ETL (Extract, Transform, Load) is a vital process in data management and analytics, with a wide range of applications across different sectors and functions like Data Warehousing, Data Integration, Business Intelligence, Data Migration and more, which why ETL is an important process in Data related operations in IT. Our ETL Training Institute has the most up-to-date syllabus and modern infrastructure, along with experienced trainers as well. Therefore, our ETL Course will give students a holistic learning of ETL, which will eventually give them a prolonged, high-paying career in ETL as a Data Engineer and so on. So go ahead and explore more down below to get all the information you need about our ETL Course with certification & placements.
ETL Training
4.80
(1024)
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DURATION
2 Months
Mode
Live Online / Offline
EMI
0% Interest
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What this Course Includes?
- Technology Training
- Aptitude Training
- Learn to Code (Codeathon)
- Real Time Projects
- Learn to Crack Interviews
- Panel Mock Interview
- Unlimited Interviews
- Life Long Placement Support
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Course Schedules
Course Syllabus
Course Fees
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Breakdown of ETL Training Fee and Batches
Hands On Training
3-5 Real Time Projects
60-100 Practical Assignments
3+ Assessments / Mock Interviews
April 2025
Week days
(Mon-Fri)
Online/Offline
2 Hours Real Time Interactive Technical Training
1 Hour Aptitude
1 Hour Communication & Soft Skills
(Suitable for Fresh Jobseekers / Non IT to IT transition)
Course Fee
April 2025
Week ends
(Sat-Sun)
Online/Offline
4 Hours Real Time Interactive Technical Training
(Suitable for working IT Professionals)
Course Fee
Save up to 20% in your Course Fee on our Job Seeker Course Series
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Syllabus of ETL Training
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Module 1 : DWH Data Ware Housing Concepts
- What is Data Warehouse?
- Need of Data Warehouse
- Introduction to OLTP, ETL and OLAP Systems
- Difference between OLTP and OLAP
- Data Warehouse Architecture
- Data Marts
- ODS [Operational Data Store]
- Dimensional Modelling
- Difference between relation and dimensional modelling
- Star Schema and Snowflake Schema
- What is fact table
- What is Dimension table
- Normalization and De-Normalization
Module 2 : ETL Testing
- ETL architecture.
- What is ETL and importance of ETL testing
- How DWH ETL Testing is different from the Application Testing
- SDLC/STLC in the ETL Projects (ex: V Model, Water fall model)
Module 3 : Challenges in DWH ETL Testing compare to other testing
- Incompatible and duplicate data
- Loss of data during ETL process
- Testers have no privileges to execute ETL jobs by their own
- Volume and complexity of data is very huge
- Fault in business process and procedures
- Trouble acquiring and building test data
Module 4 : ETL Testing Work flow activities involved
- Analyze and interpret business requirements/ workflows to Create estimations
- Approve requirements and prepare the Test plan for the system testing
- Prepare the test cases with the help of design documents provided by the
- developer team
- Execute system testing and integration testing
- Best practices to Create quality documentations (Test plans, Test Scripts and Test closure summaries)
- How to detect the bugs in the ETL testing
- How to report the bugs in the ETL testing
- How to co-ordinate with developer team for resolving the defects
Module 5 : Types of ETL Testing
- Data completeness
- Data transformation
- Data quality
- Performance and scalability
- Integration testing
- User-acceptance testing
- SQL Queries for ETL Testing
- Incremental load testing
- Initial Load / Full load testing
Module 6 : Different ETL tools available in the market
- Informatica
- Ab Initio
- IBM Data stage
Module 7 : Power Center Components
- Designer
- Repository Manager
- Workflow Manager
- Workflow Monitor
- Power Center Admin Console
Module 8 : Informatica Concepts and Overview
- Informatica Architecture
Module 9 : Sources
- Working with relational Sources
- Working with Flat Files
Module 10 : Targets
- Working with Relational Targets
- Working with Flat file Targets
Module 11 : Transformations – Active and Passive Transformations
- Expression
- Lookup –Different types of lookup Caches
- Sequence Generator
- Filter
- Joiner
- Sorter
- Rank
- Router
- Aggregator
- Source Qualifer
- Update Strategy
- Normalizer
- Union
- Stored Procedure
- Slowly Changing Dimension
- SCD Type1
- SCD Type2 — Date, Flag and Version
- SCD Type3
Module 12 : Workflow Manger
- Creating Reusable tasks
- Workflows, Worklets & Sessions
- Tasks
- Indirect Loading
- Constraint based load ordering
- Target Load plan
- Worklet ,Mapplet ,Resuable transformation
- Migration ?ML migration and Folder Copy
- Scheduling Workflow
- Parameter and variables
- XML Source, Target and Transformations
Module 13 : Performance Tuning
- Pipeline Partition
- Dynamic Partition
- Pushdown optimization
- Preparation of Test Cases
- Executing Test case
- Preparing Sample data
- Data validation in Source and target
- Load and performance testing
- Unit testing Procedures
- Error handling procedures
Objectives of Learning ETL Training
Download Syllabus
The ETL Training will cover all the topics ranging from fundamental to advanced concepts, which will make it easy for students to grasp ETL. The ETL Course Curriculum is composed of some of the most useful and rare concepts that will surely give students a complete understanding of ETL as well. So, some of those curriculum are discussed below as objectives:
- To make students more well-versed with fundamental concepts of ETL like – Data Warehousing, Challenges in ETL Testing, Types of ETL Testing etc.
- To make students know more about ETL by making them learn concepts like – ETL Tools – Informatica, Ab Initio, IBM Data stage, Power Center Components, Informatica Architecture etc.
- To make students knowledgeable in advanced ETL concepts like – Sources, Targets, Active and Passive Transformation, Workflow Manager, Performance Tuning etc.
Reason to choose SLA for ETL Training
- SLA stands out as the Exclusive Authorized Training and Testing partner in Tamil Nadu for leading tech giants including IBM, Microsoft, Cisco, Adobe, Autodesk, Meta, Apple, Tally, PMI, Unity, Intuit, IC3, ITS, ESB, and CSB ensuring globally recognized certification.
- Learn directly from a diverse team of 100+ real-time developers as trainers providing practical, hands-on experience.
- Instructor led Online and Offline Training. No recorded sessions.
- Gain practical Technology Training through Real-Time Projects.
- Best state of the art Infrastructure.
- Develop essential Aptitude, Communication skills, Soft skills, and Interview techniques alongside Technical Training.
- In addition to Monday to Friday Technical Training, Saturday sessions are arranged for Interview based assessments and exclusive doubt clarification.
- Engage in Codeathon events for live project experiences, gaining exposure to real-world IT environments.
- Placement Training on Resume building, LinkedIn profile creation and creating GitHub project Portfolios to become Job ready.
- Attend insightful Guest Lectures by IT industry experts, enriching your understanding of the field.
- Panel Mock Interviews
- Enjoy genuine placement support at no cost. No backdoor jobs at SLA.
- Unlimited Interview opportunities until you get placed.
- 1000+ hiring partners.
- Enjoy Lifelong placement support at no cost.
- SLA is the only training company having distinguished placement reviews on Google ensuring credibility and reliability.
- Enjoy affordable fees with 0% EMI options making quality training affordable to all.
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Highlights of The ETL Training
What is ETL?
ETL, which stands for Extract, Transform, Load, is a data management process involving the collection of data from diverse sources, its transformation into a usable format, and its loading into a target system. This process is essential for integrating data, maintaining quality, and preparing it for analysis and reporting.
What is ETL Full Stack?
ETL Full Stack encompasses the entire ETL process, integrating tools and technologies for each phase: extracting data from diverse sources, transforming it through cleaning and conversion, loading it into storage systems, orchestrating workflows, managing data quality, and connecting with BI tools for analysis and reporting.
What are the reasons for learning ETL?
The following are the reasons for learning ETL Course:
- Data Integration: ETL expertise allows you to merge data from various sources, providing a consolidated view necessary for thorough analysis.
- Career Advancement: Skills in ETL open opportunities in roles such as Data Engineer, Data Analyst, and BI Developer, which are highly sought after.
- Enhanced Data Quality: ETL processes improve data accuracy and reliability by cleaning and transforming it for better decision-making.
- Improved Reporting and Analytics: With ETL knowledge, you can prepare data for Business Intelligence (BI) tools, enhancing reporting and analytical capabilities.
What are the prerequisites for learning ETL?
The following are the prerequisites for learning ETL, but they are not mandatory:
- Fundamental Data Management: Knowledge of basic data concepts like data types, database schemas, and normalization is essential.
- Database Proficiency: Understanding relational databases and the ability to query them using SQL (Structured Query Language) is crucial for data extraction and manipulation.
- Programming Basics: Skills in programming languages such as Python, Java, or R can assist in scripting and automating ETL tasks.
- Data Format Awareness: Familiarity with various data formats (e.g., CSV, JSON, XML) and their roles in data exchange and storage is beneficial.
What are the course fees and duration?
Our ETL Course Fees may vary depending on the specific course program you choose (basic / intermediate / full stack), course duration, and course format (remote or in-person). On an average the ETL Course Fees range from 25k to 30k, for a duration of 2 months total with international certification.
What are some of the jobs related to ETL?
The following are the jobs related to ETL:
- ETL Developer
- Data Engineer
- Data Analyst
- Business Intelligence (BI) Developer
- Data Scientist
- Database Administrator (DBA)
List a few real time ETL applications.
The following are the real-time ETL applications:
- Fraud Detection Systems
- Social Media Analytics
- Financial Market Monitoring
- E-commerce Personalization
- IoT Data Processing
- Customer Experience Management
Who are our Trainers for ETL Training?
Our Mentors are from Top Companies like:
- Our ETL trainers are dedicated experts in enterprise data warehousing and business analytics, possessing extensive technical knowledge and experience.
- They bring practical skills in developing, managing, and optimizing data warehouses, and are proficient in extracting, transforming, and loading data from various sources.
- With a deep understanding of ETL applications and platforms, they instruct students on database development, data integration, data analysis, analytics, and reporting.
- They prepare students for certification exams through illustrative examples and live training sessions.
- Their strong communication and interpersonal skills foster effective learning and coordination with students.
- They excel in creating ETL processes for software applications, managing both structured and unstructured data, and applying best practices in data mapping.
- The trainers are capable of designing ETL workflows, performing data validation, and using ETL testing tools.
- They are also experienced in monitoring and maintaining data warehouses and resolving complex ETL issues.
- Using ETL testing tools and methods, they assess student performance and offer feedback to enhance technical skills.
- Their collaborative and supportive approach helps students acquire the knowledge needed to secure positions in leading IT companies.
Want to Speak to our Trainer about ETL Training?Request a Free Callback
What Modes of Training are available for ETL Training?
Offline / Classroom Training
A Personalized Learning Experience with Direct Trainer Engagement!
- Direct Interaction with the Trainer
- Clarify doubts then and there
- Airconditioned Premium Classrooms and Lab with all amenities
- Codeathon Practices
- Direct Aptitude Training
- Live Interview Skills Training
- Direct Panel Mock Interviews
- Campus Drives
- 100% Placement Support
Online Training
Instructor Led Live Training! Learn at the comfort of your home
- No Recorded Sessions
- Live Virtual Interaction with the Trainer
- Clarify doubts then and there virtually
- Live Virtual Interview Skills Training
- Live Virtual Aptitude Training
- Online Panel Mock Interviews
- 100% Placement Support
Corporate Training
Blended Delivery model (both Online and Offline as per Clients’ requirement)
- Industry endorsed Skilled Faculties
- Flexible Pricing Options
- Customized Syllabus
- 12X6 Assistance and Support
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Project Practices for ETL Training
Email Campaign Performance
Implement an ETL pipeline to extract metrics from email marketing platforms (such as open rates and click-through rates), aggregate and clean the data, and load it into a data warehouse for performance analysis and reporting.
Web Traffic Analysis
Extract web traffic data from server logs or analytics tools, aggregate and filter it, and load it into a data warehouse. Develop reports and visualizations to evaluate user behavior, traffic trends, and website performance.
IoT Sensor Data Management
Set up an ETL process to collect data from IoT sensors, clean and aggregate the data, and load it into a cloud-based data warehouse. Use this data for real-time monitoring and to trigger alerts based on predefined conditions.
Healthcare Data Integration
Extract patient information from different healthcare systems (like electronic health records and lab results), standardize it to meet privacy and compliance requirements, and load it into a data warehouse for integrated patient insights and healthcare analytics.
Financial Transactions Monitoring
Financial Transactions Monitoring: Develop an ETL pipeline to handle financial transactions in real-time, extracting data from logs, transforming it to validate and categorize transactions, and loading it into a system for live fraud detection and financial analysis.
Real-Time Inventory Management
Create an ETL process to continuously gather inventory data from various sources (such as POS systems and supplier databases), standardize it, and load it into a real-time inventory management system to monitor stock levels and enhance supply chain efficiency.
Social Media Sentiment Analysis
Extract social media content via APIs, process the data by cleaning and scoring sentiment, and load it into a database. Use this data to examine trends and sentiments over time.
Customer Analytics Dashboard
Build an ETL pipeline to merge customer data from multiple sources (like websites, mobile apps, and support tickets) into a data warehouse. Transform the data to create detailed customer profiles and load it into a BI tool to develop a live analytics dashboard.
Sales Data Consolidation
Extract sales information from diverse sources such as e-commerce platforms and CRM systems, standardize it, and load it into a central data warehouse for integrated reporting and analysis.
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FAQs for
ETL Training
What are some effective strategies for enhancing ETL performance?
1.
Effective strategies include optimizing queries and transformations, leveraging parallel processing, reducing data movement, implementing incremental loading, and tuning ETL jobs for specific systems. Regular performance monitoring and addressing bottlenecks are also crucial for improving efficiency.
How can you maintain data quality throughout the ETL process?
2.
Maintaining data quality involves applying validation rules, performing data cleansing, managing exceptions, and using data profiling tools. Regular data audits and consistency checks are essential to ensure accuracy and reliability.
What methods can be used to manage large volumes of data in ETL processes?
3.
Methods for managing large data volumes include data partitioning, employing bulk loading techniques, optimizing transformations, utilizing distributed computing, and compressing data. ETL processes should be designed to process data in batches or chunks to handle memory and processing constraints effectively.
How should schema changes in source data be handled during ETL?
4.
Handling schema changes involves designing flexible ETL systems that can adapt to changes, using metadata management for tracking modifications, and applying version control for schema updates. Automated tools that support schema evolution can also assist in managing these changes smoothly.
Why is metadata crucial in ETL processes?
5.
Metadata is crucial in ETL processes as it provides details about data sources, structures, transformation rules, and data lineage. It helps in managing ETL processes, ensuring consistency, supporting data governance, and aiding in troubleshooting.
How can real-time ETL be implemented and what are its challenges?
6.
Real-time ETL can be achieved through streaming data technologies and tools that enable immediate data ingestion and processing. Challenges include maintaining data consistency, managing high throughput, dealing with latency issues, and addressing real-time data quality concerns.
What security practices should be followed during ETL processes?
7.
Security practices include encrypting data both in transit and at rest, enforcing access controls and authentication, masking sensitive information, and conducting regular security audits. Compliance with data protection regulations and using secure data transfer methods are also important.
What types of tests are involved in ETL testing and how is it performed?
8.
ETL testing includes validating data accuracy, completeness, and consistency. Types of tests involve checking data extraction, verifying transformation correctness, validating data loading, performing performance tests, and conducting regression testing. Automated testing tools and frameworks can enhance the reliability and accuracy of ETL processes.
Where is the corporate office of Softlogic Systems located?
9.
The corporate office of the Softlogic Systems is located at the institute’s K.K.Nagar branch.
What payment methods does Softlogic accept?
10.
Softlogic accepts a wide range of payment methods, including:
- Cash
- Debit cards
- Credit cards (MasterCard, Visa, Maestro)
- Net banking
- UPI
- Including EMI.
Additional Information for
ETL Training
1.
Scopes available in the future for learning ETL.
The following are the scopes available in the future for learning the ETL Course:
- Enhanced Data Integration: With a growing blend of on-premises and cloud-based systems, advanced ETL processes will be necessary to unify diverse data sources, including emerging technologies like IoT, edge computing, and blockchain.
- Real-Time Data Handling: The need for real-time analytics and decision-making is rising. Mastery of ETL will involve learning to manage real-time data processing frameworks and tools to handle live data streams and provide immediate insights.
- Big Data Management: Skills in ETL will be crucial for working with big data technologies such as Hadoop, Spark, and cloud-based data lakes. These environments require specialized ETL processes to handle and process extensive data volumes effectively.
- Integration with Machine Learning and AI: ETL processes will increasingly support machine learning and AI by preparing and transforming data for model training and algorithm deployment in production settings.
- Focus on Data Quality and Governance: Future ETL practices will place a stronger emphasis on data quality and governance, utilizing advanced techniques for validation, cleansing, and ensuring compliance with data lineage and regulatory standards.
- Cloud-Based ETL Platforms: As organizations continue to transition to the cloud, proficiency in cloud-based ETL solutions like AWS Glue, Azure Data Factory, and Google Cloud Dataflow will be essential, offering scalability and flexibility.
- Adoption of DataOps and Automation: ETL will increasingly integrate with DataOps methodologies, emphasizing automation, continuous integration, and the deployment of data workflows through modern orchestration tools and automated pipelines.
- Advanced Business Intelligence and Analytics: ETL skills will be crucial for preparing data for sophisticated business intelligence and analytics tools, aiding organizations in generating actionable insights and making informed decisions.
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