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Big Data I Hadoop I Spark I NiFi I Kafka Course

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Big Data I Hadoop I Spark I NiFi I Kafka Course

Big Data I Hadoop I Spark I NiFi I Kafka Course

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Before the world changed to digital, data was small and stored at a very sluggish pace. Data was documents stored in rows and columns, storing and processing this data was simple.

But, in the year 2005 internet took the world by storm, there was tons of data in a multitude of forms and formats, semi-structured, structured data is available in form of emails, images, audio and video, and all kinds of data.

All this data is collectively known as Big Data.

What is Big Data?

Big data is a broader term in the sense that it is used for very large data sets which are considered so complex and informative on which traditional data processing applications are considered as inadequate. This is the kind of extremely large data sets that are analyzed through computational algorithms in order to reveal patterns, trends, associations, and differences specifically related to human interactions and behavior.

As big data is associated with a very large amount of data sets, therefore it does not refer to any specific quantity. However, data in terabytes, petabytes of exabytes is considered as big data.

Though Big Data is an interesting concept over overtime it became impossible to handle Big Data.

What is the solution?

Multiple storage units needed an app and this concept was integrated into Hadoop Framework, which can store and process vast amounts of data using a cluster of community hardware.

Hadoop consists of three components that were specially designed to work on by data.

Storage Unit is the first component of Hadoop, data is stored in many computers and stored in blocks.

MapReduce is the second component of Hadoop, in traditional data processing method entire data is processed on a single machine having a single processor, it is time-consuming and is inefficient when processing large volumes of data to overcome this MapReduce splits data into parts and processes each of them separately on different nodes, individual results are aggregated to give final results.

Yarn is the third component, its consists of resource manager, application master, and container.

Hadoop ecosystem comprises several other components like Hive, Pig, Apache Spark, flume, and Scoop.

Hadoop is used by companies like Facebook, IBM, eBay, Amazon, and many more.

Hadoop Applications

Data warehousing

Fraud Detection

Recommendation System

What is Spark?

Spark is in-memory computing keeping the data and improves performance by an order of magnitude.

Memory is always faster than disc, spark comes with better processing and streaming process. Spark is a great choice for cluster computing and includes language API for Scala, Java, Python, and R.

Spark can be integrated with different Hadoop ecosystem tools.

What is NiFi?

Nifi supports powerful and scalable dissected graphs of data routing, transformation, and system mediation logic.

Automate the flow of data between systems.

Drag and drop interface.

Focus on the configuration of processors i.e what matters to users.

Scalable across a cluster of machines

Data buffering/ back pressure/ Prioritization/queuing

NiFi is good for

Reliable secure transfer of data between systems.

Delivery of data from sources to an analytics platform

Enrichment and preparation of data

Conversion between formats

Extraction/pairing routing decisions

What is Kafka?

Kafka allows you to decouple the data streams and your system, source systems have data in apache Kafka and target systems source data directly from apache Kafka.

You can have any data streams in Kafka such as

Website events, pricing data, financial transactions, user interactions, database, analytics, audit, etc.

Created by LinkedIn, Kafka is an open-source project mainly maintained by Confluent. It is distributed resilient architecture, and fault-tolerant.

Kafka is used by LinkedIn, Uber, Airbnb, Netflix, and Walmart, and other 2000+ firms.

Brainmeasures Big Data, Hadoop, Spark, Nifi, and Kafka video course and certification program.

Brainmeasures Big data, Hadoop, Spark, Nifi and Kafka video course has been designed to help the candidates master the big data ecosystem. Curated by experts this is an all-inclusive course for Hadoop, spark, nifi, and Kafka. Understand what’s and why’s of the big data system and get certified. Brainmeasures certifications are used for professional purposes and Brainmeasures certifications are acknowledge and accepted by employers globally.

Pre-requisites for this course

SQL and RDBMS Basics

Unix/Linux Basic Commands

Twitter Account

What this course covers

Big Data fundamentals

Hadoop Fundamentals

Distributed Processing

Mapreduce

Data persistence

Spark Fundamentals

Kafka

Building Dataflows

Job Opportunities for certified Professionals

This certification has a tremendous growth rate with rapidly increasing use of intelligence and information systems in complex environments and the business world where data is the prime factor to make decisions based on analysis and finalization of the processes.

Database Analyst

Business Intelligence Expert

Online Information System Manager

Online Data Analyzer

Information System Analyst ERP Analyst

Business Reporting Expert

Big Data Visualizer

Information Sorter

Data Miner

Information Management Controller

Certified Information System and Business Analyst

Virtual Assistant in Information and Big Data Tracking

Big Data experts earn well, the average data engineer salary in US markets is $116,591.

Related Courses

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Hadoop Developer Course

Apache Spark Course

Apache Kafka l Kafka connect course

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Course Syllabus

Getting Started 11 lectures 17 mins
Introduction Preview 01:42
Welcome guide document 10 Pages
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Welcome guide document 10 Pages
Some title goes here 07:42
2 Some title goes here 07:42
Hello Some title goes here 07:42
This is Some title goes here 07:42

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