any number of data points in their analysis.
Both Power BI and Tableau can integrate programming languages like Python to create interactive visualizations. They can also integrate APIs to enhance effectiveness in a particular project. An API is a set of defined routines like communication protocols and tools for building software.
Both Tableau and Power BI allow users to create customized dashboards. This is applicable in the form of charts, maps, and diagrams. The aesthetically pleasing dashboards also help in enhancing the user’s productivity. However, when it comes to embedding data, it can be a challenge doing it in real-time in Tableau as compared to Power BI.
For Python, Dash is something that was created as an open-source framework for building data visualization interfaces in the Python library. It may be simple to build and interactive for usage, but all-in-all Python’s visualization landscape is quite complex as compared to others.
Tableau and Power BI boast of interfaces that do not require prior knowledge or experience of coding to develop complex visualizations. Power BI’s interface is simple, easy to learn, and is often preferred by users as compared to Tableau.
In a situation where firms have cross-functional teams, separate tableau consultants are hired to help them work around it or the project may be outsourced to a tableau consulting firm.
Since Python is a programming language, only professionals or users with prior technical knowledge can use it up to its potential.
Because Power BI is built for a common user like anyone from any department with basic knowledge of Microsoft applications, and not necessarily for a data scientist or business analyst its interface revolves around the drag-and-drop feature.
Tableau, on the other hand, provides an excellent speed with options to optimize and enhance the progress of an operation.
Python is widely appreciated by software developers all over the world for its clean and short syntax.
Tableau has numerous products such as Tableau Server, Tableau Online, Desktop, Reader, Mobile, and Prep Builder which serve different purposes. Tableau Public is free software that anyone can connect a spreadsheet to or a file and create interactive data visualizations for the web. Its subscription offerings are tailored as per the user’s needs.
Tableau as a BI tool can handle a huge volume of data without compromising on its performance. Power BI on the other hand, is capable of handling only a limited amount of data. To use a huge volume of data in Power BI, the user needs to upgrade to Power BI Premium.
Tableau Creator is designed for analysts who work individually and users who have a lot of work around data. The plan costs $70 per month for a single user and is billed annually.
Power BI is relatively a more affordable option when it comes to using Business Intelligence tools. It provides a robust trial period of 60 days free of charge against Tableau’s 14 days free trial. Power BI starts at $9.99 per user per month, while Tableau Explorer is at $35.
Python, on the other hand, wins the case here where the battle was Tableau vs Power BI. It is an open-source programming language that is freely available for everyone to use. You can simply download and install Python from their official website on your computer and it’s ready to use.
Tableau and Power BI are business intelligence tools while Python is a programming language that supports a variety of analytical and machine learning techniques.
Using a BI tool depends greatly on the requirements of the business or individual. Say, if a business makes use of Microsoft tools like SSMS, SSIS, etc, for their operations, they’ll prefer Power BI.
Small businesses with limited financial resources who seek an affordable solution to BI tools can go with Power BI. On the other hand, enterprises with decent capital and manpower to support them with data analytics as a priority will be better off with Tableau.