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.
Этот курс входит в специализацию ''Специализация Большие данные'
Big Data Modeling and Management Systems
от партнера
Об этом курсе
Недавно просмотрено: 103,852
Карьерные результаты учащихся
45%
начал новую карьеру, пройдя эти курсы
37%
получил значимые преимущества в карьере благодаря этому курсу
Приобретаемые навыки
Data ModelBig DataData ModelingData Management
Карьерные результаты учащихся
45%
начал новую карьеру, пройдя эти курсы
37%
получил значимые преимущества в карьере благодаря этому курсу
Сертификат, ссылками на который можно делиться с другими людьми
Получите сертификат по завершении
100% онлайн
Начните сейчас и учитесь по собственному графику.
Курс 2 из 6 в программе
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Прибл. 16 часа на выполнение
Предполагаемая нагрузка: 6 weeks of study, 2-3 hours/week
Английский
Субтитры: Английский
от партнера
Калифорнийский университет в Сан-Диего
UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.
Программа курса: что вы изучите
3 ч. на завершение
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.
3 ч. на завершение
14 видео ((всего 63 мин.)), 8 материалов для самостоятельного изучения
14 видео
Why is this a New Course in the Big Data Specialization?41
Summary of Introduction to Big Data (Part 1)5мин
Summary of Introduction to Big Data (Part 2)5мин
Summary of Introduction to Big Data (Part 3)5мин
Big Data Management "Must-Ask Questions"1мин
Data Ingestion4мин
Data Storage3мин
Data Quality2мин
Data Operations3мин
Data Scalability and Security2мин
Energy Data Management Challenges at ConEd4мин
Gaming Industry Data Management: Q&A with Apmetrix CTO Mark Caldwell7мин
Flight Data Management at FlightStats: A Lecture by CTO Chad Berkley13мин
8 материала для самостоятельного изучения
Slides: Summary of Introduction to Big Data10мин
Slides: Big Data Management10мин
Reading on Storage Systems10мин
Slides: Energy Data Management Challenges at ConEd10мин
Slides: Flight Data Management at FlightStats10мин
Downloading and Installing the Cloudera VM Instructions (Windows)10мин
Downloading and Installing the Cloudera VM Instructions (Mac)10мин
Instructions for Downloading Hands On Datasets10мин
3 ч. на завершение
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.
3 ч. на завершение
11 видео ((всего 52 мин.)), 8 материалов для самостоятельного изучения, 1 тест
11 видео
Data Model Structures2мин
Data Model Operations4мин
Data Model Constraints4мин
Introduction to CSV Data4мин
What is a Relational Data Model?10мин
What is a Semistructured Data Model?6мин
Exploring the Relational Data Model of CSV Files4мин
Exploring the Semistructured Data Model of JSON data3мин
Exploring the Array Data Model of an Image3мин
Exploring Sensor Data4мин
8 материала для самостоятельного изучения
Slides: What Is A Data Model?10мин
Introduction to CSV Data10мин
Slides: What Is A Relational Data Model?10мин
Slides: What is a Semistructured Data Model?10мин
Exploring the Relational Data Model of Comma Separated Values (CSV)10мин
Exploring the Semistructured Data Model of JSON data10мин
Exploring the Array Data Model of an Image10мин
Exploring Sensor Data10мин
1 практическое упражнение
Practical Quiz for Week 2 Hands-On Lectures18мин
2 ч. на завершение
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.
2 ч. на завершение
5 видео ((всего 31 мин.)), 5 материалов для самостоятельного изучения, 1 тест
5 видео
Vector Space Model11мин
Graph Data Model7мин
Other Data Models4мин
Exploring the Lucene Search Engine's Vector Data Model4мин
Exploring Graph Data Models with Gephi3мин
5 материала для самостоятельного изучения
Slides: Vector Space Model10мин
Slides: Graph Data Model10мин
Slides: Other Data Models10мин
Exploring Vector Data Models with Lucene10мин
Exploring Graph Data Models with Gephi10мин
1 практическое упражнение
Data Models Quiz18мин
2 ч. на завершение
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.
2 ч. на завершение
6 видео ((всего 29 мин.)), 7 материалов для самостоятельного изучения, 1 тест
6 видео
What is a Data Stream?5мин
Why is Streaming Data different?7мин
Understanding Data Lakes5мин
Exploring Streaming Sensor Data4мин
Exploring Streaming Twitter Data (Optional)4мин
7 материала для самостоятельного изучения
Slides: Data Model vs. Data Format10мин
Slides: What is a Data Stream?10мин
Slides: Why is Streaming Data Different?10мин
Slides: Understanding Data Lakes10мин
Exploring Streaming Sensor Data10мин
Instructions for Creating a Twitter App (Optional)10мин
Exploring Streaming Twitter Data (Optional)10мин
1 практическое упражнение
Data Formats and Streaming Data Quiz18мин
Рецензии
Лучшие отзывы о курсе BIG DATA MODELING AND MANAGEMENT SYSTEMS
от партнера PRMar 6, 2018
Pretty good course. The peer corrected assignment is avoidable. Instead, a little bit of programming may be introduced! The course becomes extremely boring due to only theoretical aspects and quizzes.
от партнера DNNov 22, 2016
Pretty good overall, although some exercises are a bit difficult to understand from the descriptions and instructions given, some graphs and initial reference documentation for exercises might help
от партнера MPOct 16, 2017
Good Explanations of Concepts and Nice Tests. I got a trilling experience in completing the peer Assignments with keen observation and Analyzing of Concepts learned.Thanq for your course very much.
от партнера VGMar 27, 2017
Nice course to describe the traditional data modeling (RDBMS) as well as various semi-structured and un-structured data modeling and management of the systems (Batch and Streaming data processing)
от партнера YGOct 30, 2016
Overall relevant and clear presentations. Course material quite general, but I guess this is expected from an introductory-level course.\n\nPeer-reviewed assignment's instructions can be clearer.
от партнера JWMay 7, 2019
I feel as though the assessment questions could have been more specific and the assessment criteria when marking could have been more precise. But other than that it was a great course.
от партнера MMSep 29, 2019
Big Data modeling is important consideration while designing big data solution. Most of other online courses lacks this module. Thanks to coursera for bringing this course. Five star.
от партнера BROct 10, 2018
It was a difficult module, although trainer tried to convey but seems it is more complex it took time for me to understand the concept and apply the same while doing my assignment.
от партнера CJFeb 3, 2018
Great overview of a few databases and what they are good at. Would have liked actual hands-on like installing a database and demonstrating the key feature the database is good at.
от партнера ACMar 23, 2020
It's a good course to get an overview of different technologies that are out there. I would highly recommend this course to anyone who wants to build a foundation for big data.
от партнера PPMar 14, 2020
If you have the fundamental knowledge of database and json, the only valuable videos for you are in week 5. As it says in next course(course 3), the course 2 is not required.
от партнера RLApr 9, 2019
As a undergraduate data analytics student, this course was an enlightening experience that complemented my more theoretical, less-applicational on campus course very well.
Специализация Большие данные: общие сведения
Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted. Apply your insights to real-world problems and questions.
*********
Do you need to understand big data and how it will impact your business? This Specialization is for you. You will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. Previous programming experience is not required! You will be guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive. By following along with provided code, you will experience how one can perform predictive modeling and leverage graph analytics to model problems. This specialization will prepare you to ask the right questions about data, communicate effectively with data scientists, and do basic exploration of large, complex datasets. In the final Capstone Project, developed in partnership with data software company Splunk, you’ll apply the skills you learned to do basic analyses of big data.
Часто задаваемые вопросы
Когда я получу доступ к лекциям и заданиям?
Зарегистрировавшись на сертификацию, вы получите доступ ко всем видео, тестам и заданиям по программированию (если они предусмотрены). Задания по взаимной оценке сокурсниками можно сдавать и проверять только после начала сессии. Если вы проходите курс без оплаты, некоторые задания могут быть недоступны.
Что я получу, оформив подписку на специализацию?
Записавшись на курс, вы получите доступ ко всем курсам в специализации, а также возможность получить сертификат о его прохождении. После успешного прохождения курса на странице ваших достижений появится электронный сертификат. Оттуда его можно распечатать или прикрепить к профилю LinkedIn. Просто ознакомиться с содержанием курса можно бесплатно.
Какие правила возврата средств?
Можно ли получить финансовую помощь?
Остались вопросы? Посетите Центр поддержки учащихся.