Class Location

Online class via Zoom

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Years of Experience in SQL Programming Training

8

Teaching Experience in detail in SQL Programming Training

I have 8 years of experience in SQL Programming, in both teaching and real time. I will teach you all concepts in SQL with real time scenarios.

Class Location

Online class via Zoom

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Years of Experience in Microsoft Power BI classes

10

Teaching Experience in detail in Microsoft Power BI classes

I have ten years of experience in teaching BI platform forms. I will teach you end-to-end concepts in PowerBI, from installation to expert BI visualization creation. I have experience in different domains in production banking and finance. The course starts with developing and implementing Power BI ad hoc and long-term reports for different applications. I will teach you how to create prototyping, design, develop, and publish Power BI Reports. Teach how to troubleshoot and resolve issues related to performance, environments, monitoring, and operability of Power BI reports within a given time frame. We will provide clear steps on how to collaborate with Business Analysts to gather business requirements for Analytics and Reporting.

Class Location

Online class via Zoom

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Years of Experience in Azure Data Factory Training

10

Teaching Experience in detail in Azure Data Factory Training

I have 5+ years of professional experience in Azure Data Engineering, with strong hands-on expertise in Azure Data Factory (ADF) for designing and implementing scalable data integration pipelines. I provide practical, industry-focused training in Azure Data Factory to help learners understand real-time data engineering workflows. My training covers Azure Data Factory from beginner to advanced level, with a strong emphasis on hands-on practice and real-world project scenarios. In my sessions, I teach the following key topics: Introduction to Azure Data Factory and its architecture Creating and managing Linked Services and Datasets Building ADF Pipelines and different activities Data ingestion using Copy Activity Working with Integration Runtime Implementing parameterization and dynamic content Pipeline scheduling using Triggers Monitoring and debugging pipelines Error handling techniques in ADF Implementing ETL and ELT data pipelines Integration with Azure Data Lake, Azure SQL Database, and Azure Databricks Performance optimization and best practices The training includes hands-on exercises and real-time project implementation, where learners build an end-to-end data pipeline using Azure Data Factory. I also support learners with: Practical assignments Real-time industry use cases Azure Data Engineering interview preparation Best practices followed in real projects My goal is to help students gain practical skills and confidence to work with Azure Data Factory in real-time data engineering environments.

Class Location

Online class via Zoom

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Years of Experience in Azure Databricks Courses

10

Teaching Experience in detail in Azure Databricks Courses

I have 5+ years of professional experience in Azure Data Engineering, with strong hands-on expertise in Azure Databricks, PySpark, and big data processing. I provide industry-oriented training in Azure Databricks, focusing on practical implementation and real-time data engineering use cases. My training is designed to help learners understand end-to-end big data processing using Azure Databricks and Apache Spark, starting from fundamentals to advanced optimization techniques. The key topics covered in my Azure Databricks training include: Introduction to Azure Databricks Databricks workspace overview Cluster creation and management Notebooks and collaborative development Apache Spark Architecture Spark components (Driver, Executor, Cluster Manager) RDD vs DataFrames vs Datasets Distributed data processing concepts Working with DataFrames Creating DataFrames Data transformations Reading data from Azure Blob Storage to Databricks Reading Data from Azure Data Lake Storage (ADLS Gen2) Mounting storage Accessing files from ADLS Gen2 Data ingestion best practices PySpark Functions and Joins Built-in PySpark functions Filtering, aggregations, and transformations Different types of joins (Inner, Left, Right, Full) Slowly Changing Dimension – SCD Type 2 Concept and real-time use cases Implementing SCD Type 2 using PySpark and Delta Lake Delta Lake vs Parquet Differences and advantages ACID transactions Data versioning and time travel Databricks Optimization Techniques Partitioning Caching File compaction Query performance tuning Auto Loader Incremental data ingestion Handling streaming data Schema evolution Delta Live Tables (DLT) Data pipeline automation Data quality checks Pipeline monitoring Workflows in Databricks Job scheduling Workflow orchestration Automation of data pipelines The training includes hands-on labs, real-time scenarios, and project implementation, where learners build complete data pipelines using Azure Databricks integrated with Azure Data Lake and Azure Data Factory. I also provide: Practical assignments and coding exercises Real-time project guidance Azure Data Engineer interview preparation Best practices followed in industry projects My objective is to help learners gain strong practical expertise in Azure Databricks and PySpark, enabling them to work confidently on real-time big data and data engineering projects.