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Courses>Database Design & Development>Learning Path: SMACK: Getting Started with the SMACK Stack
DevelopmentLearning Path: SMACK: Getting Started with the SMACK Stack
Price:Paid
Length:11 hours
Content type:video
level:beginner
Updated:19 February 2024
Published:21 August 2022
Similar courses
Opportunities
Courses>Database Design & Development>Learning Path: SMACK: Getting Started with the SMACK Stack
Learning Path: SMACK: Getting Started with the SMACK Stack
3.2 (137.0)
11 hours
137 students
What you will learn
1Basic concepts of Scala
2Analysing data using Spark in Scala
3Creation of fast data processing using SMACK Stack
Target audiences
1Data Analysts, Data Scientists, and Business Analysts can use this course to make highly precise and fast data models.
Requirements
1Experience with Scala is essential
2Basic knowledge of data processing concepts
FAQ
You can view and review the lecture materials indefinitely, like an on-demand channel.
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
Description

If you want to outrun your competitors by taking business decisions using your data, then this course is for you. 

SMACK is an open source full stack for big data architecture. It is a combination of Spark, Mesos, Akka, Cassandra, and Kafka. This stack is the newest technique developers have begun to use to tackle critical real-time analytics for big data. 

SMACK: Getting Started with Scala, Spark, and the SMACK Stack gets you familiar with Scala and understanding the various features offered by it. You will also get to understand the process for data analysis using Spark. Finally, you will be introduced to the SMACK Stack which helps us to process data blazingly fast. Development using these technologies can be summarized as: More data: Less Time. 

This Learning Path is a learner material and the curriculum is so planned to meet your learning needs. It starts with the basics of Apache Spark, one of the trending big data processing frameworks on the market today.  We it moves on to Scala, which has emerged as an important tool for performing various data analysis tasks efficiently. It will help you leverage popular Scala libraries and tools to perform core data analysis tasks with ease in Spark. In the last part, we will teach you how to integrate the SMACK stack to create a highly efficient data analysis system for fast data processing.

By the end of the course, you’ll be able to analyze and process data swiftly and efficiently as compared to other traditional data analytic systems.

About the Author:

For this course, we have combined the best works of this esteemed author:

 Nishant Garg has over 16 years of software architecture and development experience in various technologies, such as Java Enterprise Edition, SOA, Spring, Hadoop, Hive, Flume, Sqoop, Oozie, Spark, YARN, Impala, Kafka, Storm, Solr/Lucene, NoSQL databases (such as HBase, Cassandra, and MongoDB), and MPP databases (such as GreenPlum). He received his MS in software systems from the Birla Institute of Technology and Science, Pilani, India, and is currently working as a senior technical architect for the Big Data R&D Labs with Impetus Infotech Pvt. Ltd. Nishant has also undertaken many speaking engagements on big data technologies and is also the author of Learning Apache Kafka & HBase Essestials, Packt Publishing.

Anatolii Kmetiuk has been working with Scala-based technologies for four years. He has experience in Deep Learning models for text processing. He is interested in Category Theory and Type-level programming in Scala. Another field of interest is Chaos and Complexity Theory and Artificial Life, and ways to implement them in programming languages. 

Raúl Estrada Aparicio is a programmer since 1996 and Java Developer since 2001. He loves functional languages such as Scala, Elixir, Clojure, and Haskell. He also loves all the topics related to Computer Science. With more than 12 years of experience in High Availability and Enterprise Software, he has designed and implemented architectures since 2003.His specialization is in systems integration and has participated in projects mainly related to the financial sector. He has been an enterprise architect for BEA Systems and Oracle Inc., but he also enjoys Mobile Programming and Game Development. He considers himself a programmer before an architect, engineer, or developer.

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Make the most out of your online education
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Careertail
Courses>Database Design & Development>Learning Path: SMACK: Getting Started with the SMACK Stack
DevelopmentLearning Path: SMACK: Getting Started with the SMACK Stack
Price:Paid
Length:11 hours
Content type:video
level:beginner
Updated:19 February 2024
Published:21 August 2022
Similar courses
Opportunities
Courses>Database Design & Development>Learning Path: SMACK: Getting Started with the SMACK Stack
Learning Path: SMACK: Getting Started with the SMACK Stack
3.2 (137.0)
11 hours
137 students
What you will learn
1Basic concepts of Scala
2Analysing data using Spark in Scala
3Creation of fast data processing using SMACK Stack
Target audiences
1Data Analysts, Data Scientists, and Business Analysts can use this course to make highly precise and fast data models.
Requirements
1Experience with Scala is essential
2Basic knowledge of data processing concepts
FAQ
You can view and review the lecture materials indefinitely, like an on-demand channel.
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
Description

If you want to outrun your competitors by taking business decisions using your data, then this course is for you. 

SMACK is an open source full stack for big data architecture. It is a combination of Spark, Mesos, Akka, Cassandra, and Kafka. This stack is the newest technique developers have begun to use to tackle critical real-time analytics for big data. 

SMACK: Getting Started with Scala, Spark, and the SMACK Stack gets you familiar with Scala and understanding the various features offered by it. You will also get to understand the process for data analysis using Spark. Finally, you will be introduced to the SMACK Stack which helps us to process data blazingly fast. Development using these technologies can be summarized as: More data: Less Time. 

This Learning Path is a learner material and the curriculum is so planned to meet your learning needs. It starts with the basics of Apache Spark, one of the trending big data processing frameworks on the market today.  We it moves on to Scala, which has emerged as an important tool for performing various data analysis tasks efficiently. It will help you leverage popular Scala libraries and tools to perform core data analysis tasks with ease in Spark. In the last part, we will teach you how to integrate the SMACK stack to create a highly efficient data analysis system for fast data processing.

By the end of the course, you’ll be able to analyze and process data swiftly and efficiently as compared to other traditional data analytic systems.

About the Author:

For this course, we have combined the best works of this esteemed author:

 Nishant Garg has over 16 years of software architecture and development experience in various technologies, such as Java Enterprise Edition, SOA, Spring, Hadoop, Hive, Flume, Sqoop, Oozie, Spark, YARN, Impala, Kafka, Storm, Solr/Lucene, NoSQL databases (such as HBase, Cassandra, and MongoDB), and MPP databases (such as GreenPlum). He received his MS in software systems from the Birla Institute of Technology and Science, Pilani, India, and is currently working as a senior technical architect for the Big Data R&D Labs with Impetus Infotech Pvt. Ltd. Nishant has also undertaken many speaking engagements on big data technologies and is also the author of Learning Apache Kafka & HBase Essestials, Packt Publishing.

Anatolii Kmetiuk has been working with Scala-based technologies for four years. He has experience in Deep Learning models for text processing. He is interested in Category Theory and Type-level programming in Scala. Another field of interest is Chaos and Complexity Theory and Artificial Life, and ways to implement them in programming languages. 

Raúl Estrada Aparicio is a programmer since 1996 and Java Developer since 2001. He loves functional languages such as Scala, Elixir, Clojure, and Haskell. He also loves all the topics related to Computer Science. With more than 12 years of experience in High Availability and Enterprise Software, he has designed and implemented architectures since 2003.His specialization is in systems integration and has participated in projects mainly related to the financial sector. He has been an enterprise architect for BEA Systems and Oracle Inc., but he also enjoys Mobile Programming and Game Development. He considers himself a programmer before an architect, engineer, or developer.

Similar courses
Opportunities
Make the most out of your online education
Careertail
Copyright © 2021 Careertail.
All rights reserved
Quick Links
Get StartedLog InAbout UsCourses
Company
BlogContactsPrivacy PolicyCookie PolicyTerms and Conditions
Stay up to date
Trustpilot