Tableau, Alteryx, and Python are among the best data science programs available to businesses who want to be data-driven and strategic. All three business intelligence software programs can help businesses ask and answer questions faster. They also help businesses use their own information to make better decisions. Although there is some overlap in capabilities, each business intelligence tool has unique strengths and weaknesses.
Tableau is a data visualization tool. It is most often used to help businesses see and understand their data so they can ask more intelligent questions or develop deep insights. Among the many reasons why businesses choose Tableau are the two most common – Tableau’s ability to display data in an easy to understand format and its easy-to-use interface which allows non-technical people to create their own reports. Due to its ease of implementation and use, Tableau is often the first business intelligence software tool a business will implement when beginning the journey to become more data-driven.
Like Tableau, Alteryx is a visual analytics tool used by businesses interested in self-serve analytics and empowering users to ask and answer their own questions. Alteryx can do machine learning really well, but where Alteryx really shines is in the area of data blending. Tableau can do some simple data blending, but once your business finds itself constrained by its limits, its time to add Alteryx to the mix. Now, you might be wondering, why not just start with Alteryx? The answer is simple. Although Alteryx can masterfully blend complex data sets from many disparate sources, it is not great at visualizations. Alteryx and Tableau work better together.
The biggest difference between Python and Alteryx or Tableau is that Python is a programming language. Tableau and Alteryx are visual analytics tools. Users do not need to be able to write code to use Tableau or Alteryx. Adding Python to a company’s business intelligence system will require users to be able to write code. Granted, Python was developed to be much simpler than other coding languages and it is possible to use Conda packages to rapidly expand the capabilities of your business intelligence software, but it is still code. Python is extremely good at machine learning (better than Alteryx), and excels at automation. It can help with any API-driven task and can be used to support server administration.
Think of Tableau, Alteryx, and Python as a progression. If your business is just getting started with data science, Tableau is the place to start. Once your users have stretched the limits of Tableau or need to blend data more efficiently, add Alteryx. Finally, once you’re ready to dive into machine learning, API connections, and automation, it’s time to get started with Python.
Tableau, Alteryx, and Python are all capable of helping your business analysts develop independence from IT and allow self-serve data analytics to speed up the decision-making process. If you’re not sure how your business should get started of if it is the right time for you to take the next step in your data science journey, give us a call. We’re here to help.