Review: Data Visualization with Tableau Specialization By UC Davis

Almost any analytics field is a great way to kick off a successful career in tech. Data drives so much of the tech world (and corporate too, but that's a story for another time), and having an analytics background is a huge leg-up over other applicants.

Arguably one of the biggest concepts in analytics is how to effectively visualize and present data for technical and non-technical stakeholders alike. As an aspiring analyst, or someone simply looking to upskill in more advanced roles with stronger analytical chops, we'd recommend checking out UC Davis's Data Visualization Specialization.  If you're interested in learning more about the general field of analytics first, check out our piece on the different types of analysts to learn more about necessary skills and core competencies.
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UC Davis's beginner-level specialization teaches the principles and theories behind data storytelling and how to apply these practical skills to create compelling charts and dashboards in Tableau. Tableau is one of (if not the best) the most coveted tools in the analytics community for it's powerful visualizations and ease of use for power-users and decision-makers alike. In fact, we saw Tableau listed by name in more than half the analytics job descriptions we surveyed. What we're trying to say: it's worth being certified.

The courses cover topics such as the importance of correct and ethical visualizations, how to create meaningful charts and dashboards using Tableau, measuring the right KPIs for an effective story, and using data to align audiences around a common goal. The program finishes with a hands-on capstone where students can apply their newfound skills to a complete a comprehensive project with several custom visualizations and a storytelling narrative.

The five courses to complete the specialization are:

• Fundamentals of Visualization with Tableau
• Essential Design Principles for Tableau
• Visual Analytics for Tableau
• Creating Dashboards and Storytelling with Tableau
• Data Visualization Capstone

The material is taught by real (and impressive, might we add) industry professionals, and covers the basics to become a proficient in both visualization techniques and Tableau quickly and efficiently.

If you only have time for one course and want to be extra dangerous this year- maybe you're a product manager looking to influence others with your data skills- we especially loved the dashboarding and storytelling course (#4 in the curriculum). We love this course because it covers the basics of a data story and how to use data to captivate an audience of all backgrounds.

Fun fact: we at Bridged used to teach a course on data storytelling on behalf of a large agency. It was super expensive for companies to buy for their employees (I'm talking thousands of dollars for only 2 days of curriculum), and this specialization covers a lot of the basics. Needless to say, we'd super recommend!

The curriculum is meant to be consumed over a 20-ish week period, but it can also be completed at your own pace.

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Best for: Beginners, Tableau Newbies and Aspiring Analytics Professionals

This course has some great material, but it is definitely aimed at an audience with no prior knowledge of data or Tableau. If that's you, great! We definitely recommend weighing this course as a way to broaden your expertise of the role and its responsibilities.

If you have experience with data or web analytics tools, even in another platform like Google Analytics, Amplitude or Heap, this specialization may be taught at a pace that's a little slow for you. If that's you, we've compiled some supplemental resources for your learning that progress at a more engaging pace.

After completing the specialization, you'll be equipped to apply for entry-level analyst positions, and have a leg up at companies that use Tableau (which is a lot of them!).

We’ve recapped the learning objectives from each week to set your expectations for course material. The great part about this program is that you can jump to any course, and any section if it’s interesting to you. For example, if you’re looking to just learn about KPIs and building dashboard reports, you'd jump to course 4, weeks 2 & 3.

To audit an individual week-- find the exact course (we've linked them individually here) and click "audit" to save it to your profile. Then open the desired week on the side panel that aligns with our recaps.

Course 1: Fundamentals of Visualization with Tableau

Learning Objectives from Week 1: Data Visualization and its Importance

• Define the concept of data visualization and learn its importance in understanding and communicating data.
• Walk through the history of data visualization and it's evolution over time.
• Install Tableau Public and start learning the basics of how to create a visualization.

Learning Objectives from Week 2: Get to Know Tableau

• Walk through the various functionalities of the homepage, worksheet and dashboard screens.
• We recommend getting really cozy with the worksheet/dashboard screens, as this will be a bulk of where your analytics time is spent.

Learning Objectives from Week 3: Your First Visualization!!

• Learn how to create visualizations that proactively answer potential questions around a dataset.
  
• Use Tableau to create some basics, including a bar chart, line chart, treemap, and general dashboard.
  
• Practice adding simple interactions to a dashboard to make it more user-friendly.
  

Learning Objectives from Week 4: Tableau Community Projects and Visualization Best Practices

• Learn where to find help and resources for your visualizations, including ways to get involved with some analytics communities.
• Apply the 5 best practices for data visualization to improve the effectiveness and clarity of your visualizations.

Course 2: Essential Design Principles for Tableau

Learning Objectives from Week 1: Effective and Ineffective Visuals

• Identify various types of Tableau visualizations, and practice improving ineffective visualizations.
• Discuss ethical concepts and how they relate to data visualizations.

Learning Objectives from Week 2: Visual Perception and Cognitive Load

• Define and understand the concepts of cognitive load and clutter and their impact on your visualizations.
• Learn and apply principles of visual perception and use of pre-attentive attributes to guide viewer's attention and make your data more understandable.
• Practice de-cluttering your visuals to reduce cognitive load and improve their effectiveness.
  

Learning Objectives from Week 3: Design Best Practices and Exploratory Analysis

• Learn and apply Gestalt principles, pre-attentive attributes and best practices to create more accessible and aesthetic visuals.
  
• Differentiate between exploratory and explanatory analysis, and practice creating both in Tableau.
• Create a control chart and practice identifying outliers.

Learning Objectives from Week 4: Design for Understanding

• Differentiate between System 1 and System 2 thinking to better inform visualization design for a target audience. We'll recap those concepts for you below.
• System 1 is automatic, immediate and reflexive perception, while System 2 is a more slow and deliberate thought process.
• Apply best practices to ensure that visualizations are effective for your target viewing audience.
  

Course 3: Visual Analytics with Tableau

Learning Objectives from Week 1: Charting

• Understand the different types of charts available in Tableau and how to choose the best-fitting chart for your datasets.
• Practice customizing Tableau charts with things like color, shapes and sizes.
• Use Tableau Tooltip to create a self-service chart.

Learning Objectives from Week 2: Dates

• Learn date hierarchies and how to differentiate between date-types.
• Show how to convert between different types of dates.
• Create new and future dates with calculated fields.

Learning Objectives from Week 3: Table Calculations

• Practice creating new calculated fields and quick table calculations.
• Learn how and when to use filters and parameters to make your data more interactive.

Learning Objectives from Week 4: Mapping

• Learn the different ways Tableau can munch and display geographical data.
• Connect to different data sources and customize a map.
• Create dual layer maps with latitude and longitude fields.

Course 4: Creating Dashboards and Storytelling with Tableau

Learning Objectives from Week 1: Planning and Preproduction: Aligning your Audience, Stakeholders and Data

• Understand the concept of data storytelling and how to use it in visualizations.
• Learn the key elements of a data story, with the 5 Ws: WHO, WHAT, WHEN, WHERE AND WHY and apply it to a dataset.
• Practice crafting a data story to a specific audience type based on stakeholder assessments.

Learning Objectives from Week 2: Key Metrics, Indicators and Design Triggers

• Learn how to identify key metrics (also known industry-wide as KPIs) that will provide insight into business questions.
• Practice creating calculated fields (go back to course 3, week 3 for a refresher) to measure KPI progress.
• Create alerts to trigger decisions and set benchmarks for KPIs.
• Explore how data quality can affect KPI measurements and visualizations.

Learning Objectives from Week 3: Dashboard and Storytelling with Data

• Learn and apply Tableau's six best practices for dashboard design to create baller visualizations.
• Build your own dashboard and apply hierarchies, actions, filters and parameters to make the visual more interactive and informative.
• Practice framing and storytelling from your new dashboard.

Learning Objectives from Week 4: Tell the Story of Your Data

• Analyze various techniques for compelling data storytelling and avoid pitfalls that unintentionally create false narratives.
• Understand the impact of neuroscience on information processing, audience engagement, and decision drivers so you can structure your story elements in a meaningful way.
• Practice using a design checklist to frame and format a data story and develop an awareness of unconscious biases that can impact a storytelling process.

Course 5: Data Visualization Capstone Project

Learning Objectives from Milestone 1: Develop a Project Proposal

• Create a case study project proposal, including things like challenges, audience needs, and necessary data sets.

Learning Objectives from Milestone 2: Importing and Prepping the Data

• Acquire and assess the data for consistency and quality.
• Import the data into Tableau and prepare the data for analysis.

Learning Objectives from Milestone 3: Exploratory Analysis

• Conduct an exploratory analysis.
• This includes things like identifying and creating KPIs, creating dashboards for comparative views, and showcasing your ability to create different types of visualizations.

Learning Objectives from Milestone 4: Exploratory Analysis (cont.) + Dashboard Submission

• Build multiple worksheets in Tableau to assist with your data story.
• Identify the KPIs in your story and mark them in your dashboards. Note other key relationships.
• Submit your dashboard for insights and recommendations of improvement.

Learning Objectives from Milestone 5: Storytelling and Storyboarding

• Practice writing narratives to go along with your created dashboard.

Learning Objectives from Milestone 6: Final Presentation

• Wrap it all up! Your final project should be a portfolio worthy roundup of a data story that includes multiple charts and graphs, and a narrative around KPI relations.

Quick Notes

We'd be remiss to not mention the couple negative-leaning reviews, which focus on two primary things: the program material could be completed in way less time, and a few of the Tableau commands were outdated.

Our rebuttal to these: first, it feels like fabulous news the course material can be covered in significantly less time. UC Davis is a prestigious institution, and saving money while also acquiring a ready-to-share-Linkedin-worthy certification in Tableau in less than a month? Sounds amazing! Check out our other course recommendations below if you're looking to subsidize your skills and learn more than the basics of both visualization and Tableau. Otherwise, take the $49 and the gift of time given to you and hustle through the program in under a month.

Second: Tableau is a great software, but like all programs it's constantly changing. The changes are often small and can be sorted with a quick Google search. The principles and key learning blocks remain the same!
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The program is only $49/month, and comes with a Linkedin Certificate on behalf of the University of California Davis.

If you complete the curriculum on the proposed timeline, it should take about 4-5 months, though you could blitz through it on a break in far less. While that seems steep, compared to a degree or bootcamp this micro-certification is a steal!If you have a learning budget, or are dedicated to upskilling your career with a data-focus– we recommend paying for and completing the program to get the shareable certificate (GET RECEIPTS!). This will help make your Linkedin more searchable to recruiters who may be looking for specific keywords and programs.

To audit the program and simply learn the material, this program is completely free! Thanks Coursera!

This program is tried and true and has been around since 2016. Each course averages well over a thousand reviews and has an average rating of around 4.6. The capstone has a little under 400, which is to be expected for a predominantly online class. For Coursera standards, the course is incredibly popular and highly rated!

Some of our favorite positive review points:

• Excellent course.  You get right into the functionality of Tableau and the assignments are done well and reinforce the learning. - Tom W.
  
• Very interactive and easy to follow course. Detail-oriented course with both the Tableau Software and Tableau concepts. I would recommend it all range of people, be it a beginner or someone well-versed in Tableau for concept refresh. - Sabyasachi N.
  

Aggregations of negative review points:

• Instructors take a long time to reply to questions or discussion boards.
• Some of the courses were more general data visualization and not Tableau-specific.
• Some of the material could be completed in way less than the recommended timeframes (this is great for you, if you're looking to get a certification quickly).
• All of the assignments are peer-graded, which may cause some frustration. We totally get this, but for the cost of the specialization and the benefits, this feels like a small price to pay.
• The Capstone project must be completed on a set timeline due to the grading schedule. Some reviewers dinged it for not allowing them to move ahead.

... and our favorite overall review:

Excellent course for beginners with an excellent outcome. For someone who is not usually a data visualizer, I got the chance to be the one creating  a dashboard from scratch. I am so pleased with the course materials and assessments. 100% recommended.

-Bashaier B.

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For the fans of the data-storytelling piece: Udemy's Data Storytelling

This class has more than ten thousand reviews and averages a 4.5 star rating. Upon completion you will be able to use a 5-stage arc to tell memorable stories and engage your audience.

It's tool agnostic, so if you're just looking for the story piece, this might be for you. Plus, it's only twenty bucks so your risk is low.

For the fans of visualization techniques: Mastering Data Visualization: Theory and Foundations

This class is extremely highly rated with a 4.7 and more than two thousand students. It focuses on how to present data clearly and effectively. It's a more high-level course and not based on a tool (take that how you will), but a great start for beginners who may be interested in the concept. The professor brags that once you take this class, you'll look at all charts in a new light!

For analysts who just need Tableau Help: Tableau 2022 A-Z: Hands-On Tableau Training for Data Science

This course is extremely popular on Udemy with more than eighty thousand reviews and a bestseller tag. It's also extremely highly rated with a 4.6 star average.

The material is more updated than UC Davis, and goes way deeper into the functionality of Tableau as a tool. We'd recommend this as a follow-on to the course after you've learned the basics, or if you're familiar with another analytics tool and looking for something with a quicker pace.

This is specifically aimed at Coursera Data Analaytics programs-- so if you sign up for Coursera unlimited, theoretically you could stack all of these. We don't recommend that, but we do recommend checking these out and seeing if any of them hit particular concepts that are interesting to you.

For the web analytics power-user: Google's Data Analytics Specialization

Google also sponsors a data analytics certificate program through Coursera. This is one of the more coveted certificates in the industry for learning the Google Analytics tool specifically, hence our recommendation of this course from Duke. Google's course is also free to audit, but same rules apply if you want the certificate to show off at $49 a month.

Comparable mid-level program: University of Minnesota's Analytics for Decision Making

The University of Minnesota runs a great program with a 4.7 star average. It's free to audit, but if you want the certificate it's covered under a $49/month Coursera subscription. We especially love course 2 for the experimenters out there... you can never go wrong with data-driven optimization strategies.
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This is a newer beginner-level class that has a great overview of types of analytics, and when to use each method to maximize effectiveness.

For a comprehensive overview of a bunch of analytics fields: Wharton's (UPenn) Business Analytics Specialization

Wharton is a prestigious business school and offers a great overview of different analytics fields, including marketing, ops and HR analytics.
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This is definitely a beginner-level specialization for people looking to identify their favorite concepts. Read our full writeup here.

More data science-y: University of Michigan's Applied Data Science Specialization

The University of Michigan also runs a great specialization that focuses on python techniques for effective data science. The reviews said it was pretty tough, but might be worth it if you're looking to expand your skillset into data science and enrolled in other Coursera options. Read our full writeup here.

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UC Davis's tableau progam is a great way to sharpen your practical analytics skillset in a traditional online classroom format. A certification in tableau is a great way to show diligence and focus on popular technology without breaking the bank with an additional college degree or bootcamp. As mentioned before, Tableau is the #1 required skill for analytics professionals.

Here at Bridged we are huge fans of stacking micro-certifications to achieve desired career results. This program could be one notch in your arsenal to really kick your technical expertise into gear!