Prerequisites
To apply for the Apache NIFI Training, you need to either:
- To learn big data Analytics tools you need to know at least one programming language like Java, Python or R.
- You must also have basic knowledge on databases like SQL to retrieve and manipulate data.
- You need to have knowledge on basic statistics like progression, distribution, etc. and mathematical skills like linear algebra and calculus.
Course Curriculum
Module 1: Overview of Big Data and Hadoop
- 1.1 Introduction to Big Data and Hadoop
- 1.2 Overview of various components of the Hadoop ecosystem
Module 2: The architecture of Big Data
- 2.1 The architecture of Big Data Hadoop
- 2.2 The architecture of the Hadoop Distributed File System
- 2.3 The Architecture of MapReduce
Module 3: Data Lake Concepts and Constructs
- 3.1 Introduction to the Data Lake concept
- 3.2 Attributes in Data Lake
- 3.3 Support for colocation of data in various formats
- 3.4 Overcoming the problem of data silos
Module 4: Data Ingestion Tools and Concepts
- 4.1 NiFi Processor
- 4.2 Data ingestion tools
- Importing
- Transferring
- loading and processing of data
- 4.3 Introduction to Apache NiFi for data ingestion
Module 5: Data Ingestion Layer
- 5.1 Data transferring in the Data ingestion layer
- 5.2 Different types of data ingestion
Module 6: Apache NiFi Concepts
- 6.1 Apache NiFi fundamentals
- 6.2 FlowFile FlowFile
- 6.3 FlowFile Processor
- 6.4 Flow Controller
- 6.5 Dataflow Attributes and Functions in Flow Controller
Module 7: Apache NiFi Architecture
- 7.1 Introduction to Apache NiFi Architecture
- 7.2 Various components in Apache NiFi
- 7.3 FlowFile Repository
- 7.4 Content Repository
- 7.5 Provenance Repository
- 7.6 Web-based user interface
Module 8: Installation Requirements and Cluster Integration
- 8.1 Apache NiFi installation requirements
- 8.2 Cluster integration
- 8.3 How to run Apache NiFi Successfully
- 8.4 Adding a processor
- 8.5 Scaling up and down
- 8.6 Working with attributes
Module 9: Key Features of Apache NiFi
- 9.1 Important features of Apache NiFi
- 9.2 The dataflow function
- 9.3 Various aspects of FlowFile
- 9.4 File Professor
- 9.5 Flow Controller
- 9.6 Processor group and connection
Module 10: Queuing and Buffering Data
- 10.1 Data buffering in Apache NiFi
- 10.2 The concept of queuing
- 10.3 Latency and recovery
- 10.4 Working with directed graphs
- 10.5 Controller services
- 10.6 Data routing and transformation
- 10.7 Processor configuration
- 10.8 Connection and addition
Module 11: Database Connection with NiFi
- 11.1 Connecting NiFi to the Database
- 11.2 Transforming, Splitting, and Aggregating Data
- 11.3 Data egress processing
- 11.4 NiFi monitoring
- 11.5 Reporting
- 11.6 Data lineage
- 11.7 NiFi administration
- 11.8 Expression language
Module 12: NiFi Configuration Best Practices
- 12.1 Various best practices in Apache NiFi configuration
- 12.2 ZooKeeper access and properties
- 12.3 Encryption
- 12.4 The custom properties
- 12.5 Guidelines for developers
- 12.6 NiFi Kerberos interface
- 12.7 Data security in Hadoop
- 12.8 Installation of Apache NiFi,
- 12.9 Configuration
- 12.10 Deploying the toolbar
- 12.11 Building a dataflow using NiFi
- 12.12 Working with various templates
- Creating, Exporting & Importing them to construct a dataflow
- 12.13 Deploying batch ingestion and real-time ingestion in Apache NiFi
