It’s My 10 Year Blogging Anniversary!

Photo from an early blog post: 2007 Hampi, a temple town in South India recognised as UNESCO World Heritage Site
Photo from an early blog post: 2007 Hampi, a temple town in South India recognized as UNESCO World Heritage Site (Flickr)

Woohoo, it’s already ten years since I started this blog. Can’t believe it! Thanks to all of those who read my posts, and who encouraged and inspired me. Without you blogging would be only half the fun! Now, let’s have a little recap…

2007-2009 SAP and India:

It all started in 2007. I was studying Computer Science, and decided to go for an internship abroad. China and India were on my short list. I decided for India, applied for a scholarship and asked some companies for interesting project work. Before starting the adventure, I published my very first blog post to keep family and friends in loop.

For the next seven month, I lived in Bangalore, and worked for SAP Labs India to develop prototypes for mobile BI apps. I spent plenty of weekends to explore India and surrounding countries. After returning from India, I continued to work for SAP at their headquarters while finishing my degree in Karlsruhe.

2009-2012 CERN:

CERN, surrounded by snow-capped mountains and Lake Geneva, grabbed my attention during the end of my studies. CERN has tons of data: some petabytes! Challange accepted. CERN is known for its particle accelerator Large Hadron Collider (LHC). We applied machine learning to identify new correlations between variables (LHC data and external data) that were not previously connected.

2012-2015 Capgemini and MBA:

Back in Germany, I wanted to bring Big Data Analytics to companies. To one company? No, to many companies! So instead of getting hired as Head of BI for an SME, I started to work for Capgemini. I had fantastic projects, designed data-driven usecases for the financial sector, and gave advice for digital transformation inititives.

In order to keep in balance with all the project work, I dedicated many of my weekend for studies and got enrolled in Frankfurt School’s Executive MBA programme. During my studies, I focused on Emerging Markets and visited a module at CEIBS in Shanghai.

2015-201? Tableau and Futura:

I knew Tableau from my time as consultant. It is an awesome company with a great product and a mission: help people see and understand their data. That’s me! I joined Tableau to help organizations through the transition from classic BI factories to modern self-service analytics by developing data strategies, so that data can be treated as a corporate asset. This includes education, evangelism and establishing a data-driven culture.

In the evenings I’m working for Futura Analytics, a fintech startup, which I co-founded in 2017. Futura Analytics offers real-time information discovery, and transforms data from social media and other public sources into actionable signals.

What’s next?

Currently I’m looking forward to give my Data Strategy talk on TC17 accompanied by a TensorFlow demo scenario. I’m also learning Mandarin, the predominant language of business, politics, and media in China and Taiwan, for quite a while. Let’s see if that is going to influence my next steps… 🙂

7 Big Data Analytics Use Cases for Financial Institutions

Big Data Analytics
Big Data Analytics

Recently we hear a lot about Big Data Analytics’ ability to deliver usable insight – but what does this mean exactly for the financial service industry?

While much of the Big Data activity in the market up to now has been experimenting about Big Data technologies and proof-of-concept projects, I like to show in this post seven issues banks and insurances can address with Big Data Analytics:

1. Dynamic 360º View of the Customer:
Extend your existing customer views by incorporating dynamic internal and external information sources. Gain a full understanding of customers – what makes them tick, why they buy, how they prefer to shop, why they switch, what they’ll buy next, and what factors lead them to recommend a company to others.

2. Enhanced Commercial Scorecard Design and Implementation:
Financial institutions use Big Data solutions to analyze commercial loan origination, developing scorecards and scoring, and ultimately improving accuracy as well as optimizing price and risk management.

3. Risk Concentration Identification and Management:
Identify risk concentration hotspots by decomposing risk into customized insights. Clearly see factor contribution to risks and gain allocation consensus through downside risk budgeting.

4. Next Best Action Recommendations:
Make “next best action” an integral part of your marketing strategy and proactive customer care. With analytical insight from Big Data, you can answer such questions as: What approach will get the most out of the customer relationship? Is selling more important than retention?

5. Fraud Detection Optimization:
Preventing fraud is a major priority for all financial services organizations. But to deal with the escalating volumes of financial
transaction data, statisticians need better ways to mine data for insight. Optimization for your current fraud detection techniques help to leverage your existing fraud detection assets.

6. Data and Insights Monetization:
Use your customer transaction data to improve targeting of cross-sell offers. Partners are increasingly promoting merchant based reward programs which leverage a bank’s or credit card issuer’s data and provide discounts to customers at the same time.

7. Regulatory and Data Retention Requirements:
The need for more robust regulatory and data retention management is a legal requirement for financial services organizations across the globe to comply with the myriad of local, federal, and international laws (such as Basel III) that mandate the retention of certain types of data.

India still the Top Destination for Outsourcing

SAP Labs India Pvt. Ltd. in Bangalore
SAP Labs India Pvt. Ltd. in Bangalore

Asian countries, especially countries in South Asia and Southeast Asia, keep on being favored picks among organizations interested in contract out business processes offshore. India remains the top outsourcing destination, with its unrivaled advantages in scale and people skills, said the 2014 Global Services Location Index (GSLI) released by A.T. Kearney. China and Malaysia are second and third respectively.

The GSLI, which tracks offshoring patterns to lower-cost developing countries and the ascent of new locations, measures the underlying fundamentals of 51 nations focused on measurements in three general classifications, such as financial attractiveness, people skills and availability, and business environment.

Distributed since 2004 the GSLI, revealed that leading IT-services companies in India, to whom IT-related functions were outsourced, are extending their traditional offerings to incorporate research and development, product development and other niche services. The line between IT and business-procedure outsourcing there is obscuring, as players offer packages and specialized services to their customers and are developing skills in niche domains.

Furthermore, the GSLI identified a trend of multinationals reassessing their outsourcing strategies, after having aggressively outsourced back office operations in the mid-2000s; it has been noted that some companies are starting to reclaim some of these functions and undertaking them in-house again.

Alternative: SAPGUI for Java

SAPGUI for Java (Linux)

Die SAPGUI for Java bietet eine alternative Zugriffsmöglichkeit auf SAP-Systeme. So ermöglicht die in Java implementierte GUI den Einsatz von Clients mit unixoiden Betriebssystemen. Aber auch Windows-Anwendern würde ich raten einen Blick auf das plattformunabhängige Frontend zu werfen.

Im Vergleich zur klassischen SAPGUI for Windows ist das generische Java-Pendant nämlich äußerst ressourcenschonend und platzsparend (ca. 90 MB Festplattenplatz). Dafür müssen im Gegenzug auf Gimmicks wie Screen Painter und MS Office-Integration verzichtet werden. Letzteres habe ich bisweilen nicht vermisst. 🙂

MS SQL Server: ETL mit Data Transformation Services

Screenshot von SQL Server Enterprise Manager mit SAP MaxDB
Screenshot von SQL Server Enterprise Manager mit SAP MaxDB

Kürzlich stand ich vor der Herausforderung einen Datenbestand von einem Datenbanksystem (SAP MaxDB) in ein anderes (Microsoft SQL Server) zu überführen. Das Unterfangen war manuell jedoch kaum zu realisieren, da die Datenbank mehrere hundert Tabellen und unzählige Datensätze umfasst.

Abhilfe schaffte der Microsoft SQL Server Enterprise Manager. Dort finden sich die Data Transformation Services wieder, Hilfsprogramme, die es erlaubt, ETL-Prozesse (Extract, Transform, Load) beim Import in oder Export aus einer Datenbank zu automatisieren. Dabei werden verschiedene Datenbanksysteme unterstützt, sofern diese über eine ODBC– oder eine OLE DB-Schnittstelle verfügen, was auch bei SAP MaxDB der Fall ist.

Konkret bestehen die Data Transformation Services (DTS) aus folgenden Komponenten:

  • DTS Import/Export Wizard: Assistenten, die es erlauben Daten von oder zu einem MS SQL Server zu übertragen, sowie Map Transformations ermöglichen.
  • DTS Designer: Ermöglicht das erstellen von komplexen ETL-Workflows einschließlich event-basierter Logik.
  • DTS Run Utility: Planung und Ausführung von DTS-Packages; auch via Kommandozeile möglich.
  • DTS Query Designer: Eine GUI für das Erstellen von SQL-Abfragen für DTS.