Getting Started with Data (Single Book License)
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Getting Started with Data

The first book you should read to successfully get along with data.

About the Book

Is this book for me?

If you are a person working every day with systems like ERP and CRM or spreadsheets, but using "data" daily still strange and uncomfortable, this book is definitely for you.


Reviews by our readers

Below you can find some of the hundreds of reviews this book received from top-notch entrepreneurs, professors, investors, and even neuroscience and bio researchers.

"The book seems great to me. It's clear, straightforward, and looks good, all of which are the hallmarks of a well-prepared book." - Leonard Epp (LeanPub Co-founder)

"Through a didactic approach, the book invites to a reading and understanding about the wonderful data world." - Dayanne da Silva Prudêncio (Doctor in Information Science & University Professor)

"The book is very good. It highlights the basic topics for those who start in the data field, with illustrations and important information." - Grimaldo Lopes (Senior Business Intelligence Specialist & Professor)

"Excellent book for those who are starting in the data or marketing world! It's very clear and instructive." - Bernardo Zamijovsky (Investor & Entrepreneur)

"The book demystifies and explains in a simple way the main concepts involving data and, during reading, I could realize that the theme is relevant in almost everything of modern life." - Martin Arntsen (Senior Account Manager)

"I swear I liked it very much. It is a well-thought-out book, I liked the didactic structure and mainly the speech, well aligned to the target audience." - Maurício Vidor (Senior Business Consultant & Entrepreneur)

"I got very impressed by the book! It is very well written, using a light form that anyone can read and understand it - from the technician to the president of a large company. It has a very interesting didactic and it makes the readers reflect on the applicability on their daily lives." - Dagoberto Hajjar (Senior Business Consultant & Entrepreneur)

"I liked, above all, the summary at the end of each chapter with the check questions. It gets very didactic, gives a lot of comfort to those who read, feeling that they understood and got everything that was meant to be learned." - Marcelo Inglez de Souza (Senior Lawyer & Entrepreneur)

"The graphic part is very light, including graphics and figures, and it is easy to read. The writing in English seems well done and with a very accessible vocabulary." - Hélio Contador (Senior Business Consultant & Neuroscience Researcher)

"The book is extremely clear and didactic, it was done with extreme care at all levels. The chapter structure with basic and advanced parts I considered a super goal." - Diogo Lara (Psychiatrist & Entrepreneur)

"Although the content is technical, it is easy to understand due to the vocabulary and to the book structure, divided into topics. Ending each chapter with a summary and questions was really intelligent." - Higor Falcão (Bio Researcher & Entrepreneur)

"Most of the materials about technology are quite dull for those who are not in the field but, in this book, I considered the content super didactic and very easy to follow." - Lucas Galvanini (Marketing Expert & Entrepreneur)

"I really, really liked the book! The font size is great and English speech used is easy to read: simple and didactic. I also liked the "Summary" and "Let's check" at the end of each chapter, as it is a way to make the reader remember and think!" - Angélica Félix de Castro (University Professor)

"The approached topics for beginners and laypeople are a good introduction for those interested in developing in the field of Data Science and alikes. The simple speech and formatting of the pages make us want to read at a good pace without getting tired easily." - Emeson Oliveira Borges (Technical Researcher)

"I consider the book to be concise, well-written, and extensive (considering the objective of teaching the laypeople about a subject). The structure is great, with the sections well divided and fluid. I liked the job!" - Leonardo Gomes (Senior Accountant)

"The reading is easy, smooth and, in addition, the text layout and textual divisions brought dynamism to the reading, avoiding tiredness - which is excellent for a technical book! I also liked the didactics in the explanations and the questions at the end of each chapter." - Danilo Caramelo (Software Developer)


Why we wrote this book?

Since 2012, every few months, we have had to teach dozens of new team members at Simbiose Ventures about concepts related to data. This training covered data and everything else associated with it, such as databases, data engineering, data analysis, and so on.

Before deciding to write this book, our training process at Simbiose looked like a patchwork quilt: hundreds of small pieces from books, articles, and courses that talked about data. When onboarding new members on our team, we had to drown them in information because we didn't have a single, concrete source that would get them from "zero to hero" in the effort to understand data. This process usually brought two challenges:

  1. People were scared off because there was a lot to study, even before starting to work;
  2. It wasn't efficient, as we had to assemble different study tracks for other people who were not going to perform similar roles.

This changed when a specific talented, anxious, and eager girl joined our team. We gave her the mission of studying all the materials we had and creating a single book that could introduce all the concepts about data to any new team member. The book you are reading now is the result of all this fantastic teamwork.

We aim to present the data world for those interested in its importance but unsure where to start. We included parts of the history of data, the importance of data, and how it revolutionized the way we manage and calculate it, to how technology elevates the possibilities of our work and life.

As data is now part of our daily lives, we believe that any person should read this book, especially people responsible for organizations' decisions.

What to expect?

  • After reading this book, you can expect to understand the main concepts and technical aspects of data.
  • You will be able to recognize and understand most of the jargon used by data-related products and professionals as we gently introduce more than 50 terms and concepts related to data and analytics.
  • You will certainly be able to talk to other people about data, some of its possible usages, and how to initiate your first data projects.
  • Most importantly, you will surely understand what data means and how you can use it to improve your life and career.

What is this book not?

The "Getting Started With Data" book has no intention of:

  1. Substituting other great data-related books that already exist. We humbly believe this book might be an excellent first step before getting into all the existing books, as many of them presume you already have some minimum knowledge about data.
  2. Making you a "data engineer", a "data scientist", "data analyst", "business intelligence professional", and so on. The sole purpose of this book is to help you get started with data in a structured way.

If you already have a firm grasp of the basics and expect to run an incredible analysis or create an entire data infrastructure by reading this book, don't waste your time. There are much better books and resources for that, as we detail in Chapter 8, section 8.4 (A Learning Path).

How to read this book?

There are two approaches to read this book, the conceptual (overview) and technical (in-depth).

You will notice that most chapters contain two types of content: an overview of the concepts and one or more in-depth section for those interested in knowing more about the bits and bytes.

While writing this book, we made sure that just reading the concepts would be enough to grasp the essentials and get a clear understanding of the main ideas about data. Feel free to skip the "in-depth" sections if you don't have a technical background. Anyhow, if you are up for a challenge, you'll undoubtedly enjoy going deeper.

The book starts presenting concepts and a bit of history related to data in Chapter 1 (What is Data) and Chapter 2 (What is Information). In summary: how data came from raw registers to help with real-world issues, and how we developed the study field of "information" - a concept that leads the information age.

If you are a business heavy-user, a professional immersed in the technological field, or you have some experience with software development, Chapter 3 (How Data is Born) and Chapter 4 (How Data is Stored) will give you technical concepts about data within applications, as well as the differences among storage types and how they are being used depending on the needs of the data and the business.

On the other hand, you might not be a "data geek" nor wish to become one. Suppose you are only interested in learning how data can impact your business and what kind of tools and teams you have to put together to extract value from data. In that case, you can focus on Chapter 5 to Chapter 8. They discuss how analytics techniques can generate business value. From there, managing the underlying path taken by your data to be stored and analyzed affects what tools and techniques are used for actual decision-making on the top layer.

At the end of this book, in Chapter 9, you will find a conclusion that puts together and make tangible all the terms, concepts, processes, and technologies introduced during the entire book.

Finally, there's also a complete Glossary explaining all the terms and their corresponding concepts. It's divided into sections according to the concepts introduced in each chapter.

Although concepts are linked and referenced among chapters, all the parts of this book can be read independently since they offer value for different professionals. Reading through all of it won't do you any harm, though. After all, information is power and learning how to manage it will become more and more valuable as technology advances.

Enjoy your reading!

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    • Business Analysis
    • Digital Transformation
    • Databases
    • Computers and Programming
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About the Author

Simbiose Ventures
Simbiose Ventures Team

Simbiose Ventures is a Brazilian organization focused on providing a better future for low-income Brazilians by teaching them how to code and create data-related products, from which we get the necessary revenue to keep the initiative alive.


Single Book License
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Small Team Licensing (10 copies)

License this book for up to 10 people on your team and help them get started with data.

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Enterprise Licensing (100 copies)

License this book for up to 100 people in your organization or department and get started to become a data-driven organization.

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Table of Contents

    • Preface
      • Who wrote this book?
      • Why this book?
      • What to expect?
      • What is this book not?
      • How to read this book?
      • Found a mistake?
  • Part I - Data Basics
    • Chapter 1 - What is Data
      • 1.1 A Short History of Data
      • 1.2 The Growing Importance of Data
      • 1.3 Data Types
        • 1.3.1 Data Transformation
        • 1.3.2 In-depth: Data Types
      • Summary
      • Let’s check
    • Chapter 2 - What is Information
      • 2.1 Information: Data, Contextualized
      • 2.2 In-depth: Information Theory
      • Summary
      • Let’s check
    • Chapter 3 - How Data is Born
      • 3.1 User-generated Data
      • 3.2 Application-generated Data
      • 3.3 Hardware-generated Data
      • 3.4 In-depth: Data types on application data
      • 3.5 End-to-end example
      • Summary
      • Let’s check
    • Chapter 4 - How Data is Stored
      • 4.1 Structured and unstructured data
        • 4.1.1 Structured data
        • 4.1.2 Unstructured data
        • 4.1.3 Semi-structured data
      • 4.2 In-depth: Organizing the data
        • 4.2.1 The relational theory
        • 4.2.2 Graphs
        • 4.2.3 Data Lakes
      • 4.3 Types of Databases
        • 4.3.1 Row Store and Column Store databases
        • 4.3.2 OLTP and OLAP databases
        • 4.3.3 Relational Database Management Systems (RDBMS)
        • 4.3.4 NoSQL
      • 4.4 In-depth: NoSQL types of databases
        • 4.4.1 Document databases
        • 4.4.2 Key-value databases
        • 4.4.3 Graph databases
        • 4.4.4 Search engines
      • 4.5 Storage Location
        • 4.5.1 On-premises
        • 4.5.2 Cloud-based
        • 4.5.3 Hybrid
      • Summary
      • Let’s check
  • Part II - Data Usage
    • Chapter 5 - How Data is Analyzed
      • 5.1 Data Analytics: A developing concept
      • 5.2 The Parts of an Analysis
      • 5.3 Types of Analysis
        • 5.3.1 Descriptive analysis
        • 5.3.2 Diagnostic analysis
        • 5.3.3 Predictive analysis
        • 5.3.4 Prescriptive analysis
      • 5.4 In-depth: Machine Learning models
        • 5.4.1 Unsupervised learning
        • 5.4.2 Supervised learning
      • 5.5 Data Visualization
      • 5.6 Technology for analytics
        • 5.6.1 A Central Place for Data
        • 5.6.2 Data Warehouses
        • 5.6.3 Data Lakes
        • 5.6.4 Data Lakehouse
        • 5.6.5 Business Intelligence platforms
      • Summary
      • Let’s check
    • Chapter 6 - How Data is Managed
      • 6.1 Data Pipelines and ETL
      • 6.2 Data Democratization
      • 6.3 Data Governance
      • 6.4 Data Compliance and Auditing
        • 6.4.1 Performing a Data Audit
        • 6.4.2 Tools to perform Data Governance
      • 6.5 Data Quality
        • 6.5.1 Defining your Data Quality process
        • 6.5.2 Assessing your Data Quality metrics
      • Summary
      • Let’s check
    • Chapter 7 - How Data is Used in an Organization
      • 7.1 Know where you are
      • 7.2 Identify improvements
      • 7.3 Making a case for an Analytics strategy
      • Summary
      • Let’s check
    • Chapter 8 - How to Build a Data Team
      • 8.1 Identifying and acquiring capabilities
        • 8.1.1 Domain of the organization
        • 8.1.2 Cost to effectiveness
        • 8.1.3 Set up a knowledge transfer culture
        • 8.1.4 Decentralize the team
      • 8.2 Team Roles
      • 8.3 Maturity assessment
      • 8.4 A Learning Path
        • 8.4.1 Technical path
        • 8.4.2 Business path
      • Summary
      • Let’s check
    • Chapter 9 - Wrapping it up
    • Glossary
      • What is Data
      • How Data is Born
      • How Data is Stored
      • How Data is Analyzed
      • How Data is Managed
      • How Data is Used in an Organization
  • Notes

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