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Ekascloud

Azure Data Analytics

  • 24/7 Support
  • 3 Months
  • 100 Sessions

Course Description

Data Engineering on Azure introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Azure Databricks, Data Factory in Azure. This course demonstrates how to collect, store, and prepare data for the data analytics by using other Azure services such as Azure CosmosDB, Azure Stream Analytics, Azure Synapse Analytics, and Azure Blob Storage. Additionally, this course demonstrates how to use business intelligence tools to perform analysis on your data. 

This course will be delivered through a mix of Instructor-led Training (ILT) and hands-on Labs. This course allows you to test new skills and apply knowledge to your working environment through a variety of practical exercises.

One to One personalized training Schedule for Azure Data Analytics

EkasCloud provides flexible training to all it's student. Here is our training schedule. Incase you find these timings difficult, please let us know. We will try to arrange appropriate timings based on your Convenience.

12-10-2024 Saturday (Monday - Friday) Weekdays Regular 08:00 AM (IST) (Class 1Hr - 1:30Hrs) / Per Session
14-10-2024 Monday (Monday - Friday) Weekdays Regular 08:00 AM (IST) (Class 1Hr - 1:30Hrs) / Per Session
16-10-2024 Wednesday (Monday - Friday) Weekdays Regular 08:00 AM (IST) (Class 1Hr - 1:30Hrs) / Per Session
17-10-2024 Thursday (Monday - Friday) Weekdays Regular 08:00 AM (IST) (Class 1Hr - 1:30Hrs) / Per Session

Course Detail

Data Engineering on Azure introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Azure Databricks, Data Factory in Azure. This course demonstrates how to collect, store, and prepare data for the data analytics by using other Azure services such as Azure CosmosDB, Azure Stream Analytics, Azure Synapse Analytics, and Azure Blob Storage. Additionally, this course demonstrates how to use business intelligence tools to perform analysis on your data. 

This course will be delivered through a mix of Instructor-led Training (ILT) and hands-on Labs. This course allows you to test new skills and apply knowledge to your working environment through a variety of practical exercises.

Choosing the Azure Data Analytics training is an assurance to stand among the handpicked and best set of professionals in the domain. 

WHO CAN JOIN

Azure Data Analytics is sure to benefit a diversified range of patrons whether a Software Engineer, Project Manager, System Administrator, Developer, Database Admin, data warehouse technician, IoT developer, Azure Data Analytics, and AI Developer or computer science student.

This Azure Data Analytics course is thoughtfully designed to allow learners with and without a programming background to transition into the Big Data industry with the correct skill-set.

  • We recommend this course to the following:
  • Software professionals who aspire to explore a career in Azure Data Analytics.
  • IT professionals who are passionate about Azure Data Analytics.
  • professionals who are desirous of exploring the power of Azure Data Analytics.
  • Anyone who has an innate desire to study and learn Azure Data Analytics.
  • Experienced professionals that wish to shift to Azure Data Analytics as their career.

BENEFITS

  • Validate your skills and knowledge in the Azure Data Analytics field.
  • You are consistently listed among the top-paying info-tech skill worldwide.
  • Demonstrate credibility and dedication to your Azure Data Analytics career path.
  • Provide access to a network of like-minded peers and Azure Data Analytics thought-leaders.

BEST FOR YOU

  • The course deals with all Azure Data Analytics concepts
  • Very detailed and industry-standard scenario-based hands-on practice for all topics.
  • Live project-based hands-on sessions
  • Many bonus segments to cover more than the certification syllabus of Databricks 
  • Detailed soft study materials
  • Certification exam preparation with mock exams.
  • Helpful tips exam tips in every class session.

  • We check your knowledge before we start the session.
  • We build foundational topics first and core topics next.
  • Theory classes with real time case study.
  • Demo on every topic.
  • You will learn how to design architecture diagrams on real life problems.
  • Mock exam on every topic you learn.
  • Exam preparation
  • Interview preparation

Azure Data Analytics Syllabus

View Syllabus

3 months Course includes Theory, Lab, Daily Homework, Real-time Projects, Mock Exams and Mock Interview

Topics Covered

  • Types of Data, Data operations, Common Scripting languages in practice
  • Operational and Analytical Data, Data Pipelines, Data Lakes, Data Warehouses, Apache Spark
  • Azure technologies used to implement data engineering workloads
  • Understanding Azure Synapse serverless SQL pool capabilities and use cases
  • Using a CREATE EXTERNAL TABLE AS SELECT (CETAS) statement to transform data.
  • Encapsulating a CETAS statement in a stored procedure.
  • Analytical data workloads in Microsoft Azure
  • Querying data with Transact-SQL
  • Get to know Apache Spark
  • Use Spark in Azure Synapse Analytics
  • Analyze data with Spark
  • Use Apache Spark to modify and save dataframes
  • Partition data files for improved performance and scalability.
  • Transform data with SQL
  • Describe core features and capabilities of Delta Lake.
  • Create and use Delta Lake tables in a Synapse Analytics Spark pool.
  • Create Spark catalog tables for Delta Lake data.
  • Use Delta Lake tables for streaming data.
  • Query Delta Lake tables from a Synapse Analytics SQL pool.
  • Design a data warehouse schema
  • Create, load, and query data warehouse tables
  • Load Staging and Dimension tables
  • Perform post-load optimizations in a data warehouse
  • Understand network security options for Azure Synapse Analytics
  • Manage sensitive data with Dynamic Data Masking
  • Implement encryption in Azure Synapse Analytics
  • Understand pipelines in Azure Synapse Analytics
  • Create and running a pipeline in Azure Synapse Studio
  • Describe notebook and pipeline integration.
  • Use a Synapse notebook activity in a pipeline.
  • Use parameters with a notebook activity
  • Describe Hybrid Transactional / Analytical Processing patterns.
  • Identify Azure Synapse Link services for HTAP.
  • Configure an Azure Cosmos DB Account to use Azure Synapse Link.
  • Create an analytical store enabled container.
  • Create a linked service for Azure Cosmos DB.
  • Analyze linked data using Spark.
  • Analyze linked data using Synapse SQL.
  • Configure an Azure Cosmos DB Account to use Azure Synapse Link.
  • Create an analytical store enabled container.
  • Create a linked service for Azure Cosmos DB.
  • Analyze linked data using Spark.
  • Analyze linked data using Synapse SQL
  • Understand data streams, event processing, windows functions
  • Describe common stream ingestion scenarios for Azure Synapse Analytics.
  • Configure inputs and outputs for an Azure Stream Analytics job.
  • Define a query to ingest real-time data into Azure Synapse Analytics.
  • Run a job to ingest real-time data, and consume that data in Azure Synapse Analytics.
  • Configure a Stream Analytics output for Power BI.
  • Use a Stream Analytics query to write data to Power BI.
  • Create a real-time data visualization in Power BI.
  • What is Microsoft Purview, how it works, and when to use it?
  • Browse, search, and manage data catalog assets.
  • Use data catalog assets with Power BI.
  • Use Microsoft Purview in Azure Synapse Studio.
  • Browse, search, and manage data catalog assets.
  • Use data catalog assets with Power BI.
  • Use Microsoft Purview in Azure Synapse Studio.
  • Browse, search, and manage data catalog assets.
  • Use data catalog assets with Power BI.
  • Use Microsoft Purview in Azure Synapse Studio.
  • Provision an Azure Databricks workspace.
  • Identify core workloads and personas for Azure Databricks.
  • escribe key concepts of an Azure Databricks solution.
  • Describe key elements of the Apache Spark architecture.
  • Create and configure a Spark cluster.
  • Describe use cases for Spark.
  • Use Spark to process and analyze data stored in files.
  • Use Spark to visualize data.
  • Describe how Azure Databricks notebooks can be run in a pipeline.
  • Create an Azure Data Factory linked service for Azure Databricks.
  • Use a Notebook activity in a pipeline.
  • Pass parameters to a notebook.
     

Instructor

Vijilin Jerrish

jerrish has a Bachelors degree in Computer Science, He is based out of India and had trained more than 8000 students in last 9years on Networking, Linux, Automation and Cloud Technologies.

Jerrish is RHCSA, Ansible, AWS Solutions Architect Pro, Terraform and Kubernetes Certified

Frequently asked question

Q:  What if I miss a class?

A:  We will stop the course for you because it is one-to-one or one-to-two students only.

Q: What if I am not an Engineer/Programmer, can I still do the Azure Data Analytics course?

A: Azure Data Analytics is not a separate domain, but a tool/technology which can be used in any domain. Our course is designed to address the needs of non-programmers and candidates who have no IT knowledge as well. Anyone who has an interest in Azure Data Analytics can take up this course.

Q: Will I get placement assistance?

A: Yes.  you will get it, once you finish the course.

Q: What if I have queries after I complete this course?

A: You can check our blog, or send your queries from social media like Facebook, Linkedin, Instagram, Twitter, and Youtube.

Q: How soon after signing up will I get access to the course?

A: Once you join the course, our Counselor Manager book a slot with our Trainer based on your and Trainer's available time.

Q: Is the course material accessible to the students even after the course training is over?

A: Yes, you can access our course material. Not only material you can watch short and sweet videos from our Youtube Channel.

Q: What is the average salary of an Azure Data Analytics professional?

A: $429,868

Admission Process

If a student want to take admission in any course he has to go with the following steps

Step 1
1 Hour Interview
  • Discuss Learning Goals: Understand the candidate’s career objectives, learning expectations, and prior experience (if any).
  • Personalized Course Recommendation: Based on the discussion, recommend the most suitable course.
  • Course Customization: Tailor the course plan to fit the candidate’s needs, including scheduling flexibility.
Step 2
3 Hour Assessment Session
  • Technical Skills Evaluation: Hands-on tasks or exercises to evaluate the candidate’s current technical understanding (for advanced courses).
  • Cloud Fundamentals Check: For entry-level courses, a basic assessment of cloud knowledge and IT skills.
  • Feedback & Results: Provide instant feedback and suggest an appropriate course path based on assessment performance.
Step 3
Final Enrollment

Upon successful completion of the assessment, candidates receive a customized learning path, course schedule, and payment options. Candidates can finalize their enrollment by agreeing to the course structure and payment plan.

Azure Data Analytics Fees
£ 2100
Enroll Now