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Big Data Integration and Processing

Big Data,

At the end of the course, you will be able to: *Retrieve data from example database and big data management systems *Describe the connections between data management operations and the big data processing patterns needed to utilize them in large-scale analytical applications *Identify when a big data problem needs data integration *Execute simple big data integration and processing on Hadoop and Spark platforms 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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Rating 3.9 based on 333 ratings
Length 7 weeks
Starts Jul 3 (42 weeks ago)
Cost $79
From University of California San Diego via Coursera
Instructors Ilkay Altintas, Amarnath Gupta
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science
Tags Data Science Data Analysis

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What people are saying

big data integration

Its provide good platform for you to explore and do projects in spark and mongodb A kick start for Big Data Integration and processing.Thanks to my faculty for this wonderful course.

I learn both the basic ideas on the big data integration and processing, and the useful tools, like Spark, MongoDB, etc.

The final week was demanding and fleshed out concepts It was a very helpful course in understanding of the Big Data Integration and Processing.

So, in general, the course provides you with significant knowledge about big data integration processing, however there were simple exercises that could be done faster if there were no problems executing the commands.

Awesome I found this quite beneficial for me, as it provide all the relevant knowledge that is required to know all about Big Data Integration and Processing.

I loved it and invite you to try it, not only it is really hands on but you would have a taste of what is Big Data Integration and Processing.

Very nice course, it gives a new and good knowledge about Big Data Integration and Processing beautiful Very useful course.

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hands on exercises

the explanation for the hands on exercises are poor.

I enjoyed the course content, as well as the hands on exercises/quizzes.Thank you!

easy to understand and great hands on exercises.

But faced lots of issues during practicing the hands on exercises and did not get proper feedback or response on any of the queries.

instalation for pyspark is not working properly Amazing part of the specialization where first time interacted with spark and mongodb, great tech This course focuses entirely on theory and there are very few hands on exercises .

This course was very informative and provided some very good hands on exercises Too many software issues/installation bugs hampering the learning process.

An excellent overview of the subject that combines a strong theorical approach with very interesting and complete hands on exercises.I recommend the whole specialization.

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final project

Excellent final project.

Only the exercises are redeeming in giving some useful, hands-on experience with some applications but then the final project required extensive googling to figure out how to work with pyspark dataframes that weren't taught in the course.

If you do then the simplest Jupyter exercise it fails - this took me about 10 hours to figure out.Then for the final Project, technically to succeed you must miss country names in all lower case and you cannot match with countries with a 'space' e.g.

The final project is a bit tough but worth it.

The course is ok until the final project which is totally not compatible with the level of the hands on during the course ,the final project is a mess Useful course.

The final project makes a good job on making you apply a Big Data Processing Pipeline to solve a common task these days with SparkSQL: analyzing data on social media.

Great Teachers and great course that course had alot of technical training , i enjoyed every bit of it , specialy the final project , it gave you a little guidance with more space for you to develop more I did liked the subjects on this course!

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apache spark

More Hands on experience should be included.Reading of Apache Spark documentation should be made mandatory for beginners.

Would expect more fro Coursera on Apache Spark and NOSQL database courses Fantastic Course I some issues with installation of the right versions for assignments etc.

Excellent course design, it gives you basic of MongoDB, Splunk and Apache Spark.

The assignments including mongodb and apache spark are worth doing.

This is a very descent to understand MongoDB and Apache Spark.

The course is introductory level, and I recommend this course to people who have not used MongoDB and Apache Spark.

I have a much better grasp of Apache Spark and its role in big data processing and integration as a result of this course.

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about big

I am looking for a new Data Scientist career (https://www.linkedin.com/in/joseantonio11)I did this specialization to get new knowledge about Big Data and better understand the technology and your practical applications.

I learnt a lot of stuff about Big Data processing in a simple and clear way.

I learned quite a bit about Big Data problems and the varioius technologies, especially Spark, that you can use for those problems Assigments would be more complexity but for a beginner they are enough to understand framework.

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setup instructions

Good material and challenging assignments, but too many technical issues with setup instructions and spark context.

A lot of participants have had problems running shell scripts and other setup instructions that are necessary to perform some tasks, and their posts have been ignored.

My only significant complaint (and why I rated 4 stars vs. 5) is that the setup instructions for the environment needed for the hands-on exercises needs to be updated.

but it would be highly appreciated and would bring more potential students to this course if the setup instructions where more clear and right on the issue.

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Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

Volunteer Big Data Engineer $48k

Data Scientist - Big Data $68k

Big Data and AWS Data Lake $73k

Big Data Developer (Streaming Data) $77k

Big data developer with AWS $78k

Research Scientist Big Data $94k

Big Data Developer Consultant $98k

Big Data Engineer 6 $107k

Big data and ETL specialist $121k

Big Data Specialist $149k

Principal Big Data Architect $180k

Senior Big Data Sales $181k

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Rating 3.9 based on 333 ratings
Length 7 weeks
Starts Jul 3 (42 weeks ago)
Cost $79
From University of California San Diego via Coursera
Instructors Ilkay Altintas, Amarnath Gupta
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science
Tags Data Science Data Analysis

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