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Big Data Modeling and Management Systems, Калифорнийский университет в Сан-Диего

4.3
(1,959 ratings)

Об этом курсе

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+....

Лучшие рецензии

автор: MP

Oct 17, 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.

автор: VG

Mar 28, 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)

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Рецензии: 309

автор: Javed Ahmad

Apr 24, 2019

Very good Instructors. I have learnt a lot. Thanks to COURSERA.

автор: Liliana del Carmen Castellanos Montero

Apr 17, 2019

muy buen curso

автор: Brian Sotelo

Apr 15, 2019

Expected more hands-on activities and more advanced tasks

автор: Izabelle Azevedo

Apr 11, 2019

Cannot finish Twitter activities as commands shown in the video apparently don´t work with the most recent pyhton version. I am very disappointed about it, since I am mostly focused on Twitter-related data.

автор: Mayank Choudhary

Apr 10, 2019

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автор: Routhana Long

Apr 10, 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.

автор: Wayne Slocum

Apr 06, 2019

This material in this course seems to be based on a belief that the student has significantly more knowledge than assumed for the first course in the Big Data series. Because of this unfounded assumption, without regard to explanation, I have marked it down to four stars vice the five for the first course.

I think by providing the student with an adequate background, or additional resources, this course could easily be ranked as a five-star course.

In short, for no apparent reason, it quickly becomes more difficult than the first course; and instead, I wish it had been more of a natural transition from the first course.

автор: Andrea Contreras

Mar 14, 2019

Excellent course

автор: nchang

Mar 11, 2019

nice course ,assignments are well explained and are well organised

автор: Wiboon ORANSIRIKUL

Mar 06, 2019

Very good lessons