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Big Data & Hadoop

Become a Expert & Specialization in Big Data & Hadoop

100% Placement Assistance | 1000+ Hiring Partners

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About Big Data & Hadoop

Big Data is emerging as a significant source of business because of Hadoop, Spark and NoSQL technologies to accelerate big data processing. Every day, the world generates 2.99 quintillion bytes of information. The data are growing exponentially on Customer data, sales data, and stocks data, Email, social network links, and instant messages spew from a billion personal devices. Still more data is being collected in the format of Text, photos, music, and video divide and multiply in constant digital world. That’s Big Data. Big Data solutions are designed to capture, process, store, and analyze data so that the right person gets the right information, at the right time.

Who Need This Training?
Fresher’s / Experienced / Diploma / Graduate /Post-Graduate in any Stream.
Duration
450 Hrs (2hrs/Day 12 Months, 4hrs/Day 6 Months or 8hrs/Day 3 Months).
Course Fee Details
$325

Course Overview

  • This course will provide support on Preparing Hadoop Pre-Installed Environment for the industry requirement where everyone can work with the set of technology tools (and analysis techniques) that are built on these “Big Data” environments.

  • Deep understating about Hadoop Distributed file system or HDFS.

  • Providing specific privileges to a user that enables that user to administer Ambari.

  • This course offers you to learn about data fundamentals using Office 365 Excel, MySQL, PostgreSQL, MongoDB very detailed with real time data. Users can learn so many practical applications of pivot tables and Formulas, Function, Queries, Filtering data, String operations, Constraints, Partitioning and Charting.

  • Also this course offers you the deep knowledge into Data ingestion, Data transformation and Data analysis such important role on Sqoop in Hadoop ecosystem.

  • Understating and developing a software framework that allows process massive amounts of unstructured data in parallel across a distributed cluster of processors or stand-alone computers.

  • Implementing the advanced concept of Pig as a boon for programmers who were not good with Java or Python.

  • Implementing the advanced concept of Hive data warehouse system which used for analyzing structured and semi-structured data.

  • Understanding the features of Flume tool for data ingestion in HDFS. This course will provide a fundamental of Storm and Kafka use.

  • Implementing the advanced concept Apache Spark and Scala for parallel processing and data analytics applications across clustered systems.

  • Enterprises are now looking to leverage the big data environment require Big Data Architect who can design and build large-scale development and deployment of Hadoop applications.

  • Module 1: Network Fundamentals, Routing, and Switching Basics"
    Introduction to Networking Network topology architecture Network Standards and protocol stacks Physical Network Connections Ethernet LANs Ethernet Switching Introduction to Wireless LANs IP and IPv4v4 Addressing IPv4 Subnetting Introducing Basic IPv6 TCP and UDP Support and Management Protocols Communications Protocols Web Protocols Virtualization Fundamentals Introduction to Network Security Introduction to IP Telephony and VOIP Implementation Operating Cisco IOS Software and Junos Configuring a Router Exploring the Packet Delivery Process Troubleshooting a Simple Network Configuring Static Routing Understanding and Implementing VLANs and Trunking Routing Between VLANs Introducing Dynamic Routing Introducing OSPF Building Redundant Switched Topologies Improving Redundant Switched Topologies with EtherChannel Exploring Layer 3 Redundancy Introducing WAN Technologies Explaining the Basics of ACLs IP Services Automation and Programmability Implementing Wide Area Networks
  • Module 2: Core Routing and Switching
    Examining Cisco Enterprise Network Architecture Understanding Cisco Switching Paths Implementing Campus LAN Connectivity Building Redundant Switched Topology Implementing Layer 2 Port Aggregation Understanding EIGRP Implementing OSPF Optimizing OSPF Exploring EBGP Implementing Network Redundancy Implementing NAT Introducing Virtualization Protocols and Techniques Understanding Virtual Private Networks and Interfaces Understanding Wireless Principles Examining Wireless Deployment Options Understanding Wireless Roaming and Location Services Examining Wireless AP Operation Understanding Wireless Client Authentication Troubleshooting Wireless Client Connectivity Introducing Multicast Protocols Introducing QoS Implementing Network Services Using Network Analysis Tools Implementing Infrastructure Security Implementing Secure Access Control Understanding Enterprise Network Security Architecture Exploring Automation and Assurance Using Cisco DNA Center Examining the Cisco SD-Access Solution Understanding the Working Principles of the Cisco SD-WAN Solution Understanding the Basics of Python Programming Introducing Network Programmability Protocols Introducing APIs in Cisco DNA Center and vManage
  • Module 3: Advanced Enterprise Routing and switching
    Configure classic EIGRP and named EIGRP for IPv4 and IPv6 Optimize classic EIGRP and named EIGRP for IPv4 and IPv6 Troubleshoot classic EIGRP and named EIGRP for IPv4 and IPv6 Configure Open Shortest Path First (OSPF)v2 and OSPFv3 in IPv4 and IPv6 Optimize OSPFv2 and OSPFv3 behavior Troubleshoot OSPFv2 for IPv4 and OSPFv3 for IPv4 and IPv6 Implement route redistribution using filtering mechanisms Troubleshoot redistribution Implement path control using Policy-Based Routing (PBR) and IP SLAs Configure Multiprotocol-Border Gateway Protocol in IPv4 and IPv6 Optimize MP-BGP in IPv4 and IPv6 environments Troubleshoot MP-BGP for IPv4 and IPv6 Describe the features of Multiprotocol Label Switching Describe the major architectural components of an MPLS VPN Identify the routing and packet forwarding functionalities for MPLS VPNs Explain how packets are forwarded in an MPLS VPN environment Implement Cisco Internetwork Operating System Dynamic Multipoint VPNs Implement Dynamic Host Configuration Protocol Describe the tools available to secure the IPV6 first hop Troubleshoot Cisco router security features Troubleshoot infrastructure security and services
  • Module 4: Deploying Cloud Solutions
    Introduction to Cloud Computing Cloud Architectures Cloud Delivery Models Identity Access Management Amazon Storage Management Basic Operation of Amazon Linux JSON operation in AWS Resources Managing Virtual Machines (Instances) Configuring and attaching Load Balancer to Virtual Machines Content Delivery Service AWS’s DNS-as-a-Service Hosting Routing Policy AWS’s Database-as-a-Service Types of Databases Managing Databases Networking in AWS Cloud Securing and Monitoring the AWS Cloud Managing Applications Developer friendly services
  • Module 5: Implementing High Availability, Storage, and Security in the Cloud."
    High Availability and Business Continuity Minimizing and optimizing Infrastructure cost Manage and Implement the right infrastructure Network Design for a complex large scale deployment Implement the most appropriate data storage architecture Security management systems and compliance controls Design protection of Data at Rest controls Design protection of Data in Flight and Network Perimeter controls Scalability and Elasticity Cloud Migration and Hybrid Architecture Cloud Privacy and Security Governance and auditing for cloud operations. Threats, risk, and requirements landscape. Privacy, data, and digital identity. Data sensitivity, location, and legal jurisdiction. Cloud security approaches and challenges.
  • Module 6: Implementing Microsoft Azure Data Solution
    Understanding Infrastructure-as-a-Service (IaaS), Platform-as-a-Service(PaaS), and Software-as-a-Service (SaaS) Public, Private, and Hybrid cloud models. Core Azure architectural components. Core Azure Services and Products Azure Solutions Azure management tools Securing network connectivity in Azure Core Azure Identity services Security tools and features Azure governance methodologies Monitoring and Reporting in Azure Privacy, Compliance, and Data Protection standards in Azure Working with Data Storage Enabling Team-Based Data Science with Azure Databricks Building Globally Distributed Databases with Cosmos DB Working with Relational Data Stores in the Cloud Performing Real-Time Analytics with Stream Analytics Orchestrating Data Movement with Azure Data Factory Monitoring and Troubleshooting Data Storage and Processing

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