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Effective Data Analysis: Hard and Soft Skills to Accelerate Your Career
Paperback
DatabasesGeneral ComputersProgramming
ISBN13: 9781633438415
Publisher: Manning Publications
Published: Apr 15 2025
Pages: 416
Weight: 1.55
Height: 1.00 Width: 7.30 Depth: 9.10
Language: English
- 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. Foreword by Barry McCardel. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology 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. About the book 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. What's inside - Identify and incorporate external data
- Communicate with non-technical stakeholders
- Apply and interpret statistical tests
- Techniques to approach any business problem About the reader Written for early-career data analysts, but useful for all. About the author Mona Khalil is the Senior Manager of Analytics Engineering at Justworks. Table of Contents Part 1
1 What does an analyst do?
2 From question to deliverable
3 Testing and evaluating hypotheses
Part 2
4 Statistics you (probably) learned: T-tests, ANOVAs, and correlations
5 Statistics you (probably) missed: Non-parametrics and interpretation
6 Are you measuring what you think you're measuring?
7 The art of metrics: Tracking performance for organizational success
Part 3
8 Navigating sensitive and protected data
9 The world of statistical modeling
10 Incorporating external data into analyses
11 The magic of well-structured data
12 Tools and tech for modern data analytics
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