Go to Course: https://www.coursera.org/learn/big-data-integration-processing
### Course Review and Recommendation: Big Data Integration and Processing In today’s data-driven world, understanding how to manage and process large datasets is a vital skill. Coursera’s “Big Data Integration and Processing” course, part of their Big Data Specialization, offers an excellent opportunity for newcomers to data science to dive deep into the intricacies of big data management. With a clear and structured syllabus, this course prepares learners to tackle the essential challenges of big data. #### Course Overview Upon completion of the “Big Data Integration and Processing” course, you will achieve several key competencies: - **Data Retrieval**: You will learn to retrieve data from example databases and big data management systems. - **Data Management Operations**: The course will help you understand the relationships between data management operations and the big data processing patterns necessary for large-scale analytical applications. - **Problem Identification**: You'll be equipped to identify when a big data problem requires data integration. - **Big Data Integration and Processing**: Finally, you’ll execute fundamental big data integration and processing tasks using Hadoop and Spark platforms. This course is particularly ideal for beginners, but it assumes that you have completed the introductory course “Intro to Big Data” for better comprehension of the material. #### Syllabus Breakdown The syllabus consists of several modules, each designed to focus on specific aspects of big data processing: 1. **Welcome to Big Data Integration and Processing**: This introductory week sets the stage for the entire course by covering basic concepts, installing essential tools (like the Cloudera VM), and setting up your Jupyter server for practical exercises. 2. **Retrieving Big Data (Part 1)**: Here, you’ll delve into relational querying and data retrieval through Postgres, laying the groundwork for more complex data structures. 3. **Retrieving Big Data (Part 2)**: Expanding on the first part, this module introduces you to NoSQL databases such as MongoDB and Aerospike. You will also learn how to work with data frames using Pandas, empowering you to handle diverse data formats. 4. **Big Data Integration**: This module focuses on data integration tools like Splunk and Datameer, offering practical insights into the processes that drive information integration. 5. **Processing Big Data**: You will explore the concepts of big data pipelines, workflows, and the essentials of processing large datasets utilizing Apache Spark. 6. **Big Data Analytics using Spark**: Diving deeper, you will examine Spark Core and two vital tools, Spark MLlib and GraphX, which are pivotal for big data analytics. 7. **Learn By Doing: Putting MongoDB and Spark to Work**: This hands-on module allows you to apply what you have learned by analyzing Twitter data, cementing your understanding through practical application. #### Review The “Big Data Integration and Processing” course stands out for its comprehensive and intuitive approach. The sequential layout of modules supports easy comprehension, making it accessible for individuals without prior experience in data science. The practical hands-on experiences not only reinforce learning but also build confidence as you work with real-world data applications. The resources provided, such as video lectures, quizzes, and community discussions, enhance the learning process, while the well-structured content provides a solid foundation for further exploration in big data analytics. #### Recommendation I highly recommend the “Big Data Integration and Processing” course on Coursera for anyone who is stepping into the field of data science. Its robust curriculum and practical focus equip learners with valuable skills that are increasingly in demand across industries. By the end of this course, you will not only grasp the principles of big data integration and processing but also be prepared to tackle real-world problems in data management. Whether you are looking to begin a career in data science, pivot your current job role, or broaden your knowledge base, this course is a worthwhile investment in your professional development. Embrace the opportunity to deepen your expertise in big data and set yourself up for success in an evolving field!
Welcome to Big Data Integration and Processing
Welcome to the third course in the Big Data Specialization. This week you will be introduced to basic concepts in big data integration and processing. You will be guided through installing the Cloudera VM, downloading the data sets to be used for this course, and learning how to run the Jupyter server.
Retrieving Big Data (Part 1)This module covers the various aspects of data retrieval and relational querying. You will also be introduced to the Postgres database.
Retrieving Big Data (Part 2)This module covers the various aspects of data retrieval for NoSQL data, as well as data aggregation and working with data frames. You will be introduced to MongoDB and Aerospike, and you will learn how to use Pandas to retrieve data from them.
Big Data IntegrationIn this module you will be introduced to data integration tools including Splunk and Datameer, and you will gain some practical insight into how information integration processes are carried out.
Processing Big DataThis module introduces Learners to big data pipelines and workflows as well as processing and analysis of big data using Apache Spark.
Big Data Analytics using SparkIn this module, you will go deeper into big data processing by learning the inner workings of the Spark Core. You will be introduced to two key tools in the Spark toolkit: Spark MLlib and GraphX.
Learn By Doing: Putting MongoDB and Spark to WorkIn this module you will get some practical hands-on experience applying what you learned about Spark and MongoDB to analyze Twitter 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
Very Interactive course. Theatrical classes are nicely drafted. Hands On exercises are interesting and some are challenging too. Overall very interesting course. Happy learning
Some of the lectures seemed slightly lesser quality with regards to the materials. For moocs especially, I would like to have the lecture better documented in order to download and review later.
The quiz was a bit difficult since there was no much guidance on how to sort in descending order and how to find the total times a country was mentioned in a single tweet.
It was a good course, it could have been better if some examples of Spark were also provided in other Languages like Java, people without having background of python may find it difficult.
Hello Gentlemen,\n\nThis course was very helpful foe me. It enhanced my knowledge about Big Data Integration. Thank you so much for providing me such important knowledge. Thank you once again.