Datenvisualisierung mit Tableau: Geben Sie mir Feedback für die 2. Auflage des Tableau-Buchs

Buch-Cover von Datenvisualisierung mit Tableau
Buch-Cover von Datenvisualisierung mit Tableau

Wow, es ist fast ein Jahr her, seit mein Buch “Datenvisualisierung mit Tableau” veröffentlicht wurde! Ich danke allen Lesern für die vielen postiven Rückmeldungen  und freue mich, dass mein Buch Ihnen hilft Erkenntinsse aus Ihren Daten abzuleiten und diese im Unternehmen zu teilen.

Die erste Auflage des Tableau-Buchs ist auch schon fast verkauft. Daher stellt sich nun die Frage, ob es einen Nachdruck geben wird, oder ob es bereits Potential für eine zweite Auflage gibt. Um das zu entscheiden, freue mich auf Ihr Feedback!

Schreiben Sie mir dazu einfach per Email: feedback@alexloth.com

Alle Ideen und Anregungen für eine mögliche zweite Auflage sind herzlich willkommen!

Datenvisualisierung mit Tableau
  • Alexander Loth
  • Publisher: mitp
  • Edition no. 2018 (31.07.2018)
  • Broschiert: 224 pages

Visual Analytics with Tableau: Book is in Stock again

Visual Analytics with Tableau on Amazon screenshot
Visual Analytics with Tableau is on stock again: Screenshot shows availability on amazon.com

Did you get your Tableau Conference Europe 2019 ticket and now need something to read for the journey?

Then I have some good news: Right on time, just a few weeks before TCE19, my new book Visual Analytics with Tableau  is in stock again!

As you know from my previous Tableau Conference sessions and blog posts (TC18, TC17, TC16), I love social media! So thank you for your likes, shares, retweets…

Instagram ❤️

Twitter ❤️

Facebook ❤️

LinkedIn ❤️

Visual Analytics with Tableau
  • Alexander Loth
  • Publisher: Wiley
  • Edition no. 1 (31.05.2019)
  • Taschenbuch: 288 pages

Visual Analytics with Tableau: Book is Now Available

Visual Analytics with Tableau book cover
Visual Analytics with Tableau book cover

My book Visual Analytics with Tableau is now available:

From the back cover:

A 4-COLOR JOURNEY THROUGH A COMPLETE TABLEAU VISUALIZATION FOR NON-TECHNICAL BUSINESS USERS

Tableau is a popular data visualization and analytics tool favored by financial analysts, marketers, statisticians, business and sales professionals, data scientists, developers, and many others who need to explore insights and present visual, easy-to-understand data. Visual Analytics with Tableau is an accessible, step-by-step introduction to the world of visual analytics. This up-to-date guide is ideal for both beginners and more experienced users seeking a practical introduction to the fields of data analysis and visualization. Through hands-on examples and exercises, readers learn how to analyze their own data and clearly communicate the results.

This guide covers everything you need to get started with Tableau, from the first steps of connecting to data, creating different types of charts, and adding calculation fields to more advanced features such as table calculations, forecasts, clusters, and R, Python, and MATLAB integration for sophisticated statistical modelling. User-friendly instructions for existing options within the Tableau ecosystem–Tableau Desktop, Tableau Prep, Tableau Server, Tableau Online, and Tableau Public–enable you to integrate, clean, and prepare your data and share your work with others. Visual Analytics with Tableau:

  • Covers the newest versions of Tableau 2018.3 and 2019.1 plus Tableau Prep, Tableau’s brand-new data integration application
  • Requires no background in mathematics nor any programming experience
  • Focuses on the visual analytics functionality of Tableau rather than complex statistical programming
  • Offers expert guidance from popular Tableau Germany employee and visualization expert Alexander Loth
  • Discusses advanced Tableau functionality and working with different data structures
  • Provides easy-to-follow instructions, full-color illustrations, learning tools, online resources, and more

If you’re getting started with visual analytics and Tableau, this book will teach you everything you need to know to build the foundations and understand how and why to explore your data visually. Alexander has created a fantastic resource that guides you step by step through the process of preparing your data, using Tableau Desktop to analyse it and finding insights.
–Eva Murray, Head of BI and Tableau Zen Master at Exasol

If you’re keen to go from beginner to expert in Tableau, Alexander’s excellent book gives you everything you need to know. With a crisp and clear style, he talks the reader through all aspects of Tableau, from data cleaning through data analysis and into sharing insight with others.
–Andy Cotgreave, Author of Big Book of Dashboards and Technical Evangelist at Tableau Software

Visual Analytics with Tableau – an easy to understand book by Alexander Loth, one of Tableau’s very first employees based in Germany, a recognized speaker on countless conferences, and a Tableau Jedi. It contains both the basics and advanced Tableau features. If you ask me: there is nothing more you need to get started with Tableau!
–Klaus Schulte, Professor at Münster School of Business & 2019 Tableau Zen Master

Thank you all who helped me to complete this book!

Visual Analytics with Tableau
  • Alexander Loth
  • Publisher: Wiley
  • Edition no. 1 (31.05.2019)
  • Taschenbuch: 288 pages

How to research LinkedIn profiles in Tableau with Python and Azure Cognitive Services

Tableau is using Python to access the Web Services API provided by Microsoft Azure Cognitive Services
Tableau is using Python to access the Web Services API provided by Microsoft Azure Cognitive Services

A few weeks after the fantastic Tableau Conference in New Orleans, I received an email from a data scientist who attended my TC18 social media session. She had a quite interesing question:

How can a Tableau dashboard that displays contacts (name & company) automatically lookup LinkedIn profile URLs?

Of course, researching LinkedIn profiles for a huge list of people is a very repetitive task. So let’s find a solution to improve this workflow…

1. Python and TabPy

We use Python to build API requests, communicate with Azure Cognitive Services and to verify the returned search results. In order to use Python within Tableau, we need to setup TabPy. If you haven’t done this yet: checkout my TabPy tutorial.

2. Microsoft Azure Cognitive Services

One of many APIs provided by Azure Cognitive Services is the Web Search API. We use this API to search for name + company + “linkedin”. The first three results are then validated by our Python script. One of the results should contain the corresponding LinkedIn profile.

3. Calculated Field in Tableau

Let’s wrap our Python script together and create a Calculated Field in Tableau:

4. Tableau dashboard with URL action

Adding a URL action with our new Calculated Field will do the trick. Now you can click on the LinkedIn icon and a new browser tab (or the LinkedIn app if installed) opens.

LinkedIn demo on Tableau Public

Is this useful for you? Feel free to download the Tableau workbook (don’t forget to add your API key), leave a comment and share this tweet:

#TC18 Sessions: Rock your Social Media Data with Tableau

My TC18 sessions in New Orleans: "Rock your Social Media Data with Tableau"
My TC18 sessions in New Orleans: “Rock your Social Media Data with Tableau”

Anyone can analyze basic social media data in a few steps. But once you’ve started diving into social analytics, how do you bring it to the next level? This session will cover strategies for scaling a social data program. You’ll learn skills such as how to directly connect to your social media data with a Web Data Connector, considerations for building scalable data sources, and tips for using metadata and calculations for more sophisticated analysis.

First session: Tues, 23 Oct,  12:30-1:30 (Location: MCCNO – L3 – 333)

Second session: Wed, 24 Oct, 10:15-11:15 (Location: MCCNO – L3 – 346)

Twitter Analysis #TC18 Dashboard featured as Tableau Public Viz of the Day
Twitter Analysis #TC18 Dashboard featured as Tableau Public Viz of the Day

Here are some key takeaways and links (i.e. additional resources) featured during my TC18 sessions to help you formulate your social media data program in order to build a stronger presence and retrieve powerful insights:

Prolog: Introducing data artist Noah

Step 1: Understand How to Succeed with Social Media

Apple has officially joined Instagram on 7th August 2017. This isn’t your average corporate account as the company doesn’t want to showcase its own products. Instead, Apple is going to share photos shot with an iPhone:

The Customer-Centric Data Strategy

Apple’s Instagram account is more an extension of the “Shot on iPhone” billboard ad campaign.

And there are plenty takeaways for every business:

  • Wrap your data around your customers, in order to create business value
  • Interact with your customer in a natural way
  • Understand your customer and customer behaviour better by analyzing social media data

Step 2: Define Your Social Objectives and KPIs

A previous record-holding tweet: In 2014, actor and talk show host Ellen DeGeneres took a selfie with a gaggle of celebrities while hosting the Oscars. That photo has 3.44 million retweets at the time of writing:

Social Objectives:

  • Define specific KPIs for social media platforms
  • KPI objectives need to be measurable
  • Metrics should be in line with the business goals

Step 3: Assemble Your KPIs

Brand Awareness and Reputation

Step 4: Connect Your Social Media with Tableau

Option 1 – Directly from the platform: Get data directly from Facebook, Twitter, YouTube, and more

Option 2 – Via web automation: Use a service like IFTTT to store data on Google Sheets

Option 3 – Via web data connector: Use Tableau’s web data connector, e.g. the Twitter Web Data Connector by Alex Ross (a.k.a. Tableau Junkie) -> http://bit.ly/tc18_twitter

Option 4 – Code your own solution: Use an API provided by the platform -> http://bit.ly/tc17_r_fetch

Option 5 – Via a third party platform: Get data from an integrated social media platform, such as Talkwalker -> http://bit.ly/tc17_talkwalker

Talkwalker - Via a Third Party Platform

Step 5: Apply some Tips to Level Up

Gather Historic Data

Step 6: Explore Social Media Listening

Social listening means that you look beyond your own content. E.g. Talkwalker offers AI for image recognition and ggregation for online/offline media: http://bit.ly/tc17_talkwalker

Step 7: Leverage Your Analytics Tool Chain

Use Your R and Python Skills

Demo/Tutorial: Let’s See this in Tableau!

How to analyse Social Media traffic with Google Analytics in Tableau (YouTube):

How to analyse Social Media data from Twitter in Tableau (YouTube):

Slide Set

The slides presented at Tableau Conference are also available on SlideShare.

Are you on Social Media?

Feel free to retweet/share:

[Update 25 Oct 2018]: Missed the sessions? Watch the recording online!