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Microsoft Azure Data Factory
Overview
About Course
Microsoft Azure DP-200 certification training gives learners the opportunity to get used to implementing Azure Data Solution. This training ensures that learners improve their skills on Microsoft Azure SQL Data Warehouse, Azure Data Lake Analytics, Azure Data Factory, and Azure Stream Analytics
Duration: 30 days
- Week day Batches: ( Mon to fri, Sat & Sun 9am to 2pm )
- Weekend Batches: Sat & Sun ( 9am to 2pm)
- For fee and job assistance please call us on : 02033710546 or 07843259631 Email us : training@Lsatraining.co.uk
12 months interest free loan
- Course Description
- Course Content
- Labs
- Highlights
Audience Profile :
Candidates for this exam should have subject matter expertise integrating, transforming, and consolidating data from various structured and unstructured data systems into a structure that is suitable for building analytics solutions. Azure Data Engineers help stakeholders understand the data through exploration, and they build and maintain secure and compliant data processing pipelines by using different tools and techniques. These professionals use various Azure data services and languages to store and produce cleansed and enhanced datasets for analysis. Azure Data Engineers also help ensure that data pipelines and data stores are high-performing, efficient, organized, and reliable, given a set of business requirements and constraints. They deal with unanticipated issues swiftly, and they minimize data loss. They also design, implement, monitor, and optimize data platforms to meet the data pipelines needs. A candidate for this exam must have strong knowledge of data processing languages such as SQL, Python, or Scala, and they need to understand parallel processing and data architecture patterns.
- Lesson 01 – Introduction to Azure Synapse Analytics
- Lesson 02 – Describe Azure Databricks
- Lesson 03 – Introduction to Azure Data Lake storage
- Lesson 04 – Describe Delta Lake architecture
- Lesson 05 – Work with data streams by using Azure Stream Analytics
- Lesson 01 – Explore Azure Synapse serverless SQL pools capabilities
- Lesson 02 – Query data in the lake using Azure Synapse serverless SQL pools
- Lesson 03 – Create metadata objects in Azure Synapse serverless SQL pools
- Lesson 04 – Secure data and manage users in Azure Synapse serverless SQL pools
- Lesson 01 – Describe Azure Databricks
- Lesson 02 – Read and write data in Azure Databricks
- Lesson 03 – Work with Data Frames in Azure Databricks
- Lesson 04 – Work with Data Frames advanced methods in Azure Databricks
- Lesson 01 – Understand big data engineering with Apache Spark in Azure Synapse Analytics
- Lesson 02 – Ingest data with Apache Spark notebooks in Azure Synapse Analytics
- Lesson 03 – Transform data with Data Frames in Apache Spark Pools in Azure Synapse Analytics
- Lesson 04 – Integrate SQL and Apache Spark pools in Azure Synapse Analytics
- Lesson 01 – Use data loading best practices in Azure Synapse Analytics
- Lesson 02 – Petabyte-scale ingestion with Azure Data Factory or Azure Synapse Pipelines
- Lesson 01 – Data integration with Azure Data Factory or Azure Synapse Pipelines
- Lesson 02 – Code-free transformation at scale with Azure Data Factory or Azure Synapse Pipelines
Lesson 01 – Orchestrate data movement and transformation in Azure Data Factory or Azure Synapse Pipelines
- Lesson 01 – Secure a data warehouse in Azure Synapse Analytics
- Lesson 02 – Configure and manage secrets in Azure Key Vault
- Lesson 03 – Implement compliance controls for sensitive data
- Lesson 01 – Design hybrid transactional and analytical processing using Azure Synapse Analytics
- Lesson 02 – Configure Azure Synapse Link with Azure Cosmos DB
- Lesson 03 – Query Azure Cosmos DB with Apache Spark for Azure Synapse Analytics
- Lesson 04 – Query Azure Cosmos DB with SQL serverless for Azure Synapse Analytics
- Lesson 01 – Enable reliable messaging for Big Data applications using Azure Event Hubs
- Lesson 02 – Work with data streams by using Azure Stream Analytics
- Lesson 03 – Ingest data streams with Azure Stream Analytics
Lesson 01 – Process streaming data with Azure Databricks structured streaming
- Explore Azure Synapse Analytics
- Analyze data-with-sql
- Transform-data-with-sql
- Create and Analyze data in a lake database
- Analyze data in a data lake with Spark
- Transform data using Spark in Synapse Analytics
- Use Delta Lake with Spark in Azure Synapse Analytics
- Explore a relational data warehouse
- Load Data into a Relational Data Warehouse
- Build a data pipeline in Azure Synapse Analytics
- Use an Apache Spark notebook in a pipeline
- Use Azure Synapse Link for Azure Cosmos DB
- Use Azure Synapse Link for SQL
- Get started with Azure Stream Analytics
- Ingest realtime data with Azure Stream Analytics and Azure Synapse Analytics
- Create a realtime report with Azure Stream Analytics and Microsoft Power BI
- Use Microsoft Purview with Azure Synapse Analytics
- Explore Azure Databricks
- Use Spark in Azure Databricks
- Use Delta Lake in Azure Databricks
- Use a SQL Warehouse in Azure Databricks
- Automate an Azure Databricks Notebook with Azure Data Factory
Training Highlights
- More interaction with student to faculty and student to student.
- Detailed presentations. Soft copy of Material to refer any time.
- Practical oriented / Job oriented Training. Practice on Software Tools & Real Time project scenarios.
- Mock interviews / group discussions / interview related questions.
- Test Lab is in Cloud Technology – to practice on software tools if needed.
- We discuss about the real time project domains.
- The teaching methods / tools / topics we chosen are based on the current competitive job market.
Also on this course we offer the following
- Hands on Experience
- Real Time project work
- Interview based Training
Expected Salary/ Pay Package
- Expected Salaries are as follows:
- For Contractors £400 to £800 per day
- Permanent Positions £50 to £100k per annum all depends on experience and skills set
Curriculum
Instructor
