Being a data scientist requires constant learning. Between picking up new programming languages and the hottest new self-service program, prioritizing your next skill can seem intimidating. However, there is one program that deserves a place at the top of your list.
Tableau is worth learning because it is a business intelligence mainstay. Its value comes from the ability to create data visualizations without coding. Furthermore, its visualizations are easy to read and highly interactive. Knowing Tableau opens job opportunities and adds value to your skillset.
Read on to learn how Tableau works and what makes it worth adding to your toolbox.
Important Sidenote: We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and identified 6 proven steps to follow for becoming a data scientist. Read my article: ‘6 Proven Steps To Becoming a Data Scientist [Complete Guide] for in-depth findings and recommendations! – This is perhaps the most comprehensive article on the subject you will find on the internet!
Table of Contents
What is Tableau?
Three data scientists, Pat Hanrahan, Christian Chabot, and Chris Stolte, created the Tableau software back in 2003 at Stanford University. As the field of data science expanded over the past two decades, Tableau’s popularity grew with it. The software is one of the most popular data visualization programs out there.
Furthermore, the program exists on many platforms, including Windows, macOS, mobile devices, and the cloud. So what is it, and how does it work?
The Tableau platform is a data analytics program used for business management and intelligence. Compared to other data analytics programs that require a programming background, Tableau provides a user-friendly interface that anyone can use.
Unlike other programs, which need the user to learn a new programming language, Tableau runs its programming language in the background. But we’ll discuss that more later.
While primarily a data visualization software, the Tableau software suite has data preparation abilities. Tableau can connect and prepare your data, no matter the size or file format. Furthermore, the program translates data files, whether cloud-based, on-premises, or flat. Tableau features hybrid connectivity, which covers live data analysis and in-memory data analysis from encrypted sources.
The Tableau suite offers a smooth visual interpretation of data. This benefit helps developers and viewers understand data more efficiently. Tableau provides a seamless environment that is more interactive than the normal stop-and-go process of data reporting. With the possibility to alter visualizations to highlight different insights, Tableau saves time that would be spent re-examining and creating new data visualizations from scratch.
The visual interpretations of the desktop app provide part of Tableau’s interactivity. This feature is very significant for encouraging critical thinking and decision making driven by data.
Tableau Desktop gives users the agency to build their visualizations with drag-and-drop tools. Additionally, users can develop statistical modeling via AI technology with the click of a mouse. Lastly, users can ask questions about the data with natural language.
Secure sharing from an accessibility perspective is a priority of Tableau products. Tableau Server and Tableau Online both provide data sharing services on-premises and in the cloud. Additionally, Tableau Online takes out the extra work of managing data servers. For on-the-go analytics, Tableau also has a mobile app compatible with iOS and Android.
Tableau is not a one-size-fits-all product. The company goes the extra mile to provide role-specific licensing tailored to skill level and responsibilities:
- Creators assemble the analytical content. Their responsibilities include designing, cleaning, and curating data sources via dashboards and visual aids.
- Explorers can access the content made by creators, analyze that data, and create and share dashboards of their own (contingent on governed authoring).
- Viewers are the least hands-on party. This role can view and interact with data, with the ability to subscribe to updates and alerts.
What makes Tableau’s speed and accessibility possible? The answer is VizQL. VizQL, or Visual Language Query, is an offshoot of Structured Query Language. Although VizQL technically is a programming language, it runs automatically in the background of Tableau’s engine. Furthermore, the language it uses for queries is quite familiar to your average data analyst.
VizQL contains the standard commands found in most relational data management languages, like ‘where,’ ‘group by,’ and ‘order by.’ However, VizQL stands out from the pack by providing syntax that instructs how to organize the data into a table with rows and columns. This syntax makes visually presenting data as simple as dragging and dropping data from SQL. The accessibility in Tableau’s features is due to the seamless qualities of VizQL.
5 Reasons To Learn Tableau
As you can see, Tableau boasts a host of benefits. But is it worth learning if you already have a go-to visualization program, like R Shiny? Absolutely! Tableau has a stellar reputation and is very quick to learn. If you need more proof, check out our reasons for learning Tableau below:
Tableau is Universally Used
Believe it or not, Tableau was not very popular among data scientists upon inception. However, once business intelligence professionals recognized its usefulness in communicating data science among various fields, the company gained traction. Once Tableau went public on the stock market in 2013, the company raised $250 million. The rest is history.
So, where are we going with this? This astounding IPO is a testament to how widely used the Tableau software is. Need more proof? The software is a consistent leader in Gartner’s magic quadrant for business intelligence and data analytics. Furthermore, the product gets used in about 150 countries. In other words, there is a good chance the business you are working for or applying for uses Tableau.
Tableau is Available on Multiple Platforms
Tableau is not the only self-service business intelligence platform out there. For example, Power BI, a Microsoft service, has made a massive splash in the business intelligence industry and is arguably more comfortable to use. Unfortunately, it is not available to use on the macOS. If you are an analyst that relies on an Apple computer’s power and ease, this is a problem.
On the other hand, Tableau provides service on mobile devices, laptops, PCs, online, and Apple products. The macOS version of Tableau does not accommodate as many data sources. But as long as it works with the data your company uses, you will not notice the difference.
Tableau is a Valuable Data Science and Business Intelligence Tool
There is no denying it, Tableau is an exquisite business intelligence tool. Frankly, it does not substitute the extensive knowledge required of a data scientist. But that is not the point. Tableau’s value comes from its ability to translate data into tangible insights. It communicates data science to the data illiterate. When presenting to key executives, this ability is vital.
Saves Time
Since Tableau does not require coding, the data visualization process becomes much faster. But the efficiency does not stop there. Tableau visualizations are interactive, which means you can alter visualizations on-the-fly to highlight desired trends.
For example, what if you wanted to present multiple visualizations in a PowerPoint presentation to clients? If you did not have time to make numerous charts, you could follow the lead of data analyst Harry Ngo and take a few screenshots of a Tableau Highlight Table. Talk about quick and easy!
Increases Job Prospects
Tableau is not the only skill you need to score a data analysis job. However, incorporating Tableau into your toolbox will place you leaps and bounds ahead of the competition. One common step in a data analytics job application is an “Analysis and Presentation” task. In this instance, knowing Tableau will make your presentation pop with colorful and coherent visuals.
There are even jobs that specifically apply to Tableau users. For example, Tableau Consultants consult businesses using automated visualizations via Tableau Desktop, Tableau Server, and Tableau Online. In other words, you could make your Tableau knowledge into a job!
Author’s Recommendations: Top Data Science Resources To Consider
Before concluding this article, I wanted to share few top data science resources that I have personally vetted for you. I am confident that you can greatly benefit in your data science journey by considering one or more of these resources.
- DataCamp: If you are a beginner focused towards building the foundational skills in data science, there is no better platform than DataCamp. Under one membership umbrella, DataCamp gives you access to 335+ data science courses. There is absolutely no other platform that comes anywhere close to this. Hence, if building foundational data science skills is your goal: Click Here to Sign Up For DataCamp Today!
- IBM Data Science Professional Certificate: If you are looking for a data science credential that has strong industry recognition but does not involve too heavy of an effort: Click Here To Enroll Into The IBM Data Science Professional Certificate Program Today! (To learn more: Check out my full review of this certificate program here)
- MITx MicroMasters Program in Data Science: If you are at a more advanced stage in your data science journey and looking to take your skills to the next level, there is no Non-Degree program better than MIT MicroMasters. Click Here To Enroll Into The MIT MicroMasters Program Today! (To learn more: Check out my full review of the MIT MicroMasters program here)
- Roadmap To Becoming a Data Scientist: If you have decided to become a data science professional but not fully sure how to get started: read my article – 6 Proven Ways To Becoming a Data Scientist. In this article, I share my findings from interviewing 100+ data science professionals at top companies (including – Google, Meta, Amazon, etc.) and give you a full roadmap to becoming a data scientist.
Conclusion
In short, Tableau has a lot of worth in the business intelligence field. Therefore, if you are looking for a job in business intelligence or data analytics, Tableau is extremely valuable. Unlike other self-service programs that cater to specific operating systems, Tableau is available across numerous platforms.
Furthermore, the product gets used throughout the globe. However, you will most likely find the Tableau suite’s high quality and accessibility the most significant benefit.
BEFORE YOU GO: Don’t forget to check out my latest article – 6 Proven Steps To Becoming a Data Scientist [Complete Guide]. We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and created this comprehensive guide to help you land that perfect data science job.
Affiliate Disclosure: We participate in several affiliate programs and may be compensated if you make a purchase using our referral link, at no additional cost to you. You can, however, trust the integrity of our recommendation. Affiliate programs exist even for products that we are not recommending. We only choose to recommend you the products that we actually believe in.
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