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Talend
Talend is an open source data integration platform. It provides various software and services for data integration, data management, enterprise application integration, data quality, cloud storage and Big Data. Talend is considered to be the next generation leader in the cloud and Big Data integration software. It helps companies in taking real-time decisions and become more data-driven. Using Talend, data becomes more accessible, its quality enhances and it can be moved quickly to the target systems.

Training Outcomes
Complete understanding of the ETL concepts and ability to solve the real-time business problems using Talend
Comprehensive knowledge of Talend Architecture and its various Components
Familiarity with Talend Tool to automate your complete Data Integration/ Data Analysis/ Data Warehousing requirements
Interaction with various types of source or target platform like Flat Files (CSV, Fixed width), XML, Excel and work with Databases
Implementation of the real-time scenarios for Data Transformation, File & Error Handling, Scheduling Talend jobs, Automation/Parameterization
Understanding of Big Data and Hadoop concepts and the benefits of integrating Talend with Hadoop
Easy integration and Access to Hadoop Ecosystem using Talend
Implementation of Talend with HDFS, Pig, and Hive (the most demanded and futuristic skills)
Rigorous involvement of an SME throughout the Talend Training to learn industry standards and best practices
COURSE OUTLINE
Topic : Overview of the concept of Data Warehouse.
Topic : · Dimensions, Hierarchy, Facts
Topic : DW models:- Star and Snowflake schemas.
Topic : SCD: - Slowly changing Dimension types and their maintenance.
Topic : Introduction to talend.
Topic : Installation of talend TOS_DI 6.0
Topic : ·Architecture of the Talend server client enterprise version and the comparison with the TOS.
Topic : Explaining the model design and it’s palette.
Topic : ·Explaining the job designer and it’s palette.
Topic : ·Explaining the project settings and perspective and views on the GUI.
Topic : Starting talend job design and development.
Topic : Basic understanding of various types of components in talend.
Topic : Importance of the schema in configuration and setting of the components.
Topic : Database connectivity testing.
Topic : Simple jobs with random data generation.
Topic : Job versioning
SQLAlchemy
SQLAlchemy is a popular SQL toolkit and Object Relational Mapper. It is written in Python and gives full power and flexibility of SQL to an application developer. It is an open source and cross-platform software released under MIT license. SQLAlchemy is famous for its object-relational mapper (ORM), using which, classes can be mapped to the database, thereby allowing the object model and database schema to develop in a cleanly decoupled way from the beginning.

Training Outcomes
Data access techniques
Use SQLAlchemy to access your DB
What an ORM is and why you should use it
Map classes to the database
Generate the database from your in-memory models
Use the more flexible SQLAlchemy core layer
COURSE OUTLINE
Module 1 : SQLAlchemy Core
Module 2 :SQLAlchemy ORM
Module 3 : Simple statements
Module 4 : Simple ORM
Module 5 : SQLAlchemy Philosophy
Module 6 :Advanced statements
Module 7 : ORM and relations
Module 8 : Advanced ORM
Splunk
Splunk, one of the highly-used data analysis software is utilized by global organizations for searching, analyzing and monitoring through huge amount of data. Other benefits of Splunk includes report generation, dashboard creation, and visualizing of data on real-time basis. The areas where it is mostly effective, are application management, security and web analytics.

Training Outcomes
Understand Splunk Power User/ concepts.
Apply various Splunk techniques to visualize data using different graphs and dashboards.
Implement Splunk in the organization to Analyze and Monitor systems for operational intelligence.
Configure alerts and reports for monitoring purposes.
Troubleshoot different application logs issues using SPL (Search Processing Language).
Implement Splunk Indexers, Search Heads, Forwarder, Deployment Servers & Deployers.
Understand Splunk Power User/ concepts.
Apply various Splunk techniques to visualize data using different graphs and dashboards.
Implement Splunk in the organization to Analyze and Monitor systems for operational intelligence.
Configure alerts and reports for monitoring purposes.
Troubleshoot different application logs issues using SPL (Search Processing Language).
Implement Splunk Indexers, Search Heads, Forwarder, Deployment Servers & Deployers.
COURSE OUTLINE
Module 1 – Basic Understanding of Architecture
Module 2 – Introduction to Splunk's User Interface
Module 3 – Searching
Module 4 – Using Fields in Searches
Module 5 – Creating Reports and Visualizations
Module 6 – Working with Dashboards
Module 7 – Search Fundamentals
Spark using Python
This training is designed to provide you the knowledge and skills that are required to become a successful Spark Developer using Python and prepare you for the Cloudera Hadoop and Spark Developer Certification Exam (CCA175). Throughout the PySpark Training, you will get an in-depth knowledge of Apache Spark and the Spark Ecosystem

Training Outcomes
Use Python and Spark together to analyze Big Data
Learn how to use the new Spark 2.0 DataFrame Syntax
Work on Consulting Projects that mimic real world situations!
Classify Customer Churn with Logisitic Regression
Use Spark with Random Forests for Classification
Learn how to use Spark’s Gradient Boosted Trees
Use Spark’s MLlib to create Powerful Machine Learning Models
Learn about the DataBricks Platform!
Get set up on Amazon Web Services EC2 for Big Data Analysis
Learn how to use AWS Elastic MapReduce Service!
Learn how to leverage the power of Linux with a Spark Environment!
Create a Spam filter using Spark and Natural Language Processing!
Use Spark Streaming to Analyze Tweets in Real Time!
Use Python and Spark together to analyze Big Data
Learn how to use the new Spark 2.0 DataFrame Syntax
Work on Consulting Projects that mimic real world situations!
Classify Customer Churn with Logisitic Regression
Use Spark with Random Forests for Classification
Learn how to use Spark’s Gradient Boosted Trees
Use Spark’s MLlib to create Powerful Machine Learning Models
Learn about the DataBricks Platform!
Get set up on Amazon Web Services EC2 for Big Data Analysis
Learn how to use AWS Elastic MapReduce Service!
Learn how to leverage the power of Linux with a Spark Environment!
Create a Spam filter using Spark and Natural Language Processing!
Use Spark Streaming to Analyze Tweets in Real Time!
COURSE OUTLINE
Module 1: Introduction to Big Data Hadoop and Spark
Module 2: Introduction to Python for Apache Spark
Module 3: Functions, OOPs, and Modules in Python
Module 4: Deep Dive into Apache Spark Framework
Module 5 : Playing with Spark RDDs
Module 6 :DataFrames and Spark SQL
Module 7 : Machine Learning using Spark MLlib
Module 8 : Deep Dive into Spark MLlib
Module 9 : Understanding Apache Kafka and Apache Flume
Module 10 : Apache Spark Streaming - Processing Multiple Batches
Module 11 : Apache Spark Streaming - Data Sources
Module 12 : Implementing an End-to-End Projec
Module 13 : Spark GraphX (Self-Paced)
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