Learn the Data Product Owner Way: Insider Tips and Tricks
From books to movies, here are some sources from which to take lessons and inspiration.
Most companies no longer treat data casually as it is. Instead, it is crafted into a high-quality product that is easily accessible and adaptable to any business challenges.
At DKatalis, data products are handled by data product owners. They are individuals equipped with both technical and business skills to improve the functionality and viability of data products. The owner’s expertise is crucial in selecting the appropriate technology and data architecture, which impacts performance, scalability, user experience, and costs. Correct handling of data sets and the resulting courses of action can determine the success or failure of an organization. Thus, having a knowledgeable product owner who can treat data as a valuable product is essential to unlocking its full potential.
In this article, the DKatalis Data Product Owners, Abi and Nerissa, share their holy bibles for both newbies and experienced data teams seeking to widen their knowledge. Whether your thirst for knowledge can be quenched only by books about theories and practical implementations, or a more casual method like watching movies, we got you covered.
Books
Good learning source goes beyond theory and provides their audience with useful use cases and real-life examples. This book definitely checks all the boxes. Rodrigues explores all the essential concepts, techniques, and tools that combine data science with social science to gain consumer insights. Targeted to audiences just beginning their venture into the world of data science or experienced reader wanting to widen their knowledge, the information and practical samples included in this book will be very helpful.
- Visualizing Google Cloud
Priyanka Vergadia
Started out as visual notes published on GitHub, this book is an easy-to-comprehend and useful handbook for everything Google Cloud. Vergadia scoured thousands of pages of Google Cloud documentation and spent hours experimenting with virtually every Google Cloud product, then distilled that experience down to accessible, bite-sized visuals almost like a comic book. If you’re looking for a quick lesson or inspiration on cloud architecture modelling or experiments, this is for you!
For individuals aspiring towards a career in data engineering or analysis, this is a recommended read! It’s a valuable resource for comprehending the fundamental principles of data architecture, their practical implementation, and their adaptability across various industries and departments. With a wealth of industry experience, Jamesmore’s text illuminates the key decision-making junctures involved in the pipeline implementation process, such as choosing between batch versus streaming data ingestion or deciding whether to build or buy a system.
- Winning with Data
Tomasz Tunguz & Frank Bien
“When dealing with a child, one must think like a child.”
This paraphrase rings as a golden guide when we are trying to comprehend the psyche behind each behavior and motivation. The same rule of thumb also applies when we want to understand what is most important for business, especially when it comes down to leveraging data-driven decision-making in profit organizations. The book covers a wide range of topics, including data collection and analysis, visualization, machine learning, and the importance of data culture. It provides practical advice and real-world examples from the authors’ experiences in the industry, making the book accessible to both technical and non-technical readers. They also emphasize the importance of balancing the human element with data insights and encourage readers to use data to inform their decision-making rather than dictate it. This is a go-to source for anyone looking to harness the power of data to drive business success.
- The Art of Thinking Clearly
Rolf Dobelli
If you want to make a significant impact with the minimum amount of effort, this is the reading reference you have been looking for! Rolf Dobelli offers practical and concise insights into cognitive biases along with common pitfalls and errors that we all make in our thinking, but without us even realizing it. The author provides 99 chapters, each focusing on a different cognitive bias or logical fallacy, and explains how these errors can lead to poor decision-making and negative outcomes both in personal and professional lives. The book is well-organized, easy to read, and full of useful examples and tips for avoiding these common thinking errors and, most importantly, identifying one. Definitely, a must-read for anyone who wants to improve their critical thinking skills and make better decisions.
Online Class
- 100 Days of Code : The Complete Python Pro Bootcamp
Dr. Angela Yu
Let’s jump to the non-textual lesson. If anyone wants to have effective exercise without confiscating too much of their time, in the world of fitness, there is the 15 mins HIIT (High-Intensity Interval Training) for an effective calorie burnout and workout. This course can be considered the HIIT for Python programming. Designed to be completed over 100 days, it provides daily video lectures, coding exercises, and quizzes, each taking only up to 30 mins of your time. The course covers a wide range of topics, including Python basics, web development, data science, and machine learning. The instructor, Dr. Angela Yu explains the concepts clearly and provides ample examples to help learners understand the material. The course is well-structured and easy to follow, making it suitable for beginners and intermediate learners alike.
Movies
Think data science and analytics are only applicable to business? Actually, it’s applicable to almost any field that involves decision-making. This movie is a great example of a data-centric approach utilized to scout talents for the Oakland Athletics baseball team, which is often losing the talent battle with larger, more financially loaded teams. Using a method called sabermetrics, an application of statistical analysis to baseball records, especially in order to evaluate and compare the performance of individual players, the team started building a winning team of undervalued players with a low budget. It offers a fascinating insight into the world of baseball and how data-driven decision-making can lead to success in any industry.
Can data give a warning for a potential crisis? Yes, if you know how to read them, like in this movie. A 2011 drama film that portrays the use of data science in finance during the 2008 financial crisis. The movie showcases how the use of sophisticated financial models and data analysis helped the investment bankers at an unnamed financial firm uncover an impending market crash. Through the eyes of the characters, the film explores the ethical and moral considerations of using data science to make high-stakes financial decisions, highlighting the importance of responsible data usage in the world of finance. Overall, the movie offers a cautionary tale on the power and limitations of data-driven decision-making.
Data analytics is all about unearthing valuable insights by analyzing patterns, and that’s exactly what this movie is about. Following the life of British mathematician Alan Turing in cracking the German military cipher machine ENIGMA during World War II. By studying and recognizing patterns for certain words and phrases such as “Eins,” Turing and his team automated the crib process and successfully extracted concealed information from the intercepted Enigma messages.
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