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Erik Herman

Welcome to Fundamentals of Big Data, the fourth course of the Key Technologies of Data Analytics specialization. By enrolling in this course, you are taking the next step in your career in data analytics. This course is the fourth of a series that aims to prepare you for a role working in data analytics. In this course, you will be introduced to many of the core concepts of big data. You will learn about the primary systems used in big data. We’ll go through phases of a common big data life cycle. This course covers a wide variety of topics that are critical for understanding big data and are designed to give you an introduction and overview as you begin to build relevant knowledge and skills.

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What's inside

Syllabus

Big Data Concepts
In the first module of the course, we'll learn about core concepts of big data, including working with large data sets, big data strategies, and big data technologies. By the end of this module, you will know how to identify these aspects of big data and their use cases. So let's get started!
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Big Data Systems
In the second module of this course, we'll learn about the primary characteristics of a big data system, including volume, velocity, and variety.
Big Data Life Cycles
In the third module of this course, we'll learn about the phases of a big data project, including data ingestion, data persistence, computing and analysis, and data visualization.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Builds a strong foundation for beginners who aspire to work with big data
Introduces a wide variety of big data topics, including concepts, systems, and lifecycles
Taught by Erik Herman, an experienced instructor in big data
Covers phases of a common big data life cycle, providing practical insights
Part of a specialization in Data Analytics, indicating a broader learning pathway

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Reviews summary

Big data fundamentals: positive reviews

Learners say this course on Big Data fundamentals is a good overview that dives into core concepts in depth. They find the materials engaging, and the instructor is described as excellent at engaging students. Overall, this course is well-received by students.
Course provides a good overview of Big Data systems.
"good overview of bigdata system overall"
Instructor is excellent at engaging students.
"prof. Erik Herman has excellent capabillies to involve studnets in E-Learning."
Course dives deep into core concepts of Big Data.
"learn the core concepts of Big Data in a deep way"

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Fundamentals of Big Data with these activities:
Review Data Science for Business
Reviewing this book will help you solidify the concepts in the course and deepen your understanding of big data.
Show steps
  • Read the book
  • Summarize the key concepts
  • Create a mind map of the concepts
  • Discuss the concepts with a classmate
  • Write a short essay on how the concepts apply to your own work
Refresh your knowledge of data structures
Reviewing data structures will help you understand how data is stored and organized in big data systems.
Browse courses on Data Structures
Show steps
  • Review your notes from a previous data structures course.
  • Take a practice quiz or exam on data structures.
  • Work through some coding problems that involve data structures.
Attend a Data Analytics Meetup
Attending a meetup will allow you to network with other professionals in the field, which can help you learn about new opportunities.
Browse courses on Data Analytics
Show steps
  • Find a meetup in your area
  • Register for the meetup
  • Attend the meetup
  • Network with other professionals
  • Follow up with the people you met
Five other activities
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Show all eight activities
Join a Data Analytics Study Group
Participating in a study group will allow you to learn from others and get help with your coursework.
Browse courses on Data Analytics
Show steps
  • Find a study group in your area
  • Join the study group
  • Attend the study group meetings
  • Participate in the discussions
  • Help others with their work
Attend a Data Analytics Workshop
Attending a workshop will allow you to learn new skills and techniques that can help you in your career.
Browse courses on Data Analytics
Show steps
  • Find a workshop in your area
  • Register for the workshop
  • Attend the workshop
  • Practice the skills you learned
  • Apply the skills to your work
Practice Using Big Data Tools
Practicing these tools will help you become more proficient in using them, which will make you more effective in your work.
Browse courses on Big Data
Show steps
  • Install the necessary software
  • Complete the tutorials
  • Practice using the tools on sample data sets
  • Build a small data analytics project
  • Share your project with others for feedback
Create a Data Visualization for a Business Problem
Creating data visualizations will help you develop your skills in this area, which can make you more valuable in the workplace.
Browse courses on Data Visualization
Show steps
  • Identify a business problem that you can solve with data visualization
  • Collect and clean the data
  • Choose the appropriate visualization type
  • Create the visualization
  • Present your visualization to others
Build a Big Data Analytics Pipeline
Building a big data analytics pipeline will help you develop your skills in this area, which can make you more competitive in the job market.
Browse courses on Big Data
Show steps
  • Define the business problem that you want to solve
  • Gather the data
  • Clean and prepare the data
  • Build the data analytics pipeline
  • Deploy the pipeline and monitor its performance

Career center

Learners who complete Fundamentals of Big Data will develop knowledge and skills that may be useful to these careers:
Data Engineer
Building a foundation in big data is crucial for a successful Data Engineer. This course covers the core concepts of big data, enabling learners to develop skills in data ingestion, data persistence, computing, and analysis. The course also delves into big data systems and the life cycle of big data projects. With this knowledge, learners can excel in data engineering roles that require expertise in big data management and processing.
Data Architect
For aspiring Data Architects, this course lays the groundwork for understanding the complexities of big data. By gaining insights into big data concepts, systems, and life cycles, learners can build a solid foundation for designing and managing big data architectures. The course empowers learners to handle large data sets effectively and develop scalable data solutions, enhancing their ability to succeed as Data Architects.
Data Scientist
This course is highly recommended for aspiring Data Scientists who wish to specialize in big data. By mastering the fundamentals of big data, learners gain a competitive edge in handling and analyzing large data sets. The course covers techniques for data ingestion, persistence, computing, and analysis, providing a comprehensive foundation for successful data science projects involving big data.
Big Data Analyst
Professionals seeking to become Big Data Analysts will find this course invaluable. It provides a thorough understanding of big data concepts, systems, and life cycles. Learners develop skills in managing large data volumes, utilizing big data technologies, and extracting valuable insights from data. This course empowers learners to excel in their roles as Big Data Analysts, enabling them to make data-driven decisions and contribute to business outcomes.
Data Analytics Manager
For individuals aspiring to become Data Analytics Managers, this course offers a solid foundation in big data. By understanding the core concepts, systems, and life cycles of big data, learners gain the ability to lead and manage teams in big data projects. The course equips learners with the knowledge and skills to oversee data ingestion, storage, analysis, and visualization, enabling them to drive data-driven decision-making and achieve business objectives.
Data Visualization Specialist
This course may be beneficial for Data Visualization Specialists who wish to enhance their skills in big data. By gaining insights into managing large data sets and utilizing big data tools, learners can develop effective data visualization techniques for big data. The course covers data ingestion, persistence, computing, and analysis, empowering learners to handle complex data and create meaningful visualizations that drive data-informed decision-making.
Machine Learning Engineer
For Machine Learning Engineers who want to specialize in big data, this course provides a solid foundation. Learners gain an understanding of big data concepts and technologies, enabling them to build and deploy machine learning models that handle large data volumes. The course covers data ingestion, persistence, computing, and analysis, empowering learners to develop scalable and efficient machine learning solutions for big data applications.
Business Intelligence Analyst
This course may be helpful for Business Intelligence Analysts who wish to specialize in big data. By gaining insights into managing large data sets and utilizing big data tools, learners can enhance their ability to extract valuable insights from data. The course covers data ingestion, persistence, computing, and analysis, empowering learners to handle complex data and develop comprehensive business intelligence solutions that drive decision-making.
Cloud Architect
For Cloud Architects who want to specialize in big data, this course provides a solid foundation. Learners gain an understanding of big data concepts and technologies, enabling them to design and manage cloud-based big data solutions. The course covers data ingestion, persistence, computing, and analysis, empowering learners to develop scalable and cost-effective big data architectures on cloud platforms.
Software Engineer
This course may be beneficial for Software Engineers who wish to specialize in big data. By gaining insights into managing large data sets and utilizing big data tools, learners can enhance their ability to develop software solutions that handle complex data. The course covers data ingestion, persistence, computing, and analysis, empowering learners to build scalable and efficient software systems for big data applications.
Database Administrator
This course may be helpful for Database Administrators who wish to specialize in big data. By gaining insights into managing large data sets and utilizing big data tools, learners can enhance their ability to design and manage big data databases. The course covers data ingestion, persistence, computing, and analysis, empowering learners to handle complex data and develop scalable and reliable database solutions for big data applications.
Data Governance Specialist
For aspiring Data Governance Specialists, this course provides a solid foundation in big data. By understanding the core concepts, systems, and life cycles of big data, learners can effectively manage and govern data assets in big data environments. The course covers data ingestion, storage, security, and compliance, empowering learners to establish data governance frameworks and ensure data quality and integrity.
Information Security Analyst
This course may be helpful for Information Security Analysts who wish to specialize in big data security. By gaining insights into managing large data sets and utilizing big data tools, learners can enhance their ability to protect big data from security threats. The course covers data security, encryption, and access control, empowering learners to develop and implement effective big data security measures.
Data Privacy Officer
For aspiring Data Privacy Officers, this course provides a solid foundation in big data. By understanding the core concepts, systems, and life cycles of big data, learners can effectively manage and protect personal data in big data environments. The course covers data privacy regulations, compliance, and best practices, empowering learners to develop and implement data privacy programs that safeguard sensitive information.
Chief Data Officer
This course may be helpful for aspiring Chief Data Officers who wish to specialize in big data. By gaining insights into managing large data sets and utilizing big data tools, learners can enhance their ability to lead and manage big data initiatives within organizations. The course covers data strategy, governance, and analytics, empowering learners to develop and implement data-driven strategies that drive business outcomes.

Reading list

We've selected 13 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Fundamentals of Big Data.
Comprehensive guide to Spark and is helpful for understanding how to use Spark to process big data.
Provides a good overview of deep learning and is helpful for understanding how to use deep learning to analyze big data.
Provides a practical introduction to data analytics and its applications. It covers topics such as data collection, cleaning, analysis, and visualization, and useful resource for those who want to learn more about the practical aspects of big data.
Provides a good overview of data science and is helpful for understanding the role of big data in data science.
Provides a practical introduction to machine learning for big data. It covers topics such as supervised and unsupervised learning, feature engineering, and model evaluation, and useful resource for those who want to learn more about the application of machine learning to big data.
Provides a practical guide to big data and its applications. It covers topics such as data collection, cleaning, analysis, and visualization, and useful resource for those who want to learn more about the practical aspects of big data.
Provides a practical introduction to data visualization. It covers topics such as data visualization techniques, best practices, and case studies, and useful resource for those who want to learn more about the effective use of data visualization.
Provides a practical guide to big data analytics for practitioners. It covers topics such as data collection, cleaning, analysis, and visualization, and useful resource for those who want to learn more about the practical aspects of big data.
Provides a practical introduction to data mining and its applications. It covers topics such as data mining techniques, algorithms, and case studies, and useful resource for those who want to learn more about the use of data mining in various domains.
Provides a basic introduction to big data and its applications. It covers topics such as data collection, cleaning, analysis, and visualization, and useful resource for those who want to learn more about the basics of big data.
Provides an overview of the use of big data in journalism. It covers topics such as data collection, cleaning, analysis, and visualization, and useful resource for those who want to learn more about the use of big data in journalism.

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