How to learn Analytics in 2024 – Complete Guide and Resources

In this comprehensive guide, we'll walk you through the best ways to learn Analytics, from recommended books and courses to finding expert mentors who can accelerate your learning journey.

Before diving into learning Analytics, a word of caution: While there are many resources available online, it's important to follow a structured learning path and avoid getting overwhelmed. Having a clear goal and roadmap will help you stay focused and make steady progress.

If you're looking for a more guided approach, you may want to check out our Analytics mentors who can help create a personalized learning plan and provide expert guidance throughout your journey.

Getting started with Analytics

In this guide, we'll cover:

• Learning Resources - Recommended books and online courses to build your Analytics knowledge
• Expert Guidance - Finding mentors and joining communities
• Certifications - Professional certifications to validate your Analytics skills
• Career Development - Building a portfolio and preparing for jobs

Let's explore each of these areas to help you create an effective learning path for mastering Analytics.

How can I start learning Analytics?

Getting started with Analytics is very achievable with the right approach and resources. Here are some key steps to begin your learning journey:

1. Start with fundamentals. Begin by learning the core concepts and principles of Analytics. This builds a strong foundation for more advanced topics;
2. Take online courses. Platforms like Coursera, Udemy, and edX offer structured Analytics courses for beginners. These provide guided learning with hands-on practice;
3. Read documentation and books. Official documentation and recommended books can deepen your understanding of Analytics concepts;
4. Connect with a mentor. Our experienced Analytics mentors can create a personalized learning plan and guide you through your journey efficiently.

Can I learn Analytics on my own?

While self-study is possible, having expert guidance can save you months of trial and error and help you avoid common pitfalls. Here's what to consider:

1. Self-paced learning. Online resources and tutorials let you learn at your own speed, but it can be challenging to know if you're on the right track;
2. Community support. Join online communities and forums to get help, though responses may vary in quality and accuracy;
3. Professional mentorship. Working with a Analytics mentor provides personalized feedback, industry insights, and accountability to keep you progressing;
4. Structured approach. A mentor can create a customized learning path based on your goals and current skill level.

Can I learn Analytics in one month?

While you can grasp basic concepts of Analytics in a month with dedicated study, becoming proficient typically takes longer. Here's a realistic timeline:

1. First month. Master fundamental concepts and basic principles of Analytics;
2. 3-6 months. Develop intermediate skills and work on increasingly complex projects;
3. 6-12 months. Build advanced knowledge and professional-level expertise;
4. Accelerated learning. Working with one of our expert Analytics mentors can significantly speed up this timeline through focused guidance and industry best practices.

Learning Resources for Analytics

One of the most effective ways to build a strong foundation in Analytics is through carefully selected learning resources. Let's explore some key materials that can help you master this field.

Essential Reading Materials

Books remain one of the most comprehensive ways to learn Analytics in depth. They provide structured knowledge and detailed explanations that are often missing from online tutorials. Here are some recommended reading approaches:

• Start with beginner-friendly books that introduce core concepts and fundamentals
• Progress to intermediate texts that cover more advanced topics and real-world applications
• Keep reference books handy for looking up specific concepts and techniques

Recommended Books for Analytics

Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking

Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also disc…

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Storytelling with Data: A Data Visualization Guide for Business Professionals

Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for…

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Big Data at Work: Dispelling the Myths, Uncovering the Opportunities

This book will help you understand:

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Big Data: A Revolution That Will Transform How We Live, Work, and Think

It seems like “big data” is in the news every day, as we read the latest examples of how powerful algorithms are teasing out the hidden connections between seemingly unrelated things. Whether it is used by the NSA to fight terrorism or by online retailers to predict customers’ buying patterns, big data is a revolution occurring around us, in the process of forever changing economics, science, …

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View all recommended books for Analytics →

Online Learning Platforms

Online courses provide structured learning paths with hands-on practice. Here are some recommended platforms and course types:

• Interactive courses - Learn by doing with coding exercises and projects
• Video tutorials - Watch expert instructors explain concepts step-by-step
• Practice exercises - Reinforce learning through hands-on challenges

Learning Communities and Support

Having the right support system is crucial for learning Analytics. Here are some ways to get help:

• MentorCruise Community - Join our active community of learners and mentors to get support on your journey
• 1:1 Mentorship - Get personalized guidance from our expert Analytics mentors
• Work Reviews - Have experienced Analytics mentors review your work and provide detailed feedback
• Discussion Forums - Connect with peers to share knowledge and ask questions

Ready to accelerate your learning? Find a Analytics mentor who can guide you through these steps and provide personalized support.

Expert Guidance

Learning Analytics is more effective with expert guidance. Our mentors provide:

• Personalized Learning Plans - Get a customized roadmap based on your goals and current skill level
• Industry Best Practices - Learn professional standards and workflows
• Career Development - Get advice on job searching, resume building, and career advancement

Sourav Paul

5.0

Lead Software Engineer at IBM

Java Spring Boot Data Structures

Sandrina Pereira

5.0

Staff II Frontend Engineer

React Accessibility Architecture

Manson Ng

5.0

Prinicipal Software Engineer Manager at Microsoft

C# Software Engineer DevOps

Daniel Johnson

5.0

Founding Partner

Growth Growth Strategy Paid Ads

Want more options? Browse all 178 Analytics mentors to find the perfect match for your goals.

Career Guidance

Beyond technical skills, succeeding in Analytics requires strategic career planning. Our career mentors provide:

• Industry Insights - Get insider knowledge about Analytics roles and companies
• Career Strategy - Build a roadmap to reach your professional goals
• Resume & Portfolio Review - Optimize your professional materials for Analytics positions
• Interview Preparation - Practice technical and behavioral interviews with experienced professionals
• Salary Negotiation - Learn to advocate for yourself and negotiate competitive compensation

Neil Cocker

5.0

CEO

Validation Marketing Problem Discovery

Paul Kim

5.0

Director of Engineering at Coupang (ex Amazon)

Software Engineering Career Development Management

Ian Halter

5.0

Data Science Manager

Data Analysis Product Strategy Python

Ready to accelerate your Analytics career? Connect with a career mentor to start building your professional future.