Data analytics initiatives

Managing Analytics For Success

Data analytics initiatives have their tricky parts. Combine technical and managerial perspectives and learn a new framework. Apply it to your analytics project, avoid common mistakes, and improve your analytics services. 

Publisher: CRC Press Taylor & Francis Group
Language: English
Number of pages: 168
ISBN-10: 1032302402
ISBN-13: 978-1032302409

About the book

The three-axis approach to analytics projects

The categorisation of analytical initiatives can help you leverage the knowledge you have already gained and reflect it in your work. Correctly defined categories help you to simplify the complex and, at the same time, understand the critical aspects of analytical work. But how can you do that, and what makes it so complex?

Common attributes of analytics projects

Throughout the book, we reiterate that each analytics project is different. At the same time, analytics projects have a lot in common, and these features make them unique compared to other projects. Describing these commonalities can further your conceptual understanding of analytical work. These specific features impact the entire project lifecycle, and neglecting them (trying to use general approaches without tailoring them to analytics projects) can lead to failure.

General areas of risks and challenges

Challenges and risks – another critical aspect of analytical initiatives that could be the same from the overall definition perspective, but the realisation and mitigation may differ significantly based on the previously described project categorisation.

Typical failures and risks per projects types

To provide a more tangible point of view, we look at things from the opposite angle. So far, we have been looking at the typical characteristics of the analytics project (and how to categorise them). Now, we will look at specific types of projects, provide a high-level assessment of their characteristics from a risk perspective (highly generalised), and comment on the most common problems or challenges.

Typical questions for analytics projects

In the last chapter of the book, we will try to provide you with some examples of questions that could be asked of relevant people in order to analyse the project. These questions may help you  position the project correctly on each axis and understand the commonalities and general project challenges. This serves only as an example and may differ greatly based on your company and environment. 

Artefact downloads

Typical questions for analytics projects.xlsx

Typical questions for analytics projects.odt

This book was written thanks to the support of the Data & Business platform and long-term institutional support of research activities by the Faculty of Informatics and Statistics, Prague University of Economics and Business (IP40040).


We are offering three types of trainings to organisations and other groups.

Target audience

Our trainings is intended for anyone keen to understand the complexity of analytics projects, without depending on specific technology. The training can be valuable regardless of whether you have read the book or not. You can start with the book and appreciate going deeper into the selected topics and discussing concrete ideas in the training. Alternatively, start with the insights from the interactive training and enrich the experience with additional details from the book afterwards. 

The three-axis approach to analytics projects

The first one focused mainly on the content from the book’s first part – the definition of a three­-axis Framework. In the four-hour session, we will go over concrete examples from projects to discuss the crucial aspects of the framework. This approach will ensure that you will understand the concepts in deep detail. It will improve your capability to leverage them in real life. 

Commonalities, specifics and risks of analytics projects

The second training expects a basic knowledge of the analytics ecosystem (ideally, Analytics Framework). We will be focusing more on the commonalities and specifics across the different types of analytics projects, comparing analytics projects with the surrounding environment and discussing the risks.


We can customise based on your need or a specific analytics ecosystem. While we know technologies, we are not fans of customising the training to fit a specific technical toolset, as that changes too quickly – however, we can adaptto the analytical principles used in your company.

The typical training participants include

  • Project managers and delivery leads
  • Data engineers, architects, data scientists and other data and analytics professionals
  • Business analysts and product owners
  • Students

Price and location

The price depends on the number of participants, the location (on-site or off-site) and even the mode of delivery (virtual or in-person). Feel free to reach out to us, and we can discuss the details.

Why choose our training?

The training will be delivered by people who actively work in the analytical field (with proven experience). Moreover, they have experience with education and tutoring. We have long-term cooperation with universities, which allows us to provide the best content in the best possible format.

Generally, we try to support as much discussion as possible during the training. You are encouraged to bring your specific situations or examples. We will connect them into the analytical context, which could help you leverage the newly gained knowledge.

How to register

Are you interested in the training? Feel free to contact us! It does not matter whether you are looking for standard training or a customised session – we will try to find a way help you. 

About authors

Ondřej Bothe

Ondřej Bothe

Ondřej has spent his whole life working in analytics. He has worked in many different roles: from hands-on developer to manager leading a team responsible for project implementation and IT analytical landscape operation. He was on the customer side, receiving advice from a consultant, but he has also worn the consultant hat, advising clients on analytical issues across sectors. Thanks to his economic background, he has a unique view of analytical projects. He can combine the aspect of technology, the delivery approach, and an understanding of data with an economist’s perspective to ensure the best possible results for analytical insight consumers. Ondrej graduated from the University of Economics in Prague. Outside of his standard career, Ondrej has worked as a tutor for various educational programmes organized by different entities

Ondřej Kubera

Ondřej Kubera

Ondřej has spent most of his career in IT delivery and consulting, focusing on analytics, including areas such as business intelligence, information management, and data governance. He is passionate about bridging the gap between the business and technical perspectives in the data analytics domain. He graduated from the Czech Technical University in Prague and has experience from a variety of hands-on engineering, as well as client-facing and managerial roles. He has led, designed, and consulted analytics initiatives in major consulting firms, a boutique data intelligence company, and a global pharma company. Most of his analytics projects were international.

David Bednář

David Bednář

David loves data and its presentation, and he has spent most of his career in the analytics area. He benefits from experience from both the academic and the business spheres, where he works on projects that further develop his robust technological background. He is a person who likes to develop anything new and innovative, who can define new architectures and patterns, or lead young talents to growth. David graduated from the Technical University of Ostrava focusing on data management and custom data structures, where he helped with research of multidimensional data structures as a member of the Database Research Group. He has worked for international companies as a business intelligence consultant or architect, mainly focusing on improving solutions with the help of new methods and principles

Martin Potančok

Martin Potančok

Martin supports data-inspired decisions in commercial and research projects. He has experience in software development and analytics. He has worked as a business analyst and project manager on software projects delivering mainly budgeting and reporting systems for international companies. Recently, he has been working as a business analyst on data and analytics projects. At the Prague University of Economics and Business, he is in charge of data activities and research projects organized in cooperation with the Faculty of Informatics and Statistics. Specifically, he has been part of the team organizing the Data Festival, Data & Business activities, and projects to expand business capabilities using IT and analytics. He received the Josef Hlávka Award in 2015 and holds a PhD in Applied Informatics from the Prague University of Economics and Business.

Ota Novotný

Ota Novotný

Ota has over twenty years of practical experience in data and business analytics. He helps people understand the importance and principles of data analytics in both academic and business projects and shows them how to use them in their professional lives. He has already supported thousands of people, helping them familiarize themselves with this modern and increasingly promising area of interest, and a large proportion of them have chosen data analytics as their career path. He is always looking for new ways to harness the potential of data and the associated data analytics for modern business. He is the author or co-author of a number of books, conference papers, and articles in professional journals. Since 2015, he has also devoted his time to the xPORT Business Accelerator, a modern startup business centre at the Prague University of Economics and Business. He has been awarded the Associate Professor degree, as well as a PhD in Informatics at the Prague University of Economics and Business, where he defended his thesis related to the role and deployment of data analytics in corporate governance.