Schlagwort: Tableau

Welcome to the Tableau section of my blog, where I share my knowledge and experience with one of the world’s most popular data visualization tools. As someone who has worked with and used Tableau for years, I’m passionate about helping others master this powerful tool and make the most of its capabilities.

In this section, you’ll find a variety of tutorials on topics such as building visualizations, creating dashboards, and using Tableau’s advanced features. I’ll also share stories and insights from my time working with Tableau, including tips and tricks for getting the most out of the tool.

Whether you’re new to Tableau or an experienced user looking to take your skills to the next level, these tutorials and stories will give you the practical knowledge and insight you need to succeed. I believe Tableau has the power to change the way we think about and interact with data, and I’m excited to share that vision with others.

So join me on this journey as we explore the world of Tableau together and discover new ways to unlock the full potential of your data.

Künstliche Intelligenz und Automation: Was macht das intelligente Unternehmen von morgen aus? Automation KI im Fokus

Automation KI: Transformieren Sie Ihr Unternehmen
Automation KI: Transformieren Sie Ihr Unternehmen

In der heutigen, schnelllebigen Geschäftswelt spielen Künstliche Intelligenz (KI) und Automation eine immer wichtigere Rolle. Die Integration von Automation und KI kann zu zusätzlichem Absatz, effizienteren Arbeitsabläufen und einer Verbesserung der Customer Experience führen. Aber wie genau kann ein Unternehmen diese Technologien effektiv nutzen?

Bei der Expertenrunde beim Roundtable zu Künstliche Intelligenz und Automation bei Computerwoche habe ich hierzu gesprochen. Wie ich betonte:

„Tableau hilft beim Überführen von KI in praktisch umsetzbare Erkenntnisse und das Voranbringen des gesamten Unternehmens.“

Alexander Loth

Hier sind drei relevante Fragen, die sich stellen, wenn Sie mit Künsliche Inelligenz und Automation Geschäftsprozesse standardisieren und automatisieren möchten:

1. Wie sehen geeignete Einstiegszenarien und Use Cases in die KI- und Automation-Welt aus?

Der Einstieg in die Künstliche Inelligenz und Automation sollte strategisch geplant werden. Geeignete Einstiegszenarien könnten in Bereichen liegen, in denen wiederholbare, regelbasierte Aufgaben ausgeführt werden. Zum Beispiel kann ein Chatbot die Kundenservice-Abteilung unterstützen, während Robotic Process Automation (RPA) Rechnungen und Bestellungen verarbeiten kann. Use Cases erstrecken sich auf unterschiedliche Branchen wie Finanzen, Gesundheitswesen und Einzelhandel, wobei die genaue Anwendung von den spezifischen Geschäftsbedürfnissen abhängt.

2. Welche organisatorischen Anforderungen stellt die Implementierung von KI- und Automation-Lösungen an die Unternehmens-IT?

Die Implementierung von KI und Automation erfordert eine klare Datenstrategie, die die Geschäftsziele mit den technologischen Fähigkeiten abstimmt. Darüber hinaus sind eine starke Zusammenarbeit zwischen IT und Geschäftsbereichen, die Einhaltung von Datenschutzbestimmungen, ausreichende Schulung und Unterstützung der Mitarbeiter und eine robuste Infrastruktur unerlässlich, um die neuen Technologien zu unterstützen.

3. Welche Technologien stellen IT-Abteilungen vor die größten Herausforderungen? Und welche bieten den höchsten Mehrwert?

Die Integration von Künstlicher Intelligenz und Automation in bestehende Systeme kann eine Herausforderung darstellen, besonders wenn ältere Technologien nicht kompatibel sind. Cloud-Computing, maschinelles Lernen, IoT und Big Data sind Technologien, die sowohl eine Herausforderung als auch einen hohen Mehrwert bieten. Die Wahl der richtigen Tools, Plattformen und Technologien hängt von den spezifischen Geschäftsanforderungen und Zielen ab, aber eine erfolgreiche Implementierung kann zu erheblichen Effizienzsteigerungen und Wettbewerbsvorteilen führen.

Mehr zu Automation und KI im Buch Decisively Digital

Automation und KI transformieren die Art und Weise, wie Unternehmen arbeiten, und eröffnen spannende neue Möglichkeiten für Innovation und Wachstum. Die Themen, die wir hier angeschnitten haben, sind jedoch nur die Spitze des Eisbergs.

Für diejenigen, die daran interessiert sind, tiefer in die Welt der Künstlichen Intelligenz, Automatisierung und Robotic Process Automation (RPA) einzutauchen, freue ich mich, mein bald erscheinendes Buch Decisively Digital: From Creating a Culture to Designing Strategy (Amazon) anzukündigen. Dieses Werk bietet eine umfassende Analyse dieser Schlüsseltechnologien und liefert praxisorientierte Einblicke und Strategien für Unternehmen jeder Größe.

Decisively Digital wird sowohl den Anfänger als auch den Experten in die Welt von KI und Automation führen, die Themen aber noch tiefer im Detail behandeln. Bleiben Sie dran für weitere Informationen zur Veröffentlichung und wie Sie Ihr Exemplar reservieren können!

Wie immer stehe ich zur Verfügung, um Ihre Gedanken und Fragen zu Automation und KI zu diskutieren, besonders da ich meine Erfahrungen bei der Expertenrunde beim Roundtable zu Künstliche Intelligenz und Automation bei Computerwoche geteilt habe.

The Empathy Machine: Are Digital Technologies the Best Bet in Telling about your Cause?

The panel discussion „The empathy machine: are digital technologies the best bet in telling about your cause?“ took place on the opening day of the 2018 Fundamental Rights Forum (FRA). This forum was organized by the European Union Agency for Fundamental Rights, and took place at the METAStadt Vienna 25-27 September 2018.

In this panel discussion Kadri Kõusaar (a Oscar nominated film director), Fanny Hidvegi (European Policy Manager) and me discussed if digital technologies really are the “empathy machine” and how innovative applications can help human rights defenders to achieve some challenging goals such as a change in public attitudes or meeting tough fund-raising targets. The panel discussion was moderated by the virtual reality artist Dr. Frederick Baker.

In this blog post I want to share some of the panel’s questions, which I answered:

1. How do algorithms interfere with human rights?

When algorithms make certain decisions, these algorithms  tent to mirror what they are shown with training sets. This is especially apparent for issues such as bias and machine discrimination. Both might be the result of the content of the training data, which reflects existing inequalities.

2. So, it’s about the data? What else makes data so important today?

The effective use of data is vital for our understanding of fundamental issues, such as human rights violations and political instability, for informing our policy-making, and for enhancing our ability to predict the next crisis. Furthermore, the scope, complexity and life-changing importance of the work being done on topics like these across the European Union has made it more important than ever for everyone participating in the public conversation and in demographic decision-making to have access to and to be able to derive insights from key data sources.

3. Where is data coming from and how can people benefit?

Every time we google something, send a tweet, or just browse a website, we create data. With the rise of visual analytics we can benefit from this vast amount of information. Visual analytics is a hands-on approach to interacting with data that does not require any programming skills. Furthermore, communicating with data, is seen as one of the most relevant skills in today’s information age.

Global Refugee Crisis visualization on Tableau Public

4. What is the easiest way to find interesting data?

I would check out the Google’s new search engine for datasets that was just released recently! Tableau Public is a good source for existings visualizations. Many of these are based on public data.

5. What is required to enable organizations to use data for good?

Data can be used for the good of society, but private- and public-sector firms, nonprofits and NGOs still lack analytics resources and expertise. Data and analytics leaders must cross traditional boundaries to use data for good, to better compete for limited talent, and to foster an ethical culture. VizForSocialGood and Tableau Foundation are good examples.

6. How can the private sector contribute for good?

Some private sector organizations are making data open and available to researchers, nonprofits and NGOs. Examples include:

  • Mastercard anonymizing credit card data to be analyzed in smart city initiatives.
  • Google making search data available to hospitals to predict infection disease outbreaks such as flu and dengue fever.
  • Insurance companies providing anonymized healthcare data to improve patient outcomes and prevention strategies.
  • Yelp providing ratings data to cities to prioritize food safety inspectors.

The panel discussion was followed by workshops in the afternoon:

 

Is Crypto Dead? What to Buy/Mine? FinTechs beyond Blockchain?

Bitcoin crashes to lowest this year, losses top 25% in a week
Bitcoin crashes to lowest this year, losses top 25% in a week | Photo Credit: via Marco Verch

Yesterday, on my way to an AI roundtable, I had an interesting conversation about the future of crypto assets. I met Michael, who works for one of the world’s biggest insurance companies, on the train from Frankfurt to Munich. Of course, our conversation started with a nifty 7-minute Tableau demo – a wonderful ice breaker!

After closing the demo with the Bitcoin Dashboard on Tableau Public, the conversation quickly headed towards crypto assets and (non-)blockchain FinTechs. These are the top 3 of Michael’s questions that I want to share with you – together with my answers:

1. Is the blockchain innovation dead?

Absolutly not! Blockchain is a relatively new technology which has a long way to go before it becomes mainstream. Last year the most successful projects were those that aimed at adapting new technologies for convenient use. Furthermore, crypto assets create a new structure of safe and anonymous storage and managing of information. Projects like Ethereum proved to be extremely useful for building a steady and secure contracts, cloud storage and product quality control.

2. Are there still interesting crypto assets to buy or to mine?

Yes, indeed! In particular I’d suggest crypto assets targeting innovative use cases. If you buy these, you are actually investing in technology projects:

  • Factom (FCT) recently announced a partnership with Equator PRO, and according to the press release that announced the -partnership, Equator PRO is a software-as-a-service (SaaS) solution that aims to offer efficiency and oversight to help other mortgage servicers.
  • Clams (CLAM) is a crypto asset similar to bitcoin, but is using a ‘proof of stake’ system, which should be more equitable and fairer than bitcoin’s ‘proof of work’ system.
  • Electroneum (ETN) has a heavy emphasis on mobility and micropayments. A huge portion of the world’s population own a mobile phone but have no bank account. Electroneum aims to provide financial services for everybody in the world who has a mobile phone.

If you are into mining, it also makes sense if you are going to mine coins with innovative technology. Currently, I would strongly consider to mine Ravencoin (RVN) and its little sister Pigeoncoin (PGN).

Factom use cases
Factom use cases

3. Which non-blockchain related FinTech might be worth to look at?

Definetly Mintos! Mintos is much more than a regular peer-to-peer lending platform. Mintos is a global online marketplace for loans, which provides retail investors an easy and transparent way to invest in loans originated by a variety of alternative lending companies around the world. Furthermore, Mintos has demonstrated exponential growth and has become the world’s largest marketplace of its kind.

What’s your view on crypto? Let me know in the comments or via Twitter:

#TC18 Wrap-up: Azure SQL Data Warehouse speeds up your Analysis

Benchmark: Microsoft Azure SQL Data Warehouse outperforms Amazon Redshift in TCP-H 30TB
Benchmark: Microsoft Azure SQL Data Warehouse outperforms Amazon Redshift in TCP-H 30TB

Slowly the dust settles after the impressive TC18. During my wrap-up, I remembered the data warehouse benchmarks of the Azure & Tableau session by James Rowland-Jones. Especially because my customers ask me about such performance metrics over and over again.

The first benchmark (graph above) shows how Microsoft Azure SQL Data Warehouse (aka. SQL DW) outperforms Amazon Redshift – in terms of performance and price. While the second benchmark shows further performance tests for Amazon Redshift, Snowflake, Azure, Presto, and Google Big Query:

Benchmark: Microsoft Azure SQL Data Warehouse Gen 2 vs. Amazon Redshift, Snowflake, Presto, Google Big Query
Benchmark: Microsoft Azure SQL Data Warehouse Gen 2 vs. Amazon Redshift, Snowflake, Presto, Google Big Query

Since James‘ session is already available on Tableau’s Youtube channel, feel free to watch the entire Azure & Tableau session:

#TC18 Visual Diary: One Big-Easy Data Fest

Iron Viz contest at Tableau Conference TC18 in New Orleans
Iron Viz contest at Tableau Conference TC18 in New Orleans

Let me share some (personal) Tableau Conference #TC18 experiences with you!

Oct 22

Registration

Viz for Social Good

Welcome Reception

Oct 23

Opening Keynote

My 1st Session | Rock your Social Media Data with Tableau

Data Village | Diversity and Inclusion

Community Appreciation Reception

Oct 24

Keynote | Devs On Stage

My 2nd Session | Rock your Social Media Data with Tableau

Tableau User Group | Tip Battle

Iron Viz

Data Night Out

Oct 25

Keynote | Adam Grant

Data Village

Fanalytics

Goodbye

What are your #TC18 highlights?

Share your favorite moments in the blog post comments or reply to this tweet: