This training is a technical stream that contains six courses designed for data professionals that want to further their career in a fascinating discipline. As a Data engineer, transform the way organizations think, view, and create business value from data by :
- Applying the fundamentals of data architecture
- Transferring enterprise data to cloud hosted environments
- Mastering computer programming skills that are essential to create data engineering products
- Refining data that can be used to provide decision makers with actionable information
- Preparing data for presentation of business and analytical insights The Data Engineering Training concludes with a project where you will build a minimum viable data engineering product (MVP) that you can use in your resume or on your portfolio
This program is designed to give you the flexibility you need to balance your work-life schedule by providing you with the structure and support you need to be successful in achieving your career goals.
Are you a creative, curious, and ambitious professional looking to join the data revolution? If so—or if any of the following describes your situation—enrolling in our Cloud Data Engineer training and placement program could be a smart career move:
- You want to switch into the Information Technology field and start your career in the world of Cloud Computing.
- You are currently a professional working with data but are looking to advance your career by building technical skills and learn how to design, build, deploy, maintain and secure data processing workloads.
- You have interest in making data usable and valuable for others by collecting, transforming, and publishing data. This individual evaluates and selects products and services to meet business and regulatory requirements.
Cloud Data Warehouse Fundamentals:
- Big data overview and objectives.
- Hadoop architecture – History and evolutions.
- Data lake – How it works.
- Introduction of cloud data warehouse.
Azure Data Bricks, Spark, Pyspark:
- Introduction of Apache spark and data bricks cloud.
- Azure Data bricks Workspace creation, delta tables, spark SQL, cluster management.
- Spark data frames and tables.
- Data frame transformations and actions
- Managed vs. External Tables.
- Spark Web UI.
- Data frame transformations.
- Spark data types.
- Spark aggregations.
- Spark Joins.
- Spark data frame internals.
- Spark joins and optimizations.
- Advanced spark.
- Spark streaming.
Snowflake:
- Snowflake UI overview.
- Snowflake Internal stage.
- Snowflake External stages.
- Transaction, Commit and Rollback in Snowflake.
- Snowflake CDC.
- Snowflake ZERO copy cloning.
- Snowflake Time travel.
- Fail safe property in snowflake.
- Different types of tables in snowflake.
- Caching in Snowflake Data Warehouse.
- Snow pipe.
- Snowflake tasks.
Azure Data Factory:
- Data pipelines and Dataflow using ADF.
- Incremental and Batch Pipelines.
- Connectors: Azure services, databases, NoSQL, files, generic protocols, services & apps, custom.
- Activities: data movement, data transformation, control flow.
- Parameterization.
- Optimization
- Pipeline Monitoring Debugging and Performance.
- Integration Runtimes.
Data Modelling And Azure Synapse:
- Azure Synapse Introduction and account creation.
- Design a modern data warehouse using Azure Synapse analytics.
Cloud DevOps and CI/CD:
- Introduction to git.
- Introduction to CICD with azure data ops.
- Git integration in data factory.
- CI/CD data best practices.
- Training Program as per Latest Industry Demand
- Learn from IIBA Endorsed Education Provider
- Access to Learning Management System (LMS)
- Free PSM-I and PSPO-I training included in the package
- Certified Instructors with 20 plus years of experience
- Plenty of case studies, In-Class exercises, quizzes, and take-home assignments
- Usage of Industry-Standard tools
- Personalized Resume, LinkedIn Profile makeover and Cover Letter
- Comprehensive Capstone project
- Experiential learning through case studies
- Azure data Factory
- Azure Data bricks
- Azure Synapse
Azure Functions, Logic Apps, Azure Storage, - Key Vault
- Snowflake
- Microsoft Office (Word, Excel, PowerPoint)
- Microsoft Visio, Gliffy, Lucidchart
- Jira
- Confluence
This role requires you to have software development skills or proficiency in SQL, because you will be learning data pipelines in migration projects.
There is no prerequisite of learning any programing language. Though basic knowledge of python is good to have.
Absolutely yes. With our tailored programs along with hands on exercise and practice we can easily get into cloud data engineering
- Data bricks certified data engineer associate
- Microsoft Azure data engineer associate (DP 203)
No specific tool needs to be installed. All the tools and services are hosted in cloud and can easily be set up
Please refer course brochure
This cloud data engineering course is completely aligned with latest industry trends.
Cloud data engineering is domain independent. The training provided can be applicable across different domains like banking, healthcare, insurance, and telecom.
3.5 months.
Yes. Capstone project is selected in such a way that you will get a hands on exposure to work on different cloud module needed for data engineering .
COURSE DELIVERY OPTION
- Live Online ‘Instructor-Led’ training
- Self-Paced training
- Private Group Training
PREREQUISITES
- Basic understanding of any programming languages like Java, Python etc.
- Proficiency in Structure Query Language (SQL).
- Familiarity with database systems, both relational (e.g. PostgreSQL, MySQL) and NoSQL (e.g. MongoDB, Cassandra).
- Education in computer science, software engineering, data science, or information systems
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