Your One Page To Get Started With Data

Everything you need to get started with data!

Author

Joy Chatterjee
August 18, 2023

This Friday. One Page.

  • Who is this one-pager for?

  • What does this wiki cover?

    • Understanding the basics

    • Knowing the relevant tools

    • Creating the right metrics & actionable insights

    • Building data-driven workflows

  • Quote of the day!

READ TIME → 8 minutes

Welcome to this Friday!

As promised, here is your one-pager.

In this issue, we will provide a wiki full of concepts, steps and tools that can empower product teams and beginners to get started with data analytics. Whether you're a product manager, entrepreneur or just keen to get started with data science, this one-pager is the perfect wiki to kick off that journey.

Who is this one-pager for?

🎯 Product Managers: Ranges from folks who are new to data analytics and want to learn the basics, to more experienced product managers looking to enhance their skills and gain a deeper understanding of how data can impact their product management approach.

🧠 Data Science Beginners: Individuals who are new to the field of data science and analytics could benefit from the foundational concepts and resources.

📊 UX / UI Designers: User experience and user interface designers can benefit from learning about data analytics as it relates to understanding user behavior, preferences, and interactions.

👩🏻‍💻Marketing Professionals: Marketers looking to optimize their strategies through data-driven insights can find value in understanding how product managers use analytics to guide feature prioritization.

📈 Business Analysts: Ones who work closely with product managers to analyze market trends, customer behavior, and business performance, to better collaborate with product teams and interpret data-driven recommendations.

Think you know someone who might be in this list, but has not seen this one-pager? Well, you’re one click away from sharing it with them!

What does this wiki include?

Let’s start with the topics we will cover in this wiki.

This will give you an overview of the different aspects that you have to consider when thinking about getting connected to data.

  • Understanding the basics

  • Knowing the relevant tools

  • Creating the right metrics & actionable insights

  • Building data-driven workflows

Each of these topics should cover a significant chunk of the responsibilities we need to be aware of when thinking about data and analytics.

Quick Disclaimer : This Wiki serves as landing site to launch you into the various paths of data and analytics. It will not cover detailed explanations but rather serve you the entry points which will lead to platforms where you can have in-depth knowledge and understanding of these relevant topics.

Now, let’s jump into each of these topics.

How do we get started with Data & Analytics?

Understanding the basics

Its essential to first delve into the foundational concepts of data analytics. Here you should learn about various types of data, both quantitative and qualitative, and how these data sources can be collected.

The articles below will introduce key terminologies like Key Performance Indicators (KPIs), metrics, and dimensions, helping readers establish a solid understanding of the data landscape.

Knowing the relevant tools

In this section, the focus is on the tools and platforms that enable effective data analytics.

The articles and platforms will provide an overview of popular analytics tools such as Google Analytics, Mixpanel, Amplitude, and more. It will guide readers in selecting the right tools based on their specific needs, budget, and technical expertise

Creating the right metrics & actionable insights

This section will dive into the art of defining metrics that matter. Readers will learn how to set Specific, Measurable, Achievable, Relevant, and Time-bound (SMART) goals, and align metrics with their product strategy.

Data without insights is just noise. This section will also focus on turning raw data into actionable insights.

Readers will explore data visualization techniques that help simplify complex information. These articles will introduce visualization tools and best practices for creating charts, graphs, and dashboards that facilitate decision-making.

Building data-driven workflows

In this section, the articles will demonstrate how data analytics can shape product roadmaps.

Readers will learn how to use data to identify user needs, prioritize features based on user preferences, and validate assumptions through data-driven decision-making.

Real-world examples of companies that successfully integrated data into their roadmap planning will provide valuable insights.

By breaking down each section in detail, this one-pager Wiki aims to equip product managers, data science beginners, business analysts, UX/UI designers and marketing professionals with a comprehensive understanding of how to incorporate data analytics into their workflow.

From the very basics to practical applications, this guide will empower readers to leverage data-driven insights to make informed decisions and optimize their products / solutions for success.

❝

I never guess. It is a capital mistake to theorize before one has data.

Sherlock Holmes (Sir Arthur Conan Doyle)

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