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Nicholas DeGiacomo, Shrinath Parikh, Rostislav Rabotnik, Vijaya Nelavelli, Shankar Korrapolu, and Ben Larson

Join our big data online training course to gain expertise in designing big data solutions. Learn to identify big data problems and design effective solutions.

Prerequisite details

To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:

  • ETL
  • Relational database basics
  • Command line interface basics
  • Basic computer programming
  • Basic SQL
Read more

Join our big data online training course to gain expertise in designing big data solutions. Learn to identify big data problems and design effective solutions.

Prerequisite details

To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:

  • ETL
  • Relational database basics
  • Command line interface basics
  • Basic computer programming
  • Basic SQL

You will also need to be able to communicate fluently and professionally in written and spoken English.

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What's inside

Syllabus

In this lesson, we will take a 30000 foot view of Big Data and see why it is so important. We will meet the instructor and hear about the components of the course, including the final project.
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In this lesson you will learn about the main characteristics of Big Data, called the 4Vs. You will also start to explore the Big Data ecosystem.
In this lesson, you'll take a look at several of the layers that make Big Data possible, We will also look at some of the tools that help implement those layers.
In this lesson, we will look at the differences between NoSQL and SQL. We will also see why and how NoSQL databases provide capabilities that allow Big Data to be possible.
In this lesson, we will see what a Data Lake storage implementation of Big Data looks like. In addition to the benefits, we will see what considerations, risks, and challenges organizations face.
In this lesson, we will lead you through the scenario and instructions for completing the final project, which is a proposal for an actual Data Lake architecture.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores big data's 4Vs, which is standard in industry
Taught by multiple professionals with experience in the field
Develops skills for designing big data solutions, which is highly relevant to industry
Advises learners to have prior knowledge in ETL, relational database basics, command line interface basics, basic computer programming, and basic SQL, which is a common expectation

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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 Big Data Systems with these activities:
Review basic programming concepts
Basic programming concepts are essential for working with Big Data. This activity will help students to refresh their skills and ensure that they are ready for the course.
Browse courses on Programming Fundamentals
Show steps
  • Review online tutorials or documentation
  • Practice writing simple programs
Join a study group or online forum to discuss Big Data
Joining a learning community can provide students with support and motivation. It can also help them to learn from others and share their own knowledge.
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Show steps
  • Find a study group or online forum
  • Participate in discussions
  • Help others
Review basics of relational database management
Solidify your foundation in the core concepts of relational databases to ensure a strong starting point for this course.
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Show steps
  • Revisit your notes or textbooks on relational database basics
  • Complete a few practice exercises on database normalization
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Read the Big Data textbook
This book provides an excellent overview of the concepts and technologies covered in the course. It will help students to build a foundation needed to succeed in the course.
Show steps
  • Read Chapter 1: Introduction to Big Data
  • Read Chapter 2: The 4Vs of Big Data
  • Read Chapter 3: Data Storage and Processing
Explore a guide on Hadoop distributed file system
Expand your understanding of a key component of Big Data processing by following a comprehensive guide on Hadoop's distributed file system.
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Show steps
  • Find a tutorial on the Apache Hadoop website
  • Work through the tutorial, completing all exercises
  • Summarize the main concepts you have learned
Follow an online tutorial on NoSQL databases
NoSQL is a critical technology for processing large amounts of data. This tutorial will help students gain hands-on experience with a NoSQL database.
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Show steps
  • Follow the tutorial on MongoDB
  • Practice creating and querying a database
Create a data visualization using a tool like Tableau or Power BI
Data visualization is a valuable skill for exploring and communicating large datasets. This activity will give students the opportunity to apply their knowledge of big data to a practical task.
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  • Choose a dataset to visualize
  • Learn how to use a data visualization tool
  • Create a visualization that communicates the insights from the data
  • Share your visualization with others
Write a blog post or article on a Big Data topic
Writing about a Big Data topic will help students to solidify their understanding of the concepts. It will also give them an opportunity to share their knowledge with others.
Browse courses on Big Data
Show steps
  • Choose a Big Data topic to write about
  • Research the topic thoroughly
  • Write a blog post or article that is informative and engaging
  • Publish your blog post or article online
Compile your notes, assignments, and quizzes from the course
Keeping your materials organized will help you to study more effectively. This activity will help you to compile your materials and prepare for exams.
Show steps
  • Gather your notes, assignments, and quizzes
  • Organize your materials using a filing system or software
  • Review your materials regularly
Start a project to build a Big Data solution
Building a Big Data solution will give students the opportunity to apply their knowledge and skills to a real-world problem. It will also help them to develop their creativity and problem-solving abilities.
Browse courses on Data Science Projects
Show steps
  • Identify a problem or opportunity that can be solved with a Big Data solution
  • Design and develop a solution
  • Implement the solution
  • Evaluate the results
  • Share your solution with others

Career center

Learners who complete Big Data Systems will develop knowledge and skills that may be useful to these careers:
Data Engineer
Data Engineers help build and maintain systems to store and manage large amounts of data. This course will help Data Engineers understand the different technologies used in Big Data systems, and how to design and implement them. The course will also cover the challenges of working with Big Data, such as data security and scalability.
Data Scientist
Data Scientists use data to solve business problems. This course will help Data Scientists understand the different types of Big Data, and how to use them to build predictive models and make informed decisions. The course will also cover the challenges of working with Big Data, such as data cleaning and feature engineering.
Data Analyst
Data Analysts use data to identify trends and patterns. This course will help Data Analysts understand the different types of Big Data, and how to use them to perform data analysis. The course will also cover the challenges of working with Big Data, such as data quality and data visualization.
Database Administrator
Database Administrators are responsible for managing and maintaining databases. This course will help Database Administrators understand the different types of Big Data databases, and how to design and implement them. The course will also cover the challenges of working with Big Data, such as data backup and recovery.
Software Engineer
Software Engineers design and develop software applications. This course will help Software Engineers understand the different types of Big Data technologies, and how to use them to build scalable and efficient applications. The course will also cover the challenges of working with Big Data, such as data integration and data security.
Cloud Architect
Cloud Architects design and implement cloud computing solutions. This course will help Cloud Architects understand the different types of Big Data cloud services, and how to use them to build scalable and cost-effective solutions. The course will also cover the challenges of working with Big Data in the cloud, such as data security and compliance.
Data Architect
Data Architects design and implement data management solutions. This course will help Data Architects understand the different types of Big Data technologies, and how to use them to build scalable and efficient data management solutions. The course will also cover the challenges of working with Big Data, such as data governance and data quality.
Machine Learning Engineer
Machine Learning Engineers design and develop machine learning models. This course will help Machine Learning Engineers understand the different types of Big Data, and how to use them to build accurate and scalable machine learning models. The course will also cover the challenges of working with Big Data, such as data preprocessing and feature engineering.
Business Analyst
Business Analysts use data to help businesses make better decisions. This course will help Business Analysts understand the different types of Big Data, and how to use them to identify trends and patterns in business data. The course will also cover the challenges of working with Big Data, such as data collection and data analysis.
Project Manager
Project Managers plan and execute projects. This course may be useful for Project Managers who are responsible for managing Big Data projects. The course will help Project Managers understand the different types of Big Data technologies, and how to use them to plan and execute successful Big Data projects.
Data Governance Officer
Data Governance Officers are responsible for managing and protecting data assets. This course may be useful for Data Governance Officers who are responsible for managing Big Data assets. The course will help Data Governance Officers understand the different types of Big Data technologies, and how to use them to implement effective data governance practices.
Information Security Analyst
Information Security Analysts are responsible for protecting information systems from threats. This course may be useful for Information Security Analysts who are responsible for protecting Big Data systems. The course will help Information Security Analysts understand the different types of Big Data technologies, and how to use them to implement effective information security measures.
Compliance Officer
Compliance Officers are responsible for ensuring that organizations comply with laws and regulations. This course may be useful for Compliance Officers who are responsible for ensuring that organizations comply with laws and regulations related to Big Data. The course will help Compliance Officers understand the different types of Big Data technologies, and how to use them to implement effective compliance programs.
Risk Manager
Risk Managers are responsible for identifying and managing risks. This course may be useful for Risk Managers who are responsible for managing risks related to Big Data. The course will help Risk Managers understand the different types of Big Data technologies, and how to use them to identify and manage risks effectively.
Chief Data Officer
Chief Data Officers are responsible for overseeing the use of data within an organization. This course may be useful for Chief Data Officers who are responsible for overseeing the use of Big Data within their organizations. The course will help Chief Data Officers understand the different types of Big Data technologies, and how to use them to drive business value.

Reading list

We've selected eight 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 Big Data Systems.
Provides a practical introduction to MapReduce, a programming model for processing large datasets. It valuable resource for understanding the underlying technologies used in big data processing.
Provides a concise overview of NoSQL databases. It valuable resource for anyone looking to learn more about the different types of NoSQL databases and their applications.
Comprehensive guide to Spark. It covers a wide range of topics, including Spark architecture, data processing, and machine learning.
Provides a comprehensive overview of big data analytics, from strategic planning to enterprise integration. It covers a wide range of topics, including data management, data analysis, and data visualization.
Comprehensive guide to Hadoop, the open-source framework for big data processing. It provides a detailed overview of Hadoop's architecture and components, as well as practical guidance on using Hadoop for data analysis and processing.
Provides a practical guide to data science. It covers a wide range of topics, including data mining, data analysis, and machine learning.
Provides a gentle introduction to machine learning. It valuable resource for anyone looking to learn more about the basics of machine learning.

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