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.
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 worldâs 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 Michaelâs 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 âproof of stakeâ system, which should be more equitable and fairer than bitcoinâs âproof of workâ system.
Electroneum (ETN) has a heavy emphasis on mobility and micropayments. A huge portion of the worldâs 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
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:
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 youâve 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. Youâll 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.
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:
Step 1: Understand How to Succeed with Social Media
Apple has officially joined Instagram on 7th August 2017. This isnât your average corporate account as the company doesnât want to showcase its own products. Instead, Apple is going to share photos shot with an iPhone:
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 listening means that you look beyond your own content. E.g. Talkwalker offers AI for image recognition and ggregation for online/offline media:Â http://bit.ly/tc17_talkwalker
Are you ready for Tableau Conference 2018? Donât miss my Social Media Analytics sessions!
Why do we need Social Media Analytics?
Social Media Analytics transforms raw data from social media platforms into insight, which in turn leads to new business value.
What will your learn in this sessions?
Once you dive into Social Media Analytics, how do you bring it to the next level? Social data can offer powerful insights right away. In this session, you will learn how to build a mature social data program from that foundation and strategies for scaling a social data programme, as well as how to connect directly 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.
Where and when are the sessions?
Do you want to learn more about Social Media Analytics with Tableau? Meet me at the 2018 Tableau Conferences in London or New Orleans and join my sessions:
Immersive und interaktive Analyse von Finanzdaten mit Argumented Reality (Blockchain-Dashboard)
Jedes Jahr (2015, 2016, 2017 und 2018) stelle ich Digitalisierungstrends vor, die der Finanzbranche ein groĂes Potenzial bieten. Dabei geht es vor allem um einen Ăberblick darĂŒber, welche Trends und Technologien zukĂŒnftig eine gröĂere Rolle spielen werden oder könnten.
Im Folgenden habe ich die fĂŒnf Digitalisierungstrends identifiziert, die fĂŒr Banken und Versicherungen in Zukunft besonders spannend sein dĂŒrften:
1. Maschine Learning
Maschine Learning und Deep Learning werden im Investment Banking angewandt, um Unternehmensbewertungen schneller und zuverlĂ€ssiger durchzufĂŒhren. Mehr Daten denn je können hinzugezogen werden. Eine Gewichtung der Daten erfolgt komplett autonom. Da manuelle Analyse weitgehend entfĂ€llt, werden Entscheidungsprozesse drastisch beschleunigt. Investoren, die mit konventionellen Werkzeugen arbeiten, haben das Nachsehen.
2. KĂŒnstliche Intelligenz
Durch KĂŒnstliche Intelligenz gesteuerte Chatbots vermitteln den Kunden eine menschlichen-Ă€hnliche Betreuung. Chatbots werden darĂŒber hinaus in existierende Cloud-basierende Assistenten, wie Alexa oder Siri, eingebunden und sind in der Lage mittels Natural Language Processing, auch komplexere Anfragen zu verstehen. Recommender-Systeme liefern maĂgeschneiderte Lösungen, die speziell auf die BedĂŒrfnisse der Kunden abgestimmt sind.
3. Internet of Things
Wearables und in Kleidung eingearbeitete Sensoren (Internet of Things, IoT) liefern ausreichend Daten, um den Lebensstil der Kunden vollstĂ€ndig zu vermessen. Dadurch können individuelle Raten fĂŒr Versicherungen und Finanzprodukte berechnet werden. AuĂerdem bieten die IoT-Daten eine weitere Datenquelle fĂŒr die Recommender-Systeme.
4. Blockchain
VertrĂ€ge werden kostengĂŒnstig, fĂ€lschungssicher und irreversibel in der Blockchain gespeichert. Die Blockchain dienst sogenannten Smart Contracts als dezentrale Datenbank. DarĂŒber hinaus liefern Blockchain-Implementierungen, wie Ethereum, das AusfĂŒhren von Logik, die beispielsweise monatliche Zahlungen prĂŒfen und ggf. auch die ErfĂŒllung von Vertragsbestandteilen (z.B. im Schadenfall) steuern.
5. Argumented Reality
ArbeitsplĂ€tze werden mit Technik ausgestattet, die Argumented Reality ermöglicht. Lösungen wie Microsoft’s Hololense ermöglichen Analysten und HĂ€ndlern eine immersive und interaktive Analyse von Finanzdaten in Echtzeit. Insbesondere fĂ€llt dadurch auch die Zusammenarbeit mit Kollegen leichter, da Plattformen zur visuellen Kollaboration traditionelle Meetings weitgehend ablösen.
Welcher ist der 6. Trend?
Helfen Sie den 6. Digitalisierungstrend zu benennen? Nehmen Sie hierzu an der Twitter-Umfrage teil. SelbstverstĂ€ndlich freue ich mich auch ĂŒber Kommentare und eine spannende Diskussion.
Digitale Banken: Welche Digitalisierungstrends bewegen die Finanzbranche 2018: https://t.co/3wvEsofy8M Welchen Trend sehen Sie noch?
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