Effective Data Analysis
eBook Details:
- Paperback: 416 pages
- Publisher: WOW! eBook (April 15, 2025)
- Language: English
- ISBN-10: 1633438414
- ISBN-13: 978-1633438415
eBook Description:
Effective Data Analysis: Hard and soft skills to accelerate your career. Learn the technical and soft skills you need to succeed in your career as a data analyst.
You’ve learned how to use Python, R, SQL, and the statistical skills needed to get started as a data analyst so, what’s next? Effective Data Analysis bridges the gap between foundational skills and real-world application. This book provides clear, actionable guidance on transforming business questions into impactful data projects, ensuring you’re tracking the right metrics, and equipping you with a modern data analyst’s essential toolbox.
In Effective Data Analysis: Hard and soft skills to accelerate your career, you’ll gain the skills needed to excel as a data analyst, including:
- Maximizing the impact of your analytics projects and deliverables
- Identifying and leveraging data sources to enhance organizational insights
- Mastering statistical tests, understanding their strengths, limitations, and when to use them
- Overcoming the challenges and caveats at every stage of an analytics project
- Applying your expertise across a variety of domains with confidence
Effective Data Analysis is full of sage advice on how to be an effective data analyst in a real production environment. Inside, you’ll find methods that enhance the value of your work from choosing the right analysis approach, to developing a data-informed organizational culture.
Data analysts need top-notch knowledge of statistics and programming. They also need to manage clueless stakeholders, navigate messy problems, and advocate for resources. This unique book covers the essential technical topics and soft skills you need to be effective in the real world.
Effective Data Analysis helps you lock down those skills along with unfiltered insight into what the job really looks like. You’ll build out your technical toolbox with tips for defining metrics, testing code, automation, sourcing data, and more. Along the way, you’ll learn to handle the human side of data analysis, including how to turn vague requirements into efficient data pipelines. And you’re sure to love author Mona Khalil’s illustrations, industry examples, and a friendly writing style.
