Is Tableau worth learning?

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Table of Contents

At first, what is Tableau? It’s fascinating to find out what Tableau entails. A tableau is a software that is a visual analytics platform transforming how we use data to solve problems, empowering people and organizations to make the most data; thus, the concept of being data-driven comes in.
This platform makes it easier for people to explore and manage data faster and share insights that can change businesses and the world at a more comprehensive prospect. Tableau host everybody despite your profession, i.e., analyst, scientist, accountants, doctors, teachers, students, executive or business users.
Tableau is the most robust, secure, and flexible end-to-end analytics platform. Tableau was founded in 2003 due to a computer science project at Stanford with a well-laid objective of improving, analyzing, and making data more accessible to people through visualization. Tableau records the results into numerous expressive and vivid outlines to get better perception and awareness.
Co-founders Chris Stolte, Pat Hanrahan, and Christian Chabot developed and branded Tableau’s foundational technology, VizQL –which optically expresses data by translating rag–and–drop actions into data queries through an innate interface. Tableau has continuously invested in research and development at a consummate pace, developing solutions to help anyone working with data get answers faster and detect unforeseen, precipitous insights.
Salesforce acquired Tableau in 2019, but the mission remains undisputed, which is-empowering people to drive change with data. Thus, I conjure that data has limitless potential to transform businesses and the world –as long as people are empowered to use it.

Is Tableau worth learning for career
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10 Reasons why Tableau is worth it

Why Tableau? Flow along to get the hidden, precise information about the worthiness of this software.

  1. Remarkable Visualization Capabilities. This software’s visualization is superior to what the competitors offer; thus, no software can compete with Tableau with illustration and design quality. The results are available in several types of graphics also more comfortable to use in carrying out business affairs.
  2. Ease of use due to the user-friendly interface allows latent users to utilize the basic app’s functionality to the fullest.
  3. High Performance. Tableau is robust and reliable due to faster operation, even on extensive data.
  4. Multiple Data Source Connections since the software supports establishing connections with many data sources, improving data analytics and quality.
  5. Thriving Community and Forum due to diverse skills and expertise since it hosts a larger community of over millions plus worldwide users.
  6. Mobile Friendliness makes Tableau more flexible and mobile, keeping data on track and under surveillance wherever you are.
  7. First ultimate Skill for Data Science which acts as a great entry point into the World of Data.
  8. Leverage the Power of Data. Tableau helps you optimize the interrogation performance and connect to the database view easily due to inbuilt extract, transform, and loading features.
  9. No need for Coding. Every functionality in this software is subservient by drag and drop.
  10. Applicable to any Business. Tableau has varied thus very utilizable in any field of interest.

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10 reasons why Tableau is not worth it

Are there disputes or drawbacks in Tableau? Yes, I agree to challenge the credibility. Tableau is not left out. Find below the drawbacks of Tableau.

  1. High Costs. The license is quite expensive for most small to medium companies since it also requires proper deployment, implementation, maintenance, and staff training, which come at a substantial price.
  2. Inflexible pricing. Tableau’s sales model requires clients to purchase the extended license at the start, which is unfair to companies that prefer buying a set of a preferred feature at a given time.
  3. Low Customer Support Services, i.e., improper after-sale maintenance forcing customers to solve their issues independently, thus dissatisfaction.
  4. Security issues. Tableau fails to provide centralized data–level security, thus exposure to hackers.
  5. Poor BI Capabilities. It lacks functionality to a full-fledged business intelligence and also a limited capacity for result sharing.
  6. Poor Versioning since most versions do not support software rolling back.
  7. Embedment Issues. Integrating into the company’s product is a real challenge from both financial and technical points of view.
  8. Time and Resource Intensive Staff Training. Knowing all the tool’s capabilities without comprehensive employee training is impossible; thus, it needs to get immense into the tool’s functionality.
  9. Inadequate IT Assistance for Proper Use. Tableau has not developed the IT department responsible for configuration and basic functionality.
  10. Lack of Data Modelling and Data dictionary capabilities for Data Analysts.

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Tableau Certification

Skill up and stand out! Getting Tableau certification is the best thing. What you have to do is to choose the one that suits you. The following are some of Tableau’s certifications for your career;

For Tableau Desktop:

  • Desktop Specialist
  • Desktop Certified Associate
  • Desktop Certified Professional

For Tableau Server:

  • Server Certified Associate 
  • Server Certified Professional

For the First course:

  • It is advised to polish your Tableau skills, fundamental knowledge of Tableau Desktop, and implementing Tableau’s prior experience.
  • If you are to proceed with an exam, you should perform activities like; connecting data, simplifying and organizing, Chart and graph creation, Analytics, Dashboards, Mapping, calculations, etc.

The latter course offers:

  • The candidate to become a Tableau Administrator or Consultant
  • Must be conversant with skills like; Administering Tableau server, Installing and configuration, Versions and topology of Tableau Server, Troubleshooting the errors, and upgrading the system.

Choose a better career path; thus, opt for one course. I wish you the best as you undertake a course.

Is Tableau easy to Learn?

Actually, yes, Tableau is easy to learn but somehow challenging to master and very instinctual to use for a customer. You have to majorly tailor yourself into the course with various resources like; eLearning, in-person, and virtual courses.

If you are new to Tableau click this affiliate link to learn more. 

The best way to speed up on skills, tips, and tricks quickly is through Tableau training. You are set to be active and lively, managed and updated on Tableau’s training organization, comprehensive and instructor-led classes for certification. 

You can travel and look for a class in a city near one of Tableau’s conferences or instead learn from the comfort of your own home by joining live, interactive virtual training.

Your relationship with data will differ from others since learning turns us from newbies to data experts. You play a significant role by choosing the way to use Tableau, thus influence by getting the right professional advancement.

Tableau’s role-based licenses allow for the differences in the way people interact with data and therefore have different training pieces to address and bring on board the skills needed for each. Consider your training path, i.e., design, cleaning, and curation of data sources that others will use to analyze data or create visualizations and dashboards with which others will interact with.

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Learning Tableau is fun because there is a wide range of specialization one can learn apart from general ideas, which are paramount.

I concur with this statement that learning Tableau is tranquil. Thus the need for us knows thy selves before venturing into a particular course. All these require passion and the ability to integrate what you learn. Your level of creativity well captures full involvement into Tableau, and the more impactful your experiences and innovative skills are 

Join the world’s most passionate community because Tableau offers many ways to connect with peers and experts. Take advantage of learning opportunities by joining the local Tableau User Group, browsing forums, and exploring Tableau Public.

Tableau vs Python

What is the correlation between Tableau and Python? Curious? Let’s finally find what Tableau entails and similarly what Python entails.

Tableau is a business intelligence and data visualization tool, while Python is a programming language that supports various statistical and machine training techniques. When Tableau’s data visualization and Python’s machine learning capabilities are combined, the developers will rapidly create advanced data analytics applications for various business applications.

Chris Stolte and Christian Chabot in2003 developed Tableau, while Python was designed by Guido Van Rossum and first published in 1991.

Tableau is used to explore and analyze relational databases and data, extract a large amount of data, and keeps and regains from its exclusive in-memory at the engine. At the same time, Python consists of constructs with which it’s easy to execute explicit programming on small and large scales and known for its code readability.

Tableau helps create great user interfaces, while Python provides a high level of graphics interface for designing platforms identifying patterns, and emphasizing key elements.

Software developers like Tableau because of its mapping functionality due to the ease of narrating longitudes and latitudes, while they prefer Python because of its clean and short syntax.

Tableau helps self-service Business Intelligence, while Python is an open-source portable language supported by a substantial standard library.

Tableau has very minimal programming skills, while Python has multiple graphing libraries.

Tableau can consume various file types instantly, while Python is very good at dealing with streaming data and challenging to do out-of-box data visuals quickly.

Tableau can connect to various types of databases like relational databases, cloud, flat files, and spreadsheets, while in Python, it’s easy to parse data of obscure types.

With Tableau, you can collect data from various places irrespective of the databases, while Python has an ecosystem of modules and tools to collect data from multiple sources.

Tableau is known for its out-of-box connection potential, while Python, no other software, can vie with it.

Indeed Tableau is much different from Python. 

Tableau Training

Work made easy when you need Tableau training. There’s no second thought of any better place than PST Analytics for Tableau training. The key strength to outdo Tableau’s contents and problems is the practical approach you give. You need to find the best tutor to take you through Tableau, which will look like crossing a river through the bridge.

Tableau training will be worth your time and money when you get someone to take you from scratch to a confidence level that you can easily understand. What interests PST analytics is that your doubts are most welcome even after completing the course. Any day-to-day challenges in Tableau need to be reported to the concerned personal training you. By doing this, learning will be more and more sturdy and better.

Mostly, the online pieces of training will take you through Tableau by the following steps-

  1. Getting started with Tableau whereby you will understand Tableau’s fundamental concepts and features, how to connect to data sources, use Tableau’s drag and drop interface, and create captivating visualizations.
  2. Building and customizing Visualizations. You will learn how to slice and dice data with filters, create new columns using your calculated fields, and aggregate dimensions and measures in a view. You will be working with education, social, and infrastructure data.
  3. You are digging deeper—this where you learn how to visualize geographic data and plot data onto a map visualization. You will learn how to work with dates in Tableau and explore how data changes with time. You also learn how to add references, trends, and forecasting lines based on your views. This will enable you to do all exploring health statistics worldwide.
  4. You are presenting your data. You will learn best practices for formatting and presenting data to tell data-driven stories. You will also learn how to create dashboards and use them to share critical insights and support your team’s aspirations. Stock price and foreign exchange will also use.

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How long does it take to learn Tableau?

The longevity and time duration for learning Tableau depends on several factors. For instance, the input time one puts into learning the course, the ability to learn faster, and prior knowledge are essential, i.e., computer science.

The following is a general timeline for an ideal learning curve:

  1. DAYS: it will take you a few days to produce something with your data. Its conceptual shift to work with a calculated field instead of directly manipulating a cell of data like Excel.

 

  1. MONTHS: By then, look at a bunch of tutorials provided by Tableau to answer specific questions. For example, a tutorial on how to produce a Top N. Through this, you’ll be able to produce your own then develop them systematically.

 

  1. A YEAR: After a year of a year, you should have seen enough other visualizations and done enough online training to come up with something unique. There should be a general mastery of the basics and could do stuff like advanced table calculations and custom graphics.

 

  1. TO INFINITY: To infinity and beyond is where you start” training” other people. This will add much understanding to this course and give you a gate pass of being an expert. At this stage, you have acquired the relevant skills thus more knowledgeable with the software.

 

Why Learn Tableau?

Indeed Tableau is an excellent skill in business intelligence as it assists in radical decision-making. Most organizations rely on data visualization; thus, Tableau is worth it because it’s a great data visualization tool.

 Tableau is a handy tool to create interactive data visualizations very swiftly. As the marketing–leading choice for modern business intelligence, the Tableau platform is known for taking any data from almost any system and turning it into litigable insights with speed and ease. 

Customer success is paramount in Tableau as it’s a trusted leader in analytics. The customers do say, “the community will not allow you to fail. ” The products are designed to [put the user first since 

Tableau believes data analysis should be about asking questions and not about learning software. Due to best practices, Tableau enables limitless visual data exploration without interrupting the flow of analysis.

It meets the need of all of its users regardless of their skill set due to the role-based licensing uncovering of insights faster by the augmented analytics innovations help anyone from any field.

The software has enabled people to learn faster since it’s an integrated platform that is easier to start and scale.

Tableau Course

The course entails a broad scope of knowledge responsible for full equipment and relevance of the software. There is a 100% assurance for degrees and certification on every course enrolled for.

There is no restriction or procedure of choosing a Tableau course; what is most important is your interest areas and desire to study the course entirely.

Some of Tableau top 10 courses are listed below:

  • Data Visualization. Entails how to create powerful business intelligence reports, assess the quality of the data, and perform exploratory analysis. Offered at the University of California, Davis.
  • Advanced Business Analytics. Turning data into value and driving business process change by identifying and analyzing key metrics in 4 industry-relevant courses. Offered at the University of Colorado Boulder.
  • Data mining. Involves solving real-world data mining challenges by analyzing text, discovering patterns, and Visualizing data. Available at the University of Illinois at Urban –Champaign.
  • Creation of dashboards and storytelling using Tableau. This helps discover how to use the story points. Available at University of California, Davis.
  • Visualizing Citibike Trips with Tableau. It involves the creation of data visualizations and publishing of data visualizations with the dashboard in Tableau. Coursera Project Network.
  • Fundamentals of Visualization with Tableau. It helps understand and better see data. They are offered at California University, Davis.
  • Tableau Public for Project Management and Beyond. Entails learning of basics of Tableau Public, building Visualizations, Creating and sharing of dashboards. It is done at Coursera Project Network                     
  • Excel to MySQL: Analytic Techniques for Business. Involves turning data into value and driving business process change by identifying and analyzing key metrics in 4 industries –relevant courses. They are offered at Duke University.
  • Data Visualization and Communication with Tableau One of the most remarkable skills is communicating practical implications of quantitative analyses to any audience member, even the most sophisticated. They are offered at Duke University.
  • Data Visualizations with Tableau Project. This is where you will follow your own interests to create a portfolio worthy single-frame viz, or multi-frame data story shared on Tableau Public—offered at the University of California.

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10 reasons why Tableau is worth it against 10 reasons why Tableau is not worth it

Reasons why Tableau is not  worth it

Reasons why Tableau is  worth it

i)                     High cost making it difficult to be employed by medium-sized businesses.

High Performance thus time conservative and quality output of data

ii)                   Inflexible pricing thus unreliable in terms of profitability

Ease of use and implementation hence can be employed by anybody without any training

iii)                 Poor After-Sales Support hence dissatisfaction of the users thus tainted public image

Multiple Data source Connections thus making it efficient and reliable to use

iv)                 Security issues making it prone to access by hackers who steal essential and confidential information

Thriving community and Forum hence sharing of ideas and experiences which is vital in developments of the users

v)                   Poor BI Capabilities and cannot also work with uncleaned data

Mobile Support and Responsive Dashboard making it mobile thus one can monitor any activity any time everywhere

vi)                 Poor versioning control and collaboration when building data logics and dashboards

Tableau can handle large amounts of data making it dependable where there’s a large amount of data.

vii)                Embedment Issues thus challenges  instability and connectivity

Use of other scripting languages in Tableau making it reliable despite the language differences

viii)              Inadequate IT Assistance for proper use

Quick to create Interactive Visualizations thus time conscious and productive

ix)                  Time and Resource –Intensive staff Training

Allow for scheduling or notification of reports, i.e. vie email thus easy awareness of every activity taking place

x)                   Lack of data modelling and data dictionary capabilities for Data Analysts

Supports data consolidation from multiple sources

Conclusion

Tableau as the software provides a feature that can transform your data into interactive dashboards. It encompasses excellent analysis and storytelling; the data visualization removes noise from the background to focus only on essentials. This field is rich in potential applications in diverse disciplines due to the awareness of its practical and ethical complexities.

Tableau’s future is error-free software, thus making it the most preferred software to be employed. The recent developments in Tableau are a significant step in the transformation cycle, allowing for luminous software. The steps you need to undertake before using Tableau understand your goals and needs.

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Luis Gillman
Luis Gillman

Hi, I Am Luis Gillman CA (SA), ACMA
I am a Chartered Accountant (SA) and CIMA (SA) and author of Due Diligence: A strategic and Financial Approach.

The book was published by Lexis Nexis on 2001. In 2010, I wrote the second edition. Much of this website is derived from these two books.

In addition I have published an article entitled the Link Between Due Diligence and Valautions.

Disclaimer: Whilst every effort has been made to ensure that the information published on this website is accurate, the author and owners of this website take no responsibility  for any loss or damage suffered as a result of relience upon the information contained therein.  Furthermore the bulk of the information is derived from information in 2018 and use therefore is at your on risk. In addition you should consult professional advice if required.