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Ilkay Altintas and Amarnath Gupta

Once you’ve identified a big data issue to analyze, how do you collect, store and organize your data using Big Data solutions? In this course, you will experience various data genres and management tools appropriate for each. You will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools. Through guided hands-on tutorials, you will become familiar with techniques using real-time and semi-structured data examples. Systems and tools discussed include: AsterixDB, HP Vertica, Impala, Neo4j, Redis, SparkSQL. This course provides techniques to extract value from existing untapped data sources and discovering new data sources.

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Once you’ve identified a big data issue to analyze, how do you collect, store and organize your data using Big Data solutions? In this course, you will experience various data genres and management tools appropriate for each. You will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools. Through guided hands-on tutorials, you will become familiar with techniques using real-time and semi-structured data examples. Systems and tools discussed include: AsterixDB, HP Vertica, Impala, Neo4j, Redis, SparkSQL. This course provides techniques to extract value from existing untapped data sources and discovering new data sources.

At the end of this course, you will be able to:

* Recognize different data elements in your own work and in everyday life problems

* Explain why your team needs to design a Big Data Infrastructure Plan and Information System Design

* Identify the frequent data operations required for various types of data

* Select a data model to suit the characteristics of your data

* Apply techniques to handle streaming data

* Differentiate between a traditional Database Management System and a Big Data Management System

* Appreciate why there are so many data management systems

* Design a big data information system for an online game company

This course is for those new to data science. Completion of Intro to Big Data is recommended. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments. Refer to the specialization technical requirements for complete hardware and software specifications.

Hardware Requirements:

(A) Quad Core Processor (VT-x or AMD-V support recommended), 64-bit; (B) 8 GB RAM; (C) 20 GB disk free. How to find your hardware information: (Windows): Open System by clicking the Start button, right-clicking Computer, and then clicking Properties; (Mac): Open Overview by clicking on the Apple menu and clicking “About This Mac.” Most computers with 8 GB RAM purchased in the last 3 years will meet the minimum requirements.You will need a high speed internet connection because you will be downloading files up to 4 Gb in size.

Software Requirements:

This course relies on several open-source software tools, including Apache Hadoop. All required software can be downloaded and installed free of charge (except for data charges from your internet provider). Software requirements include: Windows 7+, Mac OS X 10.10+, Ubuntu 14.04+ or CentOS 6+ VirtualBox 5+.

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What's inside

Syllabus

Introduction to Big Data Modeling and Management
Welcome to this course on big data modeling and management. Modeling and managing data is a central focus of all big data projects. In these lessons we introduce you to the concepts behind big data modeling and management and set the stage for the remainder of the course.
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Big Data Modeling
Modeling big data depends on many factors including data structure, which operations may be performed on the data, and what constraints are placed on the models. In these lessons you will learn the details about big data modeling and you will gain the practical skills you will need for modeling your own big data projects.
Big Data Modeling (Part 2)
These lessons continue to shed light on big data modeling with specific approaches including vector space models, graph data models, and more.
Working With Data Models
Data models deal with many different types of data formats. Streaming data is becoming ubiquitous, and working with streaming data requires a different approach from working with static data. In these lessons you will gain practical hands-on experience working with different forms of streaming data including weather data and twitter feeds.
Big Data Management: The "M" in DBMS
Managing big data requires a different approach to database management systems because of the wide variation in data structure which does not lend itself to traditional DBMSs. There are many applications available to help with big data management. In these lessons we introduce you to some of these applications and provide insight into how and when they might be appropriate for your own big data management challenges.
Designing a Big Data Management System for an Online Game
In these lessons we give you the opportunity to learn about big data modeling and management using a fictitious online game called "Catch the Pink Flamingo".

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches methods and techniques for modeling and managing big data, which is standard in industry
Taught by Amarnath Gupta and Ilkay Altintas, who are recognized for their work in big data
Develops foundational skills in big data modeling and management, which are core skills for data scientists
Offers hands-on experience working with different types of data formats, including streaming data, which is highly relevant to industry
Provides insights into the applications used for big data management, which is useful for personal growth and development
Requires students to have the ability to install applications and utilize a virtual machine, which may be a barrier to some students

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Reviews summary

Big data modeling and management for beginners

Learners say this engaging course covers essential concepts in big data modeling and management. Hands-on exercises reinforce lessons, but some report outdated instructions. Lecturers Dr. Gupta and Dr. Altintas are described as knowledgeable and engaging. Students appreciate the practical examples and applications discussed. Overall, this course provides a solid foundation for those new to big data.
Useful for reinforcing concepts
"The hands-on assignments are not very instructive."
"I understand that the course is intended for general audience and programming or doing serious analysis might be out of its scope, but it falls short at providing a basic standing ground from which the learner could improve."
Examples and applications are helpful
"I really like both instructors.I took one star off because one of the twitter API assignments that we were supposed to do in the VM didn't work."
"Plus there's no one to support you in case an issue like this occurs."
Dr. Gupta and Dr. Altintas are praised
"What a charm are the two instructors Dr. Gupta and Dr. Altintas! They have a really good way of lecturing for all levels."
"Very informative and enjoyable!"
Instructions and software need updating
"I can't give the 5th star because of the hands on exercises that are frozen in time."
"First, with Windows 10 and 11 we have Hyper-V and the course only provides Oracle VMs that are incompatible with Hyper-V."
"Than, the exercises are in Python 2, and in 2022 it's dead and most of the things we can't make them work because there isn't support for that."

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 Modeling and Management Systems with these activities:
Organize your notes, assignments, quizzes, and exams from the course.
Stay organized by compiling and reviewing your course materials regularly to reinforce your learning.
Browse courses on Organization
Show steps
  • Gather all of your notes, assignments, quizzes, and exams from the course.
  • Organize the materials into a logical order.
  • Review the materials periodically to refresh your memory and reinforce your understanding.
Review the materials from the course's prerequisites.
Ensure your foundational knowledge is strong by reviewing the materials from the course's prerequisites.
Show steps
  • Go over your notes, assignments, and quizzes from the prerequisite courses.
  • Take practice questions or complete review exercises to test your understanding.
Form a study group with other students in the course.
Enhance your understanding of the course material by collaborating and discussing concepts with other students.
Browse courses on Collaboration
Show steps
  • Reach out to other students in the course and introduce yourself.
  • Set up a regular meeting time and place for your study group.
  • Discuss the course material, work on practice problems, and share insights.
Ten other activities
Expand to see all activities and additional details
Show all 13 activities
Volunteer at a local data science or technology organization.
Gain practical experience and connect with professionals in the field by volunteering at a local organization.
Browse courses on Data Science
Show steps
  • Research local data science or technology organizations.
  • Identify an organization that you are interested in volunteering for.
  • Contact the organization and inquire about volunteer opportunities.
Learn about Big Data Tools
There are many tools available for Big Data modeling and management. Learn about these tools and how to use them.
Browse courses on Big Data Tools
Show steps
  • Research Big Data tools
  • Find tutorials on Big Data tools
  • Follow the tutorials
Write a Big Data Management Plan
Writing a Big Data Management Plan will help you understand the challenges and opportunities of Big Data management. Write a Big Data Management Plan for a given organization.
Show steps
  • Identify the organization's Big Data needs
  • Develop a Big Data management strategy
  • Create a Big Data management plan
Install and learn to use AsterixDB and HP Vertica.
Learn how to work with two big data management systems to round out your knowledge of these tools.
Browse courses on AsterixDB
Show steps
  • Download and install AsterixDB and HP Vertica.
  • Run tutorials to learn the basics of each system.
  • Explore the documentation of each system to learn more about their features and capabilities.
Practice Working with Hadoop
Working with Hadoop is essential in Big Data and this course. Practice working with Hadoop through drills and exercises to reinforce your skills.
Browse courses on Hadoop
Show steps
  • Install Hadoop
  • Create a Hadoop cluster
  • Run a Hadoop job
Practice writing SQL queries to perform common data operations on various types of data.
Solidify your understanding of SQL and how to use it to manipulate data by completing practice drills.
Browse courses on SQL
Show steps
  • Find a set of SQL practice problems online or in a book.
  • Solve the problems on your own, referring to the documentation as needed.
  • Check your answers against the provided solutions.
Design a Big Data Model
Creating a Big Data Model will help you understand the concepts and techniques of Big Data modeling. Design and create a model for a given Big Data scenario.
Show steps
  • Identify the data sources
  • Choose a data modeling tool
  • Create the data model
  • Validate the data model
Design a big data information system for an online game company.
Apply your knowledge of big data modeling and management to a real-world scenario by designing a system for an online game company.
Show steps
  • Research the data needs of an online game company.
  • Identify the different types of data that the company will need to collect and store.
  • Design a big data information system that can meet the company's data needs.
  • Create a presentation or document that describes your design.
Start a project to build a data visualization dashboard.
Enhance your data visualization and analysis skills by building a dashboard for a dataset of your choice.
Browse courses on Data Visualization
Show steps
  • Choose a dataset that you are interested in.
  • Explore the data and identify the key insights that you want to communicate.
  • Design a dashboard that will effectively communicate these insights.
  • Implement your dashboard using a data visualization tool.
Develop a Big Data Application
Developing a Big Data application is a great way to apply your skills and knowledge. Develop a Big Data application for a real-world problem.
Browse courses on Big Data Applications
Show steps
  • Identify the problem
  • Design the application
  • Implement the application
  • Test the application

Career center

Learners who complete Big Data Modeling and Management Systems will develop knowledge and skills that may be useful to these careers:
Data Scientist
A Data Scientist is a professional who uses data to solve business problems. They collect, clean, and analyze data to identify trends and patterns. They then use these insights to develop solutions that can improve business outcomes. This course can help you develop the skills you need to become a Data Scientist. You'll learn how to collect, clean, and analyze data, and you'll gain experience using real-time and semi-structured data examples.
Data Analyst
A Data Analyst is a professional who uses data to analyze business trends. They collect, clean, and analyze data to identify patterns and trends. They then use these insights to develop reports and recommendations that can help businesses make better decisions. This course can help you develop the skills you need to become a Data Analyst. You'll learn how to collect, clean, and analyze data, and you'll gain experience using real-time and semi-structured data examples.
Data Engineer
A Data Engineer is a professional who designs and builds data systems. They work with data scientists and data analysts to develop solutions that can improve business outcomes. This course can help you develop the skills you need to become a Data Engineer. You'll learn how to design and build data systems, and you'll gain experience using real-time and semi-structured data examples.
Database Administrator
A Database Administrator is a professional who manages and maintains databases. They ensure that databases are running smoothly and that data is secure. This course can help you develop the skills you need to become a Database Administrator. You'll learn how to manage and maintain databases, and you'll gain experience using real-time and semi-structured data examples.
Software Engineer
A Software Engineer is a professional who designs, develops, and maintains software applications. They work with data scientists and data analysts to develop solutions that can improve business outcomes. This course can help you develop the skills you need to become a Software Engineer. You'll learn how to design, develop, and maintain software applications, and you'll gain experience using real-time and semi-structured data examples.
Business Analyst
A Business Analyst is a professional who analyzes business processes and develops solutions to improve efficiency and effectiveness. They work with data scientists and data analysts to develop insights that can help businesses make better decisions. This course can help you develop the skills you need to become a Business Analyst. You'll learn how to analyze business processes and develop solutions to improve efficiency and effectiveness.
Product Manager
A Product Manager is a professional who is responsible for the development and launch of new products. They work with data scientists and data analysts to develop insights that can help businesses make better decisions about product development. This course can help you develop the skills you need to become a Product Manager. You'll learn how to develop and launch new products, and you'll gain experience using real-time and semi-structured data examples.
Marketing Analyst
A Marketing Analyst is a professional who analyzes marketing data to identify trends and patterns. They use these insights to develop marketing campaigns that can reach target audiences and achieve business goals. This course can help you develop the skills you need to become a Marketing Analyst. You'll learn how to analyze marketing data and develop marketing campaigns.
Financial Analyst
A Financial Analyst is a professional who analyzes financial data to identify trends and patterns. They use these insights to make investment recommendations and develop financial plans. This course can help you develop the skills you need to become a Financial Analyst. You'll learn how to analyze financial data and develop financial plans.
Operations Research Analyst
An Operations Research Analyst is a professional who uses mathematical and statistical models to solve business problems. They work with data scientists and data analysts to develop solutions that can improve efficiency and effectiveness. This course can help you develop the skills you need to become an Operations Research Analyst. You'll learn how to use mathematical and statistical models to solve business problems.
Management Consultant
A Management Consultant is a professional who helps businesses improve their performance. They work with data scientists and data analysts to develop insights that can help businesses make better decisions. This course can help you develop the skills you need to become a Management Consultant. You'll learn how to help businesses improve their performance.
Data Architect
A Data Architect is a professional who designs and builds data architectures. They work with data scientists and data analysts to develop solutions that can improve business outcomes. This course may be useful if you want to become a Data Architect because it will help you understand the principles of data architecture.
Information Systems Manager
An Information Systems Manager is a professional who manages and maintains information systems. They work with data scientists and data analysts to develop solutions that can improve business outcomes. This course may be useful if you want to become an Information Systems Manager because it will help you understand the principles of information systems management.
IT Project Manager
An IT Project Manager is a professional who manages and coordinates IT projects. They work with data scientists and data analysts to develop solutions that can improve business outcomes. This course may be useful if you want to become an IT Project Manager because it will help you understand the principles of IT project management.
Data Governance Specialist
A Data Governance Specialist is a professional who develops and implements data governance policies and procedures. They work with data scientists and data analysts to develop solutions that can improve business outcomes. This course may be useful if you want to become a Data Governance Specialist because it will help you understand the principles of data governance.

Reading list

We've selected seven 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 Modeling and Management Systems.
Provides a comprehensive overview of big data analytics, covering both the theoretical and practical aspects. It valuable resource for anyone who wants to learn more about big data analytics, from business leaders to data scientists.
Provides a comprehensive overview of data mining, covering the concepts and techniques used to extract knowledge from large datasets. It valuable resource for anyone who wants to learn how to use data mining to gain insights and make better decisions.
Provides a comprehensive overview of Hadoop, covering the concepts and techniques used to build and manage Hadoop clusters. It valuable resource for anyone who wants to learn how to use Hadoop to process and analyze large datasets.
Provides a comprehensive overview of Spark, covering the concepts and techniques used to build and manage Spark applications. It valuable resource for anyone who wants to learn how to use Spark to process and analyze large datasets.
Provides a comprehensive overview of big data analytics with R, covering the concepts and techniques used to explore and analyze large datasets. It valuable resource for anyone who wants to learn how to use R to gain insights and make better decisions.
Provides a comprehensive overview of big data analytics with Python, covering the concepts and techniques used to explore and analyze large datasets. It valuable resource for anyone who wants to learn how to use Python to gain insights and make better decisions.
Provides a comprehensive overview of big data analytics with Go, covering the concepts and techniques used to explore and analyze large datasets. It valuable resource for anyone who wants to learn how to use Go to gain insights and make better decisions.

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