Ledger Nano S - The secure hardware wallet

Data Operations: Daten für die Analyse optimal vorbereiten

#dataops: Folgen Sie der Diskussion auf Twitter
#dataops: Folgen Sie der Diskussion auf Twitter

Kürzlich habe ich einige Blog-Posts zum Thema Datenstrategie veröffentlicht. Für viele Unternehmen geht die Entwicklung und Einführung einer Datenstrategie nicht tief genug. Häufig habe ich ähnliches gehört: “So weit ist unser Unternehmen noch gar nicht. Wir haben noch viel operativ vorzubereiten, bevor wir eine Datenstrategie voll umfänglich etablieren können.”

Ich habe in diesen Gesprächen nachgehakt, wo diese grundlegenden Lücken in den Unternehmen bestehen, und entschlossen eine neue Blog-Post-Serie aufzusetzen, um zum Thema Data Operations (#dataops) konkrete und einfach umsetzbare Vorschläge zu geben.

Daten für die Analyse vorbereiten

Eine der wesentlichen Fragen, die sich Datenanalysten immer wieder stellen, lautet: “Gibt es eine Möglichkeit meine Daten für die Verwendung mit Analysewerkzeugen, wie Tableau, optimal vorzubereiten?”

Daten können auf unterschiedliche Arten strukturiert sein. Die meisten neuen Tableau-Anwender erliegen der Versuchung, Tableau mit einem bereits formatierten und voraggregierten Excel-Bericht (siehe Abbildung 1.1) zu verbinden und diesen in Tableau zu visualisieren. Heißt es nicht mit Tableau können Daten jeder Art einfach und intuitiv verwenden werden? Sehr schnell stellt man fest, dass ein solches Vorgehen nicht funktioniert, wie erwartet und sich so auch keine Visualisierungen erstellen lassen.

Abbildung 1.1: Bereits formatierter und voraggregierter Excel-Bericht
Abbildung 1.1: Bereits formatierter und voraggregierter Excel-Bericht

Dieses Szenario, dem viele Einsteiger begegnen, ist nicht ungewöhnlich und tatsächlich ein häufiger Stolperstein bei der Einarbeitung in Tableau, der die Analyse Ihrer Daten erschweren kann.

Die folgenden Punkte zeigen Ihnen Vorschläge zur sauberen Vorbereitung Ihrer Daten anhand des Beispielberichts:

  • Verzichten Sie auf den einleitenden Text (“Temperaturmessung zum Monatsbeginn”).
  • Überführen Sie hierarchische Überschriften (“Frankfurt”, “Berlin”) auf eine Spalteninformation (neue Spalte “Ort”).
  • Pivotisieren Sie Daten von einer “weiten” Kreuztabelle mit Variablen in Spalten (“Früh”, “Mittag”, “Abend”) in eine “lange” Tabelle, die die Variablen stets in den Zeilen trägt (in diesem Beispiel die Uhrzeit).
  • Nutzen Sie vollständige Datums- und ggf. Zeitformate (“01.04.2018 06:00”) anstatt z.B. nur den Monatsnamen (“April”).
  • Überprüfen Sie, dass Zahlen im Zahlenformat und nicht im Textformat gespeichert sind.
  • Verzichten Sie voraggregierte Daten (“Durchschnitt”, “Gesamtdurchschnitt”).
  • Entfernen Sie leere Zeilen.
  • Achten Sie darauf, dass jede Spate eine aussagekräftige Spaltenüberschrift trägt.

Haben Sie diese Vorschläge befolgt, ist aus Ihrer “weiten” Kreuztabelle nun eine “lange” Zeilen-basierte Tabelle geworden, und damit die perfekte Basis zur umfangreichen Datenanalyse (siehe Abbildung 1.2).

Abbildung 1.2: Zur Datenanalyse geeignete „lange Tabelle“ ohne Aggregationen
Abbildung 1.2: Zur Datenanalyse geeignete „lange Tabelle“ ohne Aggregationen

Dieser Blog-Post ist ein Auszug aus dem Buch “Datenvisualisierung mit Tableau“, das am 31. Juli 2018 erscheinen wird:

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

Leadership: Stagnation Kills Your Business, 3 Times

Petronas Twin Towers
Petronas Twin Towers held the title of the tallest building in the world for six years (Flickr)

Your business has been thriving, and the pipeline is well filled with work? Don’t get comfortable too soon. Stagnation kicks in fast nowadays, and kills your business’ innovation, its growth, and its people.

1. Innovation 

The speed of transformation that we are currently witnessing is challenging all of us to think differently. Every industry can be disrupted, there is no safe habour. So we need to deliver our products and services in a way that is relevant today, not yesterday.

Minor product iterations do not work forever. We need to prepare product revolutions, not just iterations on what we were selling since ten years. Establishing an innovation lab engages our employees to think in innovative ways and lift our business to new heights.

2. Growth

We need to adjust our business development plan to drive business growth. This should not be a static document. Customer and market definition are changing fast and we need to adopt this in our sales strategy and in our product development.

This does not work without data. Therefore we need to implement a data strategy. Our data strategy guides our entire business how to collect and analyze data, and how to generate the insights that we use for our decisions. If we do not take advantage of data, our competition will do.

3. People

Sushi Google DoodleIt is essential for leaders to recognize that you cannot possibly manage everything. We need to employ great people. But recruiting is not the end. We need to keep your talents, empower them, and motivate them to take initiative in their roles. Stagnation will rotate employees out of the company.

Offering free sushi and laundry service might impress our new hires from university. Experienced and independent employees will be more interested in career perspectives. We should establish personal development plans for everyone, not just for the designated managers.

Although it is important for leaders to set such a career framework, we should not forget to invest in your employees’ training. Both, hard skills (technical) and soft skills (non-technical), are mandatory because they each play very important roles in the development of our employees.

In Summary

Yesterday’s innovations are tomorrow’s commodities. We need to invest in innovations, otherwise we will face disruptive competition. Creating insights from data is important for the iterative adjustments on our business development plan. Offering personal development plans and proper training avoids stagnation for your employees, which is causing brain drain.

This post is also published on LinkedIn.

How to diversify a Long-term Crypto Portfolio

Last Friday it was my pleasure to give an Executive Talk at the Frankfurt School of Finance & Management. While the focus of my presentation was Digital Transformation, plenty of the questions raised by the audience were about the cryptocurrencies use case – and how to build a crypto portfolio. After I received some more emails from the participants asking for some guidance, I decided that is might be worth to publish this blog post.

The cryptocurrency market has returned over 1200% since the beginning of 2017. It is very hard to find this kind of return on investment (ROI) in the stock market or anywhere else. If you had made an investment of $500 in January, you would have made $6000 in less than a year! This guide is aiming to show you how to implement a cryptocurrency portfolio for a long-term investment.

In general, I recommend balancing your portfolio with up to five coins in the Top 10 market cap, making up 90-95% of your total cryptocurrency investment. And then add smaller coins (a.k.a. altcoins) – in projects you believe in – to fill up the remaining 5-10%. This mirrors the more technical analysis done by Timothy Chong on exploring a Markowtiz-style crypto optimization.

Bitcoin (30%)

Bitcoin (BTC) is the father of all blockchains, and is considered to be gold of cryptosphere. It is expected to grow step-by-step, without dramatic events. It is a safe long-term investment choice for many.

Price (as of time of writing): $16,708
Gain Over Past Year: 2,170%
Market Cap: $278 B (#1)
Circulating Supply: 16,734,237 BTC

Ethereum (30%)

Ethereum (ETH) is different to Bitcoin in that its sole purpose is not to be used as a medium of value exchange. Instead, Ethereum allows developers to build dApps using smart contracts. The tradeable currency of the Ethereum project is known as Ether.

Price (as of time of writing): $470
Gain Over Past Year: 5740%
Market Cap: $45 B (#2)
Circulating Supply: 96,272,074 ETH

Bitcoin Cash (10%)

Bitcoin Cash (BTC) is similar to Bitcoin in that it too is supposed to be a currency that is dedicated to serving as a medium for the purchase of various goods and services. The key difference between Bitcoin Cash and Bitcoin is that the former has an 8MB block size, whereas Bitcoin has a 1MB block size. A bigger block size allows Bitcoin Cash to process transactions faster than Bitcoin, and at a lower fee.

Price (as of time of writing): $1385
Gain Over Past 4 Month: 502%
Market Cap: $24 B (#3)
Circulating Supply: 16,849,738 BCH

Litecoin (10%)

Litecoin (LTC) is often marketed as being the silver to Bitcoin’s gold status. Being a hard fork of Bitcoin, Litecoin shares many similarities to the original coin. Litecoin can also be used as a value exchange coin. However, Litecoin’s block generation time of 2.5 minutes, compared to Bitcoin’s 10 minutes, and a different hashing algorithm (Scrypt), are features designed to produce a more innovative cryptocurrency.

Price (as of time of writing): $170
Gain Over Past Year: 4690%
Market Cap: $10 B (#5)
Circulating Supply: 54,255,483 LTC

Monero (10%)

Monero (XMR) is similar to Bitcoin in that it allows value exchange. However, Monero differs from Bitcoin in that it is focused on providing greater privacy to those that utilize their blockchain, using their stealth address mechanism. Anonymity is likely to become more and more important in a world where Bitcoin addresses can be traced. As more regulation starts entering the cryptocurrency space, an increasing number of individuals will gravitate towards privacy-focused coins such as Monero that can mask their transactions.

Price (as of time of writing): $264
Gain Over Past Year: 3370%
Market Cap: $4 B (#9)
Circulating Supply: 15,449,232 XMR

Electroneum (5%)

Electroneum (ETN) is a brand new cryptocurrency launching on September 14th – and is one of the projects were I see tremendous potential. Electroneum is developed to be used in the mobile gaming and online gambling markets, its goal is to be the most user-friendly cryptocurrency with wallet management and coin mining all possible on a mobile app.

Price (as of time of writing): $0.12
Gain Over Past 1 Month: 30%
Market Cap: $257 M (#44)
Circulating Supply: n/a (launched recently)

Zclassic (5%)

Zclassic (ZCL) is a great initiative as it is the first major fork of Zcash. Zclassic improves Zcash by removing the “founders fee”, which means that 100% of the coins mined go to the miners instead of 20% going to the founders. Like Zcash, Zclassic features zk-SNARKs, a new form of zero-knowledge cryptography. The privacy guarantee of Zcash and Zclassic is derived from the fact that shielded transactions can be fully encrypted on the blockchain. Furthermore, an upcoming fork of Zclassic is currently under discussion, which could dramatically boost the price of Zclassic.

Price (as of time of writing): $1.67
Gain Over Past Year: 328%
Market Cap: $3 M (#435)
Circulating Supply: 1,809,800 ZCL

Other altcoins have high potential as well. WTC, VTC, and VEN are also good worth to be considered. What is your cryptocurrency investment strategy? I’m happy to discuss more ideas in the comments!

This blog post is an opinion and is for information purposes only.  It is not intended to be investment advice. I am an investor and I contribute to the Zclassic fork project, and it is to my benefit that the project succeeds.

[Update 12 Dec 2017] Frequently asked questions after blog post release:

Q: Isn’t it too late to start buying Bitcoins now?
A: No. I’m very confident that Bitcoin will hit the 100,000 EUR/BTC mark by the end of 2018.

Q: Where can I buy bitcoins, ether and other coins?
A: Coinbase is a US-based cryptocurrency exchange where you can buy and sell Bitcoin, Ethereum, and Litecoin. bitcoin.de is the first Germany-based exchange where you can buy and sell Bitcoin, Ethereum, and Bitcoin Cash.

Q: Where can I buy alternative coins, such as Monero or Zclassic?
A: I prefer Cryptopia for most altcoin transactions (XMR, ETN, ZCL). If a coin is not available on this exchange, eg. IOTA, I’ll trade them on Binance.

Q: How can I store my cryptocurrencies in a secure way?
A: Either you can generate and print a paper wallet, or you can get a hardware wallet, such as the Ledger Nano S.

[Update 14 Dec 2017] Join the poll to find a name for our upcoming Zclassic fork:

Data Science Toolbox: How to use Julia with Tableau

R allows Tableau to execute Julia code on the fly
R allows Tableau to execute Julia code on the fly

Michael, a data scientist, who is working for a German railway and logistics company, recently told me during an FATUG Meetup that he loves Tableau’s R and Pyhton integration. As he continued, he raised the raised the question for using functions they have written in Julia. Julia, a high-level dynamic programming language for high-performance numerical analysis, is an integral part of newly developed data strategy in the Michael’s organization.

Tableau, however, does not come with native support for Julia. I didn’t want to keep Michael’s team down and was looking for an alternative way to integrate Julia with Tableau.

This solution is working flawless in a production environment since several months. In this tutorial I’m going to walk you through the installation and connecting Tableau with R and Julia. I will also give you an example of calling a Julia statement from Tableau to calculate the sphere volume.

1. Install Julia and add PATH variable

You can download Julia from julialang.org. Add Julia’s installation path to the PATH environment variable.

2. Install R, XRJulia and RServe

You can download base R from r-project.org. Next, invoke R from the terminal to install the XRJulia and the RServe packages:

> install.packages("XRJulia")
> install.packages("Rserve")

XRJulia provides an interface from R to Julia. RServe is a TCP/IP server which allows Tableau to use facilities of R.

3. Load libraries and start RServe

After packages are successfully installed, we load them and run RServe:

> library(XRJulia)
> library(Rserve)
> Rserve()

Make sure to repeat this step everytime you restart your R session.

4. Connecting Tableau to RServe

Now let’s open the Help menu in Tableau Desktop and choose Settings and Performance >Manage External Service connection to open the External Service Connection dialog box:

TC17 External Service Connection

Enter a server name using a domain or an IP address and specify a port. Port 6311 is the default port used by Rserve. Take a look on my R tutorial to learn more about Tableau’s R integration.

5. Adding Julia code to a Calculated Field

You can invoke Calculated Field functions called SCRIPT_STR, SCRIPT_REAL, SCRIPT_BOOL, and SCRIPT_INT to embed your Julia code in Tableau, such as this simple snippet that calculates sphere volume:

6. Use Calculated Field in Tableau

You can now use your Julia calculation as an alternate Calculated Field in your Tableau worksheet:

Using Julia within calculations in Tableau (click to enlarge)
Using Julia calculations within Tableau (click to enlarge)

Feel free to download the Tableau Packaged Workbook (twbx) here.

Further reading: Mastering Julia

Social Media and the Customer-centric Data Strategy #data17 #resources

Social media marketing mix
Do you analyze your social media marketing mix? | Photo Credit: via Richard Goodwin

With over 3 billion active social media users, establishing an active presence on social media networks is becoming increasingly essential in getting your business front of your ideal audience. These days, more and more consumers are looking to engage, connect and communicate with their favorite brands on social media.

Adding social media to your customer-centric data strategy will help boost brand awareness, increase followership, drive traffic to your website and generate leads for your sales funnel. In 2017, no organization should be without a plan that actively places their brand on social media, and analyzes their social media data.

Once you’ve started diving into social media analytics, how do you bring it to the next level? This session covers a customer-centric data strategy for scaling a social media data program.

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

The Data Opportunity

TC17 Social Media Slides: The Data Opportunity

Focus on relevant metrics for your strategy

TC17 Social Media Slides: Sentiment Analysis

How to get Social Media in Tableau?

TC17 Social Media Slides: 3rd Party Platform Talkwalker

Tips to Level Up

TC17 Social Media Slides: Unshorten URLs in Tableau with R

Tutorials and Slide Set

The slides and tutorials presented at Tableau Conference on Tour in Berlin are also available on SlideShare, and on YouTube in English and German.

English Tutorials

German Tutorials

Slide Set