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学生对 加州大学圣地亚哥分校 提供的 Big Data Modeling and Management Systems 的评价和反馈

2,791 个评分
468 条评论


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+....


Oct 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.

Mar 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)


26 - Big Data Modeling and Management Systems 的 50 个评论(共 457 个)

创建者 Andrew C

Dec 11, 2018

Level of content between week four and five is vastly gapped. Too big of a jump. No explanation of BDMS and DBMS in between

创建者 Kaddoum R

Nov 16, 2016

Too high level. Last assignment too ambiguous, peer assessment was completely random and not reliable to pass the course.

创建者 James K

Feb 11, 2017

Too simple, no programming, just theory.

创建者 Irfan S

Sep 26, 2017

Very basic and lack real time

创建者 Leslie X

Jun 23, 2016

hard to follow not because it is difficult, but the lecture is only slides, texts, reading slides, very boring and not so many hand-on instruction. only thing i remember is the instructor's face after finish this class. Dont know why you add this into such a good specialist.

创建者 Robert P

Sep 25, 2016

Poorly designed assignment on data modeling did little to expand my knowledge on the topic. Which is a shame since the individual lectures were well done and very interesting. The "Pink Flamingo" peer-peer-reveiwed exercise needs to go.

创建者 Kjell L

Sep 12, 2016

The last peer review is really hard to do. Hard is because the wording is very ambiguous and not all understand how to review. There was a guy who answered with SQL query. This is hardcore since we have not learned that yet...

创建者 John F

Aug 10, 2020

Maybe this course would have made more sense at the end of the specialization. But here it just seems like an unnecessary spike in difficulty to understand (not necessarily difficulty to pass) due to the poor lecturing style.

创建者 William R

Oct 5, 2016

As a manager in an IT consultancy, I can't justify sending my personnel through this course, even at $69 per course. The amount of information gained is very thin and does not move one toward being productive.

创建者 Niti

Nov 5, 2017

The content is only intended for people who have a background in this field. The peer graded assignment is completely unclear on instructions . the test is not at all well devised. I am regretting.

创建者 Rafael M

Jan 6, 2021

constant problem during every exercise, Prepare to spend more time troubleshooting virtual machine problems and CentOS 6 issues than learning about BIG Data

创建者 Deleted A

Aug 30, 2018

Disastrous set-up of grading assignment. Waiting for 7 days to get rated. No possibility to contact any Coursera staff directly.

创建者 Avazeh G

Oct 18, 2020

Boring, impractical, very broad, 4 years out of date. Trains you on a bunch of clunky definitions but no useful substance

创建者 Piyush P

Sep 29, 2017

This course is the worst course on Coursera. I can't understand what it is trying to achieve.

创建者 Seth D

Aug 18, 2016

Very basic, the 'hands on' exercises are not very hands on and do not actually add much value

创建者 Kari S

Feb 13, 2017

Course material is very poor and did not give much support for doing assignments.

创建者 Nick G

Mar 10, 2020

This course is SERIOUSLY out dated and hasn't been updated in several years.

创建者 Qian H

Jul 10, 2017

Bad course without many useful info

创建者 andrehmerli

Nov 6, 2016

The course gives an extensive overview of the topic. I have particularly appreciated the hands on section.

My recommendation to all the students is to not overlook the hands on and create some personal notes and code archive to quickly review those topics.

Some particular good learning for myself: lucene. I have used lucene at work both directly and wrapped within elastic search: in both cases I was not going deep in understanding the data model behind lucene and concepts like similarity. You can leave like that in the vast majority of the current jobs where lucene is a third party system invoked upon needs but understanding the model behind was simply much more easy than I expected.

创建者 Joydeep S

Jul 18, 2017

This course was really nice and very well put together. I learned a lot and more so, learned in a structured manner. For people like me who come from traditional data background and new to big data concepts this way of presenting the course is very important and fruitful. I hoping to complete the rest of the courses in this series and end up with a good depth in knowledge of big data

创建者 Jose A R N

Sep 13, 2017

My name is Jose Antonio. I am looking for a new Data Scientist career (

I did this course to get new knowledge about Big Data and better understand the technology and your practical applications.

The course was excellent and the classes well taught by the Teachers.

Congratulations to Coursera team and Teachers.

创建者 sarsiz

May 13, 2017

I thoroughly enjoyed this course. The content was good and it definitely needs some changes. You should explain according to me in more detail about how using a particular method of data structure you can structure the data. The exercise was easy. And please add some more exercise so that learners need to work little harder to pass the quiz.

创建者 Sukanta M

Nov 15, 2017

I was looking for this type of course of BigData. I have spent hours to read through different blogs and articles. But couldn't get better idea/direction how to start or where to start. This is ideal course for getting started on Big Data. I enjoyed all the slides and hands on very much. Thank you.

创建者 Sita R P G

Oct 23, 2016

Modeling is the start and gives an insight how to choose the correct model for a big data project. The correct choice of the model spells success for the project. Many data models were introduced and the hands-on exercises were helpful in better understanding of the concepts.

创建者 Mohamad K

Aug 20, 2019

Its extremely an important course to understand the different between DBMS and BIG data and why DBMS changed to BDMS. Its also give nice intro to unstructured data process such images and graph Nodes. Study this course will remove many questions in your mind.