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Ivan Puzyrevskiy,
Pavel Mezentsev,
Emeli Dral,
Alexey A. Dral,
Artyom Vybornov,
Vladislav Goncharenko,
and
Ivan Mushketyk
There is a significant number of tasks when we need not just to process an enormous volume of data but to process it as quickly as possible. Delays in tsunami prediction can cost people’s lives. Delays in traffic jam prediction cost extra time. Advertisements based on the recent users’ activity are ten times more popular.
However, stream processing techniques alone are not enough to create a complete real-time system. For example to create a recommendation system we need to have a storage that allows to store and fetch data for a user with minimal latency. These databases should be able to store hundreds of terabytes of data,...
Read more
There is a significant number of tasks when we need not just to process an enormous volume of data but to process it as quickly as possible. Delays in tsunami prediction can cost people’s lives. Delays in traffic jam prediction cost extra time. Advertisements based on the recent users’ activity are ten times more popular.
However, stream processing techniques alone are not enough to create a complete real-time system. For example to create a recommendation system we need to have a storage that allows to store and fetch data for a user with minimal latency. These databases should be able to store hundreds of terabytes of data,...
Read more
There is a significant number of tasks when we need not just to process an enormous volume of data but to process it as quickly as possible. Delays in tsunami prediction can cost people’s lives. Delays in traffic jam prediction cost extra time. Advertisements based on the recent users’ activity are ten times more popular.
However, stream processing techniques alone are not enough to create a complete real-time system. For example to create a recommendation system we need to have a storage that allows to store and fetch data for a user with minimal latency. These databases should be able to store hundreds of terabytes of data, handle billions of requests per day and have a 100% uptime. NoSQL databases are commonly used to solve this challenging problem.
After you finish this course, you will master stream processing systems and NoSQL databases. You will also learn how to use such popular and powerful systems as Kafka, Cassandra and Redis.
To get the most out of this course, you need to know Hadoop and SQL. You should also have a working knowledge of bash, Python and Spark.
Do you want to learn how to build Big Data applications that can withstand modern challenges? Jump right in!
Register for this course and see more details by visiting:
OpenCourser.com/course/quwtxy/big
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what to watch for , and
possible dealbreakers
Teaches stream processing systems and NoSQL databases, which may be valuable in meeting industry demands for fast data processing
Taught by a team with notable instructors in the field, such as Pavel Mezentsev and Alexey A. Dral
Utilizes widely adopted systems such as Kafka, Cassandra, and Redis, enhancing its practical relevance
Requires prerequisites in Hadoop, SQL, bash, Python, and Spark, potentially limiting accessibility for beginners
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Reviews summary
Disappointing big data course
From the one review of this course, students found that the tools and assignments given were lackluster and, in the case of the first week’s assignment, impossible to complete within any reasonable time frame.
Activities
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Big Data Applications: Real-Time Streaming.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Big Data Applications: Real-Time Streaming will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
Data Engineers help improve the performance of data pipelines and databases and develop tools that data scientists and analysts can use to run machine learning models and generate business insights. This course provides a foundation in stream processing systems, NoSQL databases, Kafka, Cassandra, and Redis, all of which are essential technologies for Data Engineers to master.
Data Scientist
Data Scientist
Data Scientists contribute to the design and implementation of data processing pipelines that transform raw data into actionable insights. This course can help Data Scientists gain proficiency in processing large volumes of streaming data and storing and retrieving data with minimal latency, which are critical skills for building real-time data-driven applications.
Database Administrator
Database Administrator
Database Administrators ensure that databases are operating smoothly and efficiently. This course provides a deep dive into NoSQL databases, which are commonly used for storing and managing large volumes of data in real-time applications. By gaining expertise in these technologies, individuals can enhance their ability to design, implement, and manage scalable and high-performance database systems.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course can help Software Engineers build real-time data processing applications that can handle large volumes of streaming data. The course covers stream processing systems, NoSQL databases, Kafka, Cassandra, and Redis, which are essential technologies for developing scalable and fault-tolerant software systems.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. This course provides a foundation in stream processing systems and NoSQL databases, which are essential technologies for Data Analysts who want to work with real-time data. By gaining expertise in these technologies, individuals can enhance their ability to analyze streaming data and generate actionable insights.
Systems Engineer
Systems Engineer
Systems Engineers design, implement, and maintain complex computer systems. This course can help Systems Engineers build and manage scalable and fault-tolerant systems that can handle large volumes of streaming data. The course covers stream processing systems, NoSQL databases, Kafka, Cassandra, and Redis, which are essential technologies for designing and implementing high-performance systems.
Cloud Architect
Cloud Architect
Cloud Architects design and manage cloud-based infrastructure and applications. This course provides a foundation in stream processing systems and NoSQL databases, which are essential technologies for building real-time data processing applications in the cloud. By gaining expertise in these technologies, individuals can enhance their ability to design and implement scalable and fault-tolerant cloud-based systems.
Business Analyst
Business Analyst
Business Analysts help businesses understand their data and make better decisions. This course can help Business Analysts build a foundation in stream processing systems and NoSQL databases, which are essential technologies for analyzing real-time data. By gaining expertise in these technologies, individuals can enhance their ability to identify trends and patterns in data and provide valuable insights to businesses.
Data Warehouse Engineer
Data Warehouse Engineer
Data Warehouse Engineers design and manage data warehouses, which are used to store and analyze large volumes of data. This course can help Data Warehouse Engineers build a foundation in stream processing systems and NoSQL databases, which are essential technologies for building real-time data warehouses. By gaining expertise in these technologies, individuals can enhance their ability to design and implement scalable and fault-tolerant data warehouses.
DevOps Engineer
DevOps Engineer
DevOps Engineers bridge the gap between development and operations teams. This course can help DevOps Engineers build a foundation in stream processing systems and NoSQL databases, which are essential technologies for building and managing real-time data pipelines. By gaining expertise in these technologies, individuals can enhance their ability to design and implement scalable and fault-tolerant data pipelines.
Information Security Analyst
Information Security Analyst
Information Security Analysts protect computer systems and networks from unauthorized access and attacks. This course can help Information Security Analysts build a foundation in stream processing systems and NoSQL databases, which are essential technologies for detecting and responding to security threats in real-time. By gaining expertise in these technologies, individuals can enhance their ability to design and implement secure systems and networks.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers develop and deploy machine learning models. This course can help Machine Learning Engineers build a foundation in stream processing systems and NoSQL databases, which are essential technologies for building and managing real-time machine learning models. By gaining expertise in these technologies, individuals can enhance their ability to design and implement scalable and fault-tolerant machine learning models.
Software Architect
Software Architect
Software Architects design and develop software systems. This course can help Software Architects build a foundation in stream processing systems and NoSQL databases, which are essential technologies for building scalable and fault-tolerant software systems. By gaining expertise in these technologies, individuals can enhance their ability to design and implement complex software systems.
IT Project Manager
IT Project Manager
IT Project Managers plan and execute IT projects. This course can help IT Project Managers build a foundation in stream processing systems and NoSQL databases, which are essential technologies for managing real-time data projects. By gaining expertise in these technologies, individuals can enhance their ability to plan and execute successful IT projects.
Data Privacy Officer
Data Privacy Officer
Data Privacy Officers develop and implement policies and procedures to protect personal data. This course can help Data Privacy Officers build a foundation in stream processing systems and NoSQL databases, which are essential technologies for managing and protecting real-time data. By gaining expertise in these technologies, individuals can enhance their ability to develop and implement effective data privacy policies and procedures.
For more career information including salaries, visit:
OpenCourser.com/course/quwtxy/big
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Time
26 hours
Via
Coursera
Institution
Yandex
Instructors
Ivan Puzyrevskiy
Pavel Mezentsev
Emeli Dral
Alexey A. Dral
Artyom Vybornov
Vladislav Goncharenko
Ivan Mushketyk
This course belongs to a
collection
called
Big Data for Data Engineers. It's comprised of five courses:
- Big Data Services: Capstone Project
- Big Data Applications: Machine Learning at Scale
- Big Data Applications: Real-Time Streaming (viewing)
- Big Data Essentials: HDFS, MapReduce and Spark RDD
- Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames
Good to know
Teaches stream processing systems and NoSQL databases, which may be valuable in meeting industry demands for fast data processing
Taught by a team with notable instructors in the field, such as Pavel Mezentsev and Alexey A. Dral
Utilizes widely adopted systems such as Kafka, Cassandra, and Redis, enhancing its practical relevance
Requires prerequisites in Hadoop, SQL, bash, Python, and Spark, potentially limiting accessibility for beginners
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