Название: Data Science for Managers: How to Use Data (Big and Small) to Solve Business Challenges, Second Edition
Автор: Richard Boire
Издательство: Palgrave Macmillan/Springer
Год: 2026
Страниц: 294
Язык: английский
Формат: pdf (true), epub
Размер: 33.5 MB

In today’s world of Big Data, data scientists must stay ahead of the game, especially in environments that are increasingly unstructured and semi-structured. They need fresh skills to navigate these complex environments. It is also important to question whether Big Data analytics fundamentally differs from Small Data analytics.

In Data Science for Managers, industry expert Richard Boire breaks down the vast field of Data Science into easy-to-understand insights. Using real-world examples from leading global companies, this book provides a clear, step-by-step guide to help business managers harness the power of Data Science. Boire's 4-step process walks you through deciding when to use Data Science, implementing it, and making sense of the results to improve customer ROI and business outcomes.

Packed with engaging stories and case studies, this work also highlights potential pitfalls in Data Science and shares strategies for avoiding them. This updated edition focuses on new developments related to AI and Machine Learning, with guidance for data managers on how to use this technology in developing business solutions.

The varying formats of data have created the need for technical capabilities in extracting information from the web. To address this need, social media vendors provide Application Programming Interface (APIs) to help read the data that is arising in these constantly changing file formats. For those users that are more technical, programs such as Python, Java etc. allow the analyst to extract this type of information without using any software vendor tool.

The software component of Data Science remains the area of this field which continues to see the most change. Why is this so? With cheap and easy access to data through technology, there has been huge demand in trying to empower more people to do data analysis. Historically, this type of capability was isolated to highly technical people with strong programming skills. In the very early days of Data Science, those with SAS programming skills were treated as the data science gurus within any company. These skillsets are still highly valued, but interest has moved on to other tools such as Python, which are more compatible with the Web. At the same time, there has also been a shift to empower other individuals in the area of Data Science. The first scenario is to empower regular business analysts with the capability of doing non-statistical data analysis. In the second scenario, organizations would like to empower more mathematically oriented individuals to conduct statistical-type analyses, yet their capabilities are limited because they do not have strong programming skills. In both of the above scenarios, new software can help to facilitate the Data Science exercise by eliminating the need for someone to write programming code. Instead, the Graphical User Interface (GUI) provides the interface that allows the analyst to conduct a Data Science exercise. The analyst still needs to have a very deep understanding of the Data Science process, but they can now conduct this exercise without writing any programming code.

Data Science for Managers is a book for marketers, IT professionals, analysts, and anyone else who wants to transform mountains of data into actionable insights and effective business strategies. With the rise of AI and cutting-edge technology, it equips you with the tools you need to navigate this new landscape and turn complex data into tangible results. Whether you're new to Data Science or looking to sharpen your skills, this book is your guide to unlocking the full potential of Big Data.

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