Big Data I Hadoop I Spark I NiFi I Kafka Course
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.
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