At a Glance

Title: Network Science

Target Audience: Students, Researchers, Professionals in the fields of Network Theory and Science

Topic: Network Theory and Science

Author: Albert-László Barabási

Language: English

Pages: 498

Price: approx. 52 Euros (Hardcover Edition)

Positive: Comprehensive overview of Network Science, profound analysis and research

Negative: very complex, abundant content, steep learning curve

Buy: Amazon

Read: Website / PDF

In Detail

Albert-László Barabási, a renowned scientist in the field of network research, has created a comprehensive work with his book “Network Science” that offers profound insights into network theory and its diverse applications. As the Robert Gray Dodge Professor of Network Science and the Director of the Center for Complex Network Research at Northeastern University, with positions at Harvard Medical School and Central European University in Budapest, Barabási brings rich expertise to this book.

The book “Network Science” covers a wide range of topics, from physics to computer science and engineering to economics and social sciences. It is richly illustrated and offers an innovative design to make network theory accessible to an interdisciplinary audience. It addresses, among other things, the origins of the theory of six degrees of separation, explains the robustness of networks against random failures, and explores how viruses like Ebola and H1N1 spread. Moreover, it discusses why our friends, on average, have more friends than we do. The book utilizes numerous real-world examples and offers extensive online resources, including videos and software for network analysis.

In terms of strategy development and strategic thinking, the content of the book can be particularly enlightening. The understanding of the structure and dynamics of networks that the book conveys can be of great benefit for developing data strategies. A specific example is the opportunity for companies to apply the principles of network theory to analyze and optimize organizational structures. This can help dismantle silos, promote collaboration, and create a more efficient organizational structure. Understanding how information or viruses spread in networks can contribute to developing effective communication strategies.

The book is aimed at a wide and interdisciplinary audience, including professionals from physics, computer science, engineering, economics, and social sciences. It is suitable for managers who want to understand the dynamics of networks in organizations, as well as for non-specialists who want to engage with the topics of networks, strategy, and data-driven future.

The main theme of the book is unmistakably the science of networks. It distinguishes itself from other books on a similar topic by its interdisciplinary approach, comprehensive treatment of a variety of topics, and the provision of extensive online resources. The clear distinction between material for undergraduate and graduate students, as well as the inclusion of mathematical formulas and derivations, make it a versatile and valuable companion for anyone interested in network science.

In conclusion, “Network Science” by Albert-László Barabási is a groundbreaking and comprehensive work that offers profound insights into the complexity and dynamics of networks. It is a valuable resource for anyone wishing to apply this knowledge in various fields, especially in the development of corporate and data strategies.

This text was created with the help of ChatGPT.

At a Glance

Title: Networks, Crowds, and Markets: Reasoning about a Highly Connected World

Target Audience: Students, Scientists, Professionals in the fields of Economics, Sociology, Computer Science, and Applied Mathematics

Topic: Networking of modern society and its impacts on social, economic, and technological worlds

Author: David Easley and Jon Kleinberg

Language: English

Pages: 744

Price: approx. 44 Euros (Kindle Edition) | approx. 62 Euros (Hardcover Edition)

Positive: Interdisciplinary approach, accessibility to a wide audience, relevance for understanding networks and collective behavior

Negative: complex, partly mathematical

Buy: Amazon

Read: Website / PDF

In Detail

“Networks, Crowds, and Markets: Reasoning about a Highly Connected World” by David Easley and Jon Kleinberg is a comprehensive work that dedicates itself to the examination of the complex networking of modern society and the associated phenomena. The book combines scientific perspectives from economics, sociology, computer science, information technology, and applied mathematics, to convey a profound understanding of how social, economic, and technological worlds are interconnected.

The book is divided into seven parts and addresses a variety of topics, including graph theory in social networks, games, markets and strategic interaction in networks, the World Wide Web, network dynamics, population models, and institutions and aggregated behavior. It explores how networks, incentives, and the aggregated behavior of crowds interact in different contexts and discusses specific topics like link analysis, PageRank, web search, sponsored search markets, network effects, information cascades, and power laws.

The book is written at an introductory level and is aimed at students of various disciplines, interested in networks and their impact on society. It doesn’t require any formal prerequisites and is therefore accessible to a wide audience, including engineers, especially computer engineers, as well as a broader audience in the social sciences.

With exercises for each chapter and sections with advanced material, the book is excellently suited as a teaching resource. It offers an extensive list of topics almost encyclopedically associated with networks and is therefore a valuable resource for those seeking an introduction to this field.

For strategy developers and entrepreneurs, the book provides valuable insights into the dynamics of networks and markets. It demonstrates how information, social interactions, and economic transactions are intertwined and how decisions can have subtle consequences for others. The concepts presented in the book, especially from the chapters on game theory and auctions, can help understand and analyze strategic interactions and competitive dynamics better. This is essential for companies operating in a competitive market environment and looking to strengthen their position.

The insights from the chapters on sponsored search markets offer practical applications for marketing strategies, especially online. Companies can learn how to optimize their online presence and interact more effectively with potential customers to increase conversions.

The chapter on negotiations and power in networks can aid leaders and managers in understanding the dynamics of negotiations and power relations in network structures. This is particularly relevant for companies engaged in negotiations with business partners, suppliers, or customers and looking to develop effective negotiation strategies.

In addition, the sections on network effects and information cascades allow a deeper understanding of how information and trends spread in networks. This can be beneficial for developing viral marketing campaigns or managing corporate reputation in social networks.

Overall, the diverse topics and concepts of the book offer a plethora of application possibilities for strategy developers and entrepreneurs aiming to optimize their business practices and assert themselves in a networked and dynamic market environment.

The book has a high customer rating of 4.6 out of 5 stars on Amazon and is praised by experts like Daron Acemoglu and Stan Wasserman. It is described as a masterful introduction to networks, combining game-theoretical and algorithmic approaches to investigate social, economic, and communicative networks.

“Networks, Crowds, and Markets: Reasoning about a Highly Connected World” is an outstanding and versatile work that covers a wide range of topics and provides a solid introduction to the world of networks. It is not only of great value for academics and students but also for practitioners, strategists, and entrepreneurs, who want to understand and apply the principles and dynamics of networks in practice. With its clear structure, interdisciplinary approach, and practical relevance, it is an indispensable tool for anyone dealing with the diverse aspects of networks, crowds, and markets.

This text was created with the help of ChatGPT.

AI technology can boost the ways businesses operate today. And after seeing people and companies explore the options of Generative AI for a while. Now businesses see the potential to improve efficiency, productivity, quality, innovation and more. Especially when it comes to

• Automating tasks
• Optimizing processes
• Enhancing decision-making

To overcome the barriers of scale especially small businesses and entrepreneurs need experts they understand AI and data strategy to translate the company’s business goals into valuable and data-driven actions.

Going Full AI In, Comes With Challenges

Besides the typical questions which come with a decision to use AI technology on business like

• How can I identify the most valuable use cases?
• How can I improve quality and availability of their data?
• How can I enhance my learning and innovation capabilities?

Generative AI can also pose some challenges and risks for data strategy, such as ensuring the accuracy, reliability, and ethics of the generated data or content; protecting the intellectual property and privacy of the data sources; managing the complexity and uncertainty of the generative process; and aligning the generative outcomes with the business.

To manage these challenges, here our 3 touchpoints you should focus on to tackle the risks:

1. Let value be your guide: Focus on what value you want to create with generative AI for your business, rather than what you can do with it.
2. Focus on key points of the data life cycle: Ensure high quality of all data throughout its life cycle.
3. Develop multiple interventions: Use both human and automated methods to ensure the quality of all data.

How Can I Get Started With Generative AI?

That’s where the Generative AI Canvas comes in handy. The Generative AI Canvas is a free framework developed by Datentreiber in collaboration with the Foundation Factory.

It helps you to explore the possibilities of generative AI by providing three starting points as a source of inspiration:

• Input
• Function
• Output

The input can be any type of data that you have or can access, such as text, images, audio, video, or code. The function can be any action that a generative AI can perform on the input data, such as extraction, filtering, anonymization, enhancement, detection, prediction, summarization, explanation, or transformation. The output can be any type of content that you or your customers want as a result of the generative AI process.

Meet Afke Schouten Our AI Strategy Consultant

Afke Schouten, one of our talented experts at Datentreiber, defines her mission as

“I am on a mission to help companies generate true value with AI.”

Her primary objective is to equip stakeholders at every level, from board members to data scientists, with the necessary AI, and AI Management knowledge and skills they need to generate value for their organization.

She is an experienced Data Scientist, Corporate Trainer and University Lecturer. She will guide you through the challenges and opportunities which come with AI and helping you translate your objectives into an AI Strategy for your company.

Follow Afke on LinkedIn

We Pave The Way To Your AI Strategy

If you are new to the Canvas Framework or need assistance transforming your company with AI technology? We are happy to guide you in planning and implementing a successful data-driven AI strategy for your company. We also provide the tools and methods to enable your employees to drive AI initiatives on their own.

Remember what you were doing on November 30, 2022? For many, it was the “iPhone moment of artificial intelligence”: the company OpenAI released the first version of its chatbot ChatGPT, making generative AI available to a broad public – just as Apple ringed in the age of smartphones with the iPhone. But the success of ChatGPT is even more remarkable than that of the iPhone: Within five days, one million users signed up and just two months later there were 100 million users. This made ChatGPT the fastest-growing application of all time.

What Is Generative AI?

ChatGPT is just one example of a new category of AI applications: generative AI. Previous AI systems are exclusively analytical: they dissect huge amounts of data and find relevant information in the data. One example is recognizing people in video data.

In contrast to analytical, generative AI enables new content to be generated, such as videos featuring a specific person. To do this, machine learning processes analyze a great deal of training data – in the case of ChatGPT, according to the chatbot’s own statement, it was 570 GB of text data – and create a so-called “foundation model” from this. The underlying model of ChatGPT is called “GPT” (for “Generative Pre-trained Transformer”).

This model serves as a basis to perform many different tasks: Summarizing texts, answering questions, or even writing poetry. Other AI systems, however, specialize in image & video data: for example, DALL-E generates realistic photos. This enables new use cases, such as fake videos, which politicians and others increasingly fall victim to. But generative AI doesn’t just cause problems – it also creates new opportunities, especially for companies.

What Is the Generative AI Canvas?

To explore these possibilities, Datentreiber has developed a canvas in collaboration with the Foundation Factory: the Generative AI Canvas. As a visual collaboration tool, the Generative AI canvas is part of the Data Strategy Design Kit and, therefore, freely available under a Creative Commons license. Interdisciplinary teams consisting of AI, IT & business experts can use the canvas to develop application ideas for generative AI in a collaborative workshop – for example, in a Data Thinking Workshop using the Data Strategy Design method or in an AI Use Case Ideation Workshop (more on this at the end of the article).

You can download the canvas as a PNG or PDF file and print it yourself or use it on a virtual whiteboard. Alternatively, you can order a pre-printed version on synthetic paper in DIN A0 format from Stattys. All versions look the same, as follows:

The Use of the Canvas Is Quickly Explained and Learned:

• On the left side under Input, you list your available data sources, distinguishing them by data type. These data serve as input for the generative AI to generate an output.
• On the right side under Output, you gather ideas for what a generative AI could generate in terms of content based on the input and what the company or its customers desire.
• In the middle, under Function, you consider which functions an AI could or would have to perform on the input to generate the respective outputs. Possible AI operations can be roughly divided into categories such as recognition & prediction or conversion & translation and can be combined as desired.

The categories under Input, Function, and Output serve as a source of inspiration. Further information on them can be found in the text on the canvas (PNG with text, PDF).

What Can I Do With the Generative AI Canvas?

To understand the potential of Generative AI and the use of the Generative AI canvas, we created examples in Miro – a well-known virtual whiteboard software. You can view the Miro examples here without logging in or downloading the software.

Example 1 of 6

We’ll start with a simple example: our fictitious company, the Sad HiPPO Company, has lots of software code programmed – but hardly documented. This is where a generative AI like ChatGPT can help by creating documentation for the code:

Example 2 of 6

An AI could also fulfill multiple functions, that is, operations on the input data executed in sequence. For example, the Sad HiPPO Company could use an AI solution to anonymize images:

Example 3 of 6

An AI system can produce multiple outputs on the same inputs by performing different functions. Based on drawings of buildings, the Sad HiPPO Company could firstly generate photo-realistic images and secondly create a 3D model of the building. The result of a brainstorming session with Canvas would then look like this:

Example 4 of 6

Also, different input can be combined to generate “fake videos”, for example:

A realistic use case for such fakes is that Sad HiPPO Company wants to protect the identity of the people on the videos.

Example 5 of 6

There are no limits to your imagination when developing application ideas: the Generative AI Canvas makes it possible to map even complex functions, such as an AI for image editing via text input:

Example 6 of 6

And even so-called multimodal AI solutions are conceivable or designable. A multimodal AI is able to process and output different data modalities (data types). The following example is taken from a demonstration video for GPT-4 – the fourth and multimodal version of GPT – and shows how GPT generates the appropriate code and images from a line drawing of a website:

How Do I Get Started With the Generative AI Canvas?

The AI Foundation and Datentreiber have developed an interesting workshop format, especially for companies: during a four-hour Generative AI Use Case Ideation, we work with you and your team to identify the use cases relevant to your business and determine the next-best project to demonstrate the benefits of Generative AI for your company. The workshop can take place onsite at your premises or online in Miro, for example.

Our certified experts will guide your team safely and purposefully through the agenda:

1. The workshop will start with a keynote speech by the well-known AI expert Prof. Dr. Peter Gentsch on the opportunities & risks of generative AI.
2. Using interactive examples with ChatGPT, DALL-E & Co. you will then learn practically about the potentials of Generative AI.
3. We then jointly analyze your business model or your critical business processes or focus on the needs of your customers.
4. To then create application ideas for Generative AI – under the guidance of the Datentreiber experts.
5. Finally, we evaluate the use cases by cost-benefit ratio and select the next-best project.

During the implementation of the project, the AI Foundation and Datentreiber are of course also available to provide you with advice and support. We are at your disposal for a personal conversation.

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Boyan Angelov is not only a Data Strategist, but also a successful Author and Data Strategy Consultant. We meet Boyan in a restaurant in Berlin. While we enjoy our meal, we conduct a short but exciting interview with the absolutely likeable “data nerd”.

Who are you and what do you do?

My name is Boyan Angelov. I am an Author, Data Strategist and Data Strategy Consultant. Originally from Bulgaria, I now live near Berlin.

I studied biology in Bremen and then came to bioinformatics via biochemistry. That’s also where I met my wife and we started a family very early. So nine years ago I started working as a Data Scientist. I didn’t have time to do my doctorate. As they say, “We were young and needed the money.”

I was able to use my skills at various Berlin and Amsterdam start-up companies and later became CTO (Chief Technology Officer). It was a valuable experience where I learned a lot about people and improved my leadership skills.

When were your first contacts with Datentreiber?

I gave a workshop on data strategy in Miro and Martin Szugat commented on it. Miro is an online collaboration tool that I have been very excited about for a while. We got to talking and I learned about the Data Strategy Design method of Datentreiber. The method totally excited me from the start because it gives the strategist a practical tool that makes creating a data strategy absolutely logical and almost easy.

What is the best thing about the Data Strategy Design method?

The canvases are absolutely unique, whether used in print or online, for example in Miro. In addition, everything is freely available to everyone under a Creative Commons licence. Sure, we have to mention Datentreiber as the source, but that’s all. The method is always being developed further and anyone can use it. Many more people around the world should know and learn this method.

Your second book “Elements of Data Strategy” was published at the end of January. Would you like to tell us a little bit about it?

“I wish I had this book when I started, and I hope it helps a new generation of Data Strategists!” – Boyan Angelov (Author, Data Strategist & Consultant)

When I started working as a Consultant designing data strategies for companies, there wasn’t much reading on the subject. There were some books, but most of them didn’t have a method and after reading them, you weren’t any smarter than before. Actually, I wrote this book because I wished I had read such a book when I started working in this field. Critics might say that I don’t have much experience myself. However, the interviews with very experienced experts in the data scene are the core of the book. The book not only contains my own experience, but also a lot of concentrated superpower from greats like Nicolas Averseng, Noah Gift, June Dershewitz and many more. A highlight is the interview with Datentreiber Martin Szugat. He brings much of his years of experience as a Data Strategy Consultant to this book. The book also describes all common methods and explains them to the reader.

How long did it take you?

The book was already finished in 1.5 years. As I said, I had always wanted to have a book like this and had already prepared many elements. In the end, it turned out to be over 300 pages. I printed the book myself. That way I am as flexible as possible and have everything in my own hands.

For whom have you written this book?

The target group of the book is not the people on the technical side and also not those on the business side. Actually, it is exactly those in between, who translate and mediate between both worlds, just as we consultants do.

What drives you personally?

I enjoy life with my wife and our three children in the Berlin outback. Far away from the hustle and bustle of the big city, it’s a good place to live. The kids are 9, 6 and 4 years old. Sometimes it’s like a little kindergarten at home.

Last question: Explain to your children what a Data Scientist or Data Strategist does all day?

I do something with robots. I teach them what they can then do. Like you, the robots are always learning and gaining new skills day by day.

Thank you very much for this wonderful interview.

Title: „Elements of Data Strategy: A Framework for Data and AI-Driven Transformation”

Target group: CDO, CTO, Head of Data & Management Consultants

Subject: A toolbox for all data strategists. The book “Elements of Data Strategy” defines the required components, their relationships and the plans for carrying out the required activities.

Author: Boyan Angelov (LinkedIn)
Language: Englisch
Pages: 334

Price:
19,70 € (Amazon as paperpack)
20,99 € (Amazon as Kindle Edition)

In short: A practical toolbox that shows all the components, relationships and plans needed to implement and create a data strategy.

In detail: Elements of Data Strategy defines the components needed, their relationships, and blueprints for conducting the required activities. The 3D model—Due Diligence, Design, and Delivery— is at the core. These three phases ensure that the data strategy is informed, complete, and operational. Interviews with data strategy leaders worldwide from organizations such as Amazon, Publicis Sapient, Duke University, Deloitte, and others, provide additional guidance.

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The Path to Data Strategy

The digital transformation has now arrived in all branches. Data is one of the most important corporate resources. If you analyze data correctly and, above all, analyze the right data, you will gain important insights for your business decisions.

In order to use data profitably in a company, a well-founded data strategy is needed. Digital skills and trained employees are the decisive factor for economic success.

We have been successfully using the Data Strategy Design Method we developed in our consulting projects for many years. It is a visual innovation method based on the Design Thinking approach. With the help of the so called Canvas (visual collaboration tools), you can explore your data landscape, identify relevant applications and develop a plan to increase your analytical maturity.

Learning Method

In our open training courses, you will learn the method of data strategy design. Additionally, you will gain valuable insights from the practical experience of our clients. After our seminar, you will be able to independently develop and implement your data strategy. All of the canvas tools we use are open source and therefore freely and freely available.

• In the seminar “Data Strategy & Culture”, you will learn all about the possibilities of data-driven business models and processes.
• The “Data Design Thinking” seminar is a follow-up seminar to “Data Strategy & Culture” and shows you how your company can successfully identify, design and implement successful data science and analytics projects using the data strategy design method.
• The “Data Business Consulting” seminar is the right choice for you if you already have a solid understanding of analytics and data science and are already familiar with our method. We will show you the right tool to develop data-driven business models and processes together with your team or your clients.

Current Schedule

Presence events in the mountains

We are drawn back to the mountains and invite you to join us. We offer presence seminars in the form of 2-day seminars in the Bavarian foothills of the Alps in Weilheim i.OB.

15.-16.05.2023: Presence Seminar: Data Strategy & Culture
19.-20.06.2023: Presence Seminar: Data Design Thinking
18.-19.09.2023: Presence Seminar: Data Business Consulting

Online Trainings

Already at the beginning of the year, we have planned the trainings for you again as online trainings. These will take place on five Fridays from 10 a.m. to 3 p.m. (plus a housekeeping appointment).

20.01.|27.01.|03.02.|10.02.|17.02.|2023: Online Training: Data Design Thinking
21.04.|28.04.|05.05.|12.05.|19.05.|2022: Online Training: Data Business Consulting
06.10.|13.10.|20.10.|27.10.|10.10.|2023: Online Training: Data Strategy & Culture
17.11.|24.11.|01.12.|08.12.|15.12.|2023: Online Training: Data Design Thinking

On-site Training with Datentreiber 

Our training courses are available as individual online, on-site, and off-site events for your company. The employees will learn the most important methods and tools to independently leverage the company’s data for commercial purposes. We are happy to create an offer for you.

Ongoing Online Training 

In collaboration with our partner Stackfuel, we currently offer a continuing education online training course to expand your data competency through the membership learning platform. The content of data literacy, AI literacy, data-driven management, AI-driven management, data storytelling, and more is available to you anytime and anywhere. An entry is possible at any time. If you or your employees are interested, we can offer you special Datentreiber conditions. The quota is limited. Write to us to receive more information.

January 2022

How do I find and choose the best AI use case in the process and manufacturing industry? Martin Szugat gives you advice on this topic in the Industrial AI Academy from NNAISENSE. Employees in the manufacturing industry can request free access by emailing Ralf Haller.

February 2022

In January and February, we proudly and happily certified further data strategy consultants according to the data strategy design method. The experts accompany our clients with our unique method, common values and each with very specific expertise.

March 2022

Pierre-Philippe Mathieu and team members from the European Space Agency (ESA) gave an overview of the current successes and challenges of AI for space applications and presented some methodological use cases at the Data Brain Meetup.

Datentreiber expert Martin Szugat was a guest at the 2nd International Summit for Industrial AI Applications of our partner NNAISENSE. The event took place remotely for the second time and Martin gave a presentation titled: “How to Find Industrial AI Business Cases”.

Our Marketing Manager Catarina Gryska has been successful at Datentreiber for one year. Many valuable moments lie behind her. She is proud to be a team member of Datentreiber. In the interview, she describes her experiences and personal highlights in her first year in the position.

April 2022

Successful AI applications require high data quality, which in turn requires a clear data strategy. Martin Szugat reveals how companywide data strategies lead to successful AI projects in the article Planungssache in the iX magazine published by Heise Verlag.

Martin Szugat gave a talk at the AI Meetup in Frankfurt on how to design successful AI products. Afterwards, Gabriela Cortes from Amazon gave insights into the world of Alexa. The AI Meetup is organised monthly online by the AI Lab of Frankfurt School of Finance & Management.

A new member in our network since February is Philipp Baron von Loringhoven, whom we would like to introduce to you in our blog. Philipp is a marketing specialist who knows a lot about digital analytics and marketing automation in combination with data science.

May 2022

Companies often confuse data strategy with data architecture. The participants of the amexus event learned more about this during Martin Szugat’s presentation: Design Thinking for a value-oriented and user-centred data strategy.

Marketing is no longer possible without it: the marketing data strategy. You can learn interesting facts about this in this podcast episode of DataEngage. Datentreiber expert Phillip Baron von Loringhoven talks to Martin Szugat about what a good data strategy is and where and how it helps in marketing.

June 2022

Data governance is a difficult subject to explain. There is no standard definition and this often leads to mistrust in the topic. Since a standardised language is enormously important, the Datentreiber expert & managing partner of iDIGMA GmbH reveals the definition and much more in this interview.

At the Datendinner in Munich, the participants enjoyed short impulse presentations. Christian Gersmeier from the Seven.One Entertainment Group was one of the speakers who got the conversation going with his talk: How can we prove the uplift of digital marketing on TV ratings?

July 2022

Our expert group meeting took place in Kochel a. See at the beginning of July. The purpose of the two-day meeting was for all experts to get to know each other personally, to further develop our method of data strategy design and to work on our own strategy in a workshop.

Since 1 July 2022, there has been another managing partner alongside Martin Szugat: Georg Arens. Georg brings over 30 years of experience in data projects. In the interview, he reveals what the right start is for companies that want to become data-driven.

Because the participants and the Datentreiber team enjoyed it so much last year, a hike with the participants of the open Data Design Thinking training took place again this year in July. This year we went together to the Herzogstand with summery temperatures.

Our data strategy design method is used worldwide. Data specialists from Germany, Austria, Switzerland, the Netherlands, the UK, France, the USA, Russia, Peru, Mauritius, Brazil and Morocco use it. In the summer, she travelled to the USA again with Datentreiber expert Georg Arens.

August 2022

Martin Szugat describes in the article in iX – magazine for professional IT from heise online how you too can make good use of data in your company with the method developed by Datentreiber & make a significant contribution to the success of your company: Data Thinking: mehr Wert aus Daten ziehen.

September 2022

How is a data strategy currently understood and practised in companies? This is what a study in the research seminar “Challenges in Digital Technology Management” of the Faculty of Business Administration at the University of Applied Sciences Munich has now found out.

Typical marketing questions: What is the benefit of which channel? Where should I invest? How can we achieve our sales goals together with sales? In this article, Datentreiber expert Lutz Klaus writes about an effective tool for answering these questions: KPI driver trees.

October 2022

The conferences Predictive Analytics World for Industry 4.0, for Healthcare & for Business took place at the same time as Deep Learning World from 5 to 6 October 2022 in Berlin. While Martin Szugat led through the programme, Georg Arens used the time at the stand for intensive networking also with the speakers.

The Datendinner took place among our customers at the Früh am Dom in Cologne. This time, Nora Reich (Product Owner Big Data & Artificial Intelligence, KfW) and Kai Schlolaut (Digital Marketing Data Analyst & Global Digital Marketing, Weleda AG) gave short keynote speeches between the courses.

November 2022

In the fully booked Data Design Thinking online training, participants learned how to design and implement successful data strategies and projects. The online training Data Business Consulting continued at the end of the month. Further dates for 2023 have already been set.

In this interview, Datentreiber expert Sarah Stemmler tells us where companies need to start if they really want to become data driven and why a strategy can only be effective if it is accompanied by a good culture. Sarah also introduces the recently launched Tech Leaders Academy.

December 2022

At the beginning of December, we at Datentreiber are curious and want you to answer two short questions. There is also something to win. We are giving away 10 licences of StackFuel Membership, an in-service online training course for the data & AI sector, to all participants.

For each training or workshop, we planted a tree in 2022. With the PLANT-MY-TREE® initiative, we have chosen a mixed forest. Together with our customers, we are making the world a good bit greener and compensating for our CO2 consumption.

We wish you a good conclusion for the year 2022 and are already looking forward to a successful year 2023 together!

May the data be with you.

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We visit Sarah Stemmler in beautiful Passau. Shaped by a centuries old history and the developer spirit that can only be attributed to a student city, ideas and progress are constantly flowing in this Bavarian city alongside three rivers. Sarah has been at home here since 2013 and founded synsugar GmbH six months ago together with her partner Sebastian Henneberg. Before that, Sarah had already been working as a freelance data consultant for two years. In the interview with Datentreiber, she tells us where her enthusiasm for the world of data comes from and how she became aware of Datentreiber.

Who are you and what do you do?

I am Sarah Stemmler and a former Data Scientist. I started my own business as a data and analytics consultant in 2020. In May of this year, we founded synsugar GmbH. We are my partner Sebastian Henneberg and me.

In the beginning, in addition to my consulting work, I was still processing and analysing data in projects. I needed this mix to orientate myself and to recognise what is really important to me personally. At that time, I intensively studied the topic of data strategy and thus became aware of Datentreiber. In the data strategy design method, data analytics topics and design thinking are combined. This is enormously effective and exactly my thing.

Besides consulting, Sebastian and I share another passion: teaching, training or developing people. In the summer of this year, we made this idea concrete. Because we want to inspire and qualify more tech experts for leadership tasks.

Are you talking about the recently launched Tech Leaders Academy? The LinkedIn community was eagerly awaiting it.

Yes, exactly. In the Tech Leaders Academy, which is a product of synsugar GmbH, we pursue precisely this goal. For years, we have experienced that teams or experts and there are no exceptions, “techies” only perform well with very good leadership. A tech expert is not the same as a good leader, even if he or she is often expected to fill this role at a young age.

What exactly does the programme look like?

We offer the young leaders a 6 week on the job course. Every week there is an interactive workshop, individual coaching complements everything and practical tasks in your own company ensure that you can apply or try out what you have learned.

Of course, the exchange within the group (approx. 10 – 12 people) is also beneficial for everyone. We all know the feeling that only we are dealing with certain issues. Often, many people struggle with very similar challenges in their daily work and, at best, have already developed effective solution strategies. We want to bore as little as possible with theory, but motivate people to take action and dissolve any fears that may arise.

Sebastian and I will share our experiences as team leaders, from consulting and self-employment in this area with the participants. Together with other strong role models who embrace modern leadership, we will help the young talents to get ahead. Those who register this year can still benefit from our launch price of 1,850 € without and 2,600 € with individual coaching.

When was your first contact with the world of data?

  When I came to the beautiful city of Passau in 2013 for my Master’s degree in business administration, there were several compulsory subjects, including statistics. So I was forced to deal with data. I quickly found it very exciting and inspiring, as I felt it was like a practical tool. From the second semester onwards, I enthusiastically attended the statistics lectures and seminars. For my master’s thesis, I was then given data and allowed to analyse it. It was about online purchase data from a food manufacturer. I analysed it to see if online purchasing behaviour in Berlin differs depending on the district or milieu.

What is your secret superpower?

I am bridging the gap between the data side and the business side. Someone who understands both sides is also called a data translator. My strong empathy for people helps me understand the very different areas. Among other things, I can read people so well because I have been active as a mentor for a very long time and have coached and developed many people. What always gives me a lot of pleasure is to bring people from outside the field, who have had little contact with data and AI topics, closer to this area.

What makes you a Datentreiber expert?

We Datentreiber experts drive our clients forward. In a nice way I can force our customers to their success. In addition to my very strong strategic and analytical way of thinking, I have a sympathetic power of perseverance and can thus motivate our customers to achieve their best performance.

How do you contribute to the business success of our customers?

I focus on the essentials. As a good consultant does, I help them to help themselves. We don’t want to accompany our clients for a long time or implement their projects for them, instead we help them to set a framework. The Data Strategy Design method is a powerful tool for this. The first turnaround is to look at the usability, or the user of the technical solution. Many want to overwhelm everything with technology and lose sight of the human being, who in the end either buys or uses the solution. Towards the user perspective, for example with the help of the Analytics Use Case Canvas.

Is the Analytics Use Case Canvas your personal favourite?

In fact, yes. When I was still on the technical side, I did exactly that wrong. Instead of starting with the user, I thought of great technical solutions that either had no benefit or were not accepted by the user. Now I start on the right side and think first: What is the user’s problem? I try to find the solution to the problem from the user’s point of view (non technical/analytical) and then concentrate on the solution and what benefit it has for the user.

What have been the learnings that you have drawn from the customer projects so far?

After I was certified as a Datentreiber expert in February 2022, I got the chance to work on a very complex project together with Georg Arens and Martin Szugat. Here I learned that sometimes we have to start much farther up front. First of all, we have to initiate a change in thinking within the company and the culture has to follow suit. What is a data strategy? Why do we need it? A statement that Martin quotes again and again: “Culture eats strategy for breakfast“. I agree with that 100%. If a company is not ready for change, even with the best method and the best tools, it will only move forward in very small steps. However, a well structured method such as Data Strategy Design and the Canvas tools help enormously to make a difference.

What is your tip for companies that want to become data-driven?

A lot of experimentation, rather small loops than a big project in which all the energy and power is spent and then just get going. It’s an advantage if you already know where the journey is going and have already taken the first steps. If you get stuck, we are there immediately to offer support and guidance.

What is it that drives you personally?

I want to collect as many museum days as possible and am therefore a great fan of change, further development and variety. Anyone who knows the bestseller “Big Five for Life” by John Strelecky knows what I’m talking about. It’s about collecting as many moments or experiences in life as possible so that you can look back on wonderful things at the end. For me, that can be an exciting day at work or a beautiful day in the mountains. I choose very well what I spend my time on. I always focus on the things that are particularly important to me.

Thank you very much for this wonderful interview. It is an honour and a pleasure to work with you to drive our clients forward.

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At a Glance

Title: Elements of Data Strategy: A Framework for Data and AI-Driven Transformation

Target Audience: CDOs, CTOs, Head of Data, Management Consultants, and all professionals responsible for value creation from data initiatives.

Topic: The book addresses the design of a data strategy for an organization and provides a framework for data- and AI-driven transformation.

Author: Boyan Angelov

Language: English

Pages: 317 pages

Price: approx. 9 Euro (Kindle Edition) | 18 Euro (Paperback Edition)

Pros: Comprehensive framework, Practical applications, Expert insights, Clear presentation.

Cons: Somewhat technical, Potentially overwhelming for beginners.

Purchase: Amazon

In Detail

The book “Elements of Data Strategy: A Framework for Data and AI-Driven Transformation” by Boyan Angelov is not just another guide to data strategy but an essential reference for executives and data experts. It serves as a compass for CDOs, CTOs, data leaders, and management consultants looking to navigate the complex world of data- and AI-driven transformation.

Boyan Angelov, a renowned data strategist, brings over a decade of experience from diverse fields – from bioinformatics and clinical studies to HRTech and LegalTech. His broad spectrum of experiences in both academic and business environments, combined with his active participation in scientific projects and regular lectures at international conferences, establishes him as an authority in this domain.

The centerpiece of the book is the 3D model, consisting of the “Due Diligence”, “Design”, and “Delivery” phases.

• Due Diligence: This phase is about understanding the business strategy and aligning with it. Current systems are audited, data maturity is evaluated, and a gap analysis is performed to determine the current state of the data strategy in comparison to the objectives.

• Design: Here, the necessary data products are designed. This includes ideation, feasibility studies, and prioritization of data projects. The target data architecture and the required technology are also determined. In addition, data governance structures and an operational model for the data organization are developed in this phase.

• Delivery: The Delivery phase is about implementing the data strategy. Here, agile methods like “Soft Agile” and “Lean Data” are introduced to make swift progress without wasting too many resources. Various methods for value creation are also introduced, such as DataOps and MLOps.

Angelov emphasizes that an effective data strategy requires not only technical know-how but also careful planning, thoughtful design, and efficient implementation. He delves into each of these phases in detail, outlining the necessary components, their interactions, and concrete steps for implementation. To further enrich the reader, Angelov integrates interviews with leading data strategists from global organizations, including heavyweights like Amazon, Publicis Sapient, and Deloitte. These firsthand insights provide not only theoretical but also practical perspectives on the challenges and best practices in data strategy.

Critics particularly praise the book for its comprehensive framework and the wealth of practical examples. However, some pointers suggest that the technical depth might be overwhelming for newcomers. Yet, it’s precisely this depth that makes “Elements of Data Strategy” an indispensable tool for professionals aiming to develop a robust and future-proof data strategy.

In conclusion, “Elements of Data Strategy: A Framework for Data and AI-Driven Transformation” is a must-read for anyone looking to master today’s data landscape and seize the opportunities of tomorrow.

This text was created with the help of ChatGPT.

Who are you and what do you do?

I am passionate about sailing and have been helping clients navigate with data for over 30 years. Since 2015, I have focused entirely on the topic of data strategy and have worked closely with Datentreiber ever since. However, the connection with Martin Szugat has existed for a longer time. We got to know and appreciate each other more than 10 years ago. At that time, I had just started my own software company and really appreciated the exchange with Martin about Social CRM and similar topics. What can I say? The need for Social CRM was “manageable” at that time, but the need for data consulting was huge.

How did you get into the topic of data?

The topic of data has accompanied me from the very beginning. I studied computer science with a focus on database systems and then worked for many years for American software companies such as MicroStrategy or IBM in the BI, data warehouse and analytics area. Along the way, I actually filled all roles from developer to managing director. In addition, I founded companies, e.g. in the field of data engineering, and managed them successfully or with great learning effects.

I find the trend exciting that the Big Data hype is probably over and people are thinking about data modelling again instead of believing in magic in the data lake. Something similar is also happening in the field of AI and the often exaggerated expectations of statistical methods, whether predictive models or fully automated prescriptive AI, are being corrected.

The Datentreiber managing partners Martin Szugat (right) and Georg Arens (left)

What is your core competence?

Let’s put it this way: as a sailor, I can read a sea chart and know the weather forecast. I then know where the shallows are, how high the waves are likely to be and from where the wind is blowing and how strong. Translated, this means that I can really understand everyone involved through over 30 years of experience with data projects. I know the technical side well and know what a data architecture should look like, and at the same time I also understand the requirements and challenges of the business or management side. It is therefore easy for me to create a common understanding here. I am also very familiar with the processes of large corporations, as we often advise them at Datentreiber, due to my past.

What makes Datentreiber so exciting for you?

Datentreiber is the only data strategy consultancy with a method. The Data Strategy Design method sets us apart from all other consultancies. We have a structured approach to designing a data strategy. We give our clients a framework for thinking that they can use to get started. We don’t deliver PowerPoint battles that then gather dust in some drawer. Together with our customers, we develop a procedure with concrete measures that make a lasting contribution to the success of the company. The method is suitable for bringing IT, data and business together at one table and creating a common vision. Successful data projects are not made in IT/data alone, but with an interdisciplinary team.

How do you contribute to the business success of our customers?

To describe it in a figure from a study by Michael Kroker that already dates back two years: Data-driven companies increase turnover and profit by 17 percent on average. I help to raise this potential and create innovation with data. It would also be irresponsible for companies not to care about data. To put it more drastically: Either companies do it or they die.

What is your tip for companies that are on the way to becoming a data-driven company?

Do it! Do it! Do it! But don’t start with the data! Sounds illogical at first, but many people consider what data they have first in order to decide what they want to do. That’s putting the cart before the horse and the wrong view. It is important to take a step towards the user perspective. So look at the goals and only then look at what data could be useful to achieve those goals. So forget the data for now and think about what you want first.

What drives you personally?

I started owning a sailboat a few years ago. It’s currently moored in Emden on the Dutch border. I can even work remotely on board. Martin would rather go to space, to Mars or at least the moon. For me, the Mediterranean is enough.

Thank you very much Georg! We look forward to working with you in the future!

Would you also like to meet our new managing partner?

In autumn, you will have the opportunity to attend Predictive Analytics World & Deep Learning World in Berlin in person. Send us an email and we’ll be happy to send you a discount code for the conference or make a short appointment with Georg right here.