New Learning | Premium Moodle Theme

MCSA: Data Engineering with Azure

Description

During this five-day course, the student will develop the skills to design and implement big data engineering workflows with the Microsoft Cloud Ecosystem and Microsoft HD Insight to extract the greatest amount of value from Data.

The MCSA: Data Engineering with Azure Certification will give validation to the skills learned in implementing big data engineering workflows with Microsoft Cloud services and Microsoft HD Insight.

This course is ideal for:

  • Data Engineer
  • Data Architect
  • Data Scientist
  • Data Developer

After completing this course, students will be able to:

  • To describe the purpose of Azure Data Factory, and explain how it works
  • To describe how to create Azure Data Factory pipelines that can transfer data efficiently
  • To describe how to perform transformations using an Azure Data Factory pipeline
  • To describe how to monitor Azure Data Factory pipeline, and how to protect the data flowing through these pipelines

20755: Perform data engineering on Microsoft HD Insight

  • Deploy HDInsight Clusters
  • Authorizing Users to Access Resources
  • Loading Data into HDInsight
  • Troubleshooting HDInsight
  • Implement Batch Solutions
  • Design Batch ETL Solutions for Big Data with Spark
  • Analyze Data with Hive and Phoenix
  • Describe Stream Analytics
  • Implement Spark Streaming Using the DStream API 
  • Develop Big Data Real-Time Processing Solutions with Apache Storm
  • Build Solutions that use Kafka and HBase

 

Perform Big Data Engineering on Microsoft Cloud Services (beta)

  • Describe common architectures for processing Big Data using Azure tools and services
  • Use Azure Stream Analytics to design and implement stream processing over large-scale data
  • How to include custom functions and incorporate machine learning activities into an Azure Stream Analytics job
  • How to use Azure Data Lake Store as a large-scale repository of data files
  • How to use Azure Data Lake Analytics to examine and process data held in Azure Data Lake Store
  • How to create and deploy custom functions and operations, integrate with Python and R, and protect and optimize jobs
  • How to use Azure SQL Data Warehouse to create a repository that can support large-scale analytical processing over data at rest
  • How to use Azure SQL Data Warehouse to perform analytical processing, how to maintain performance, and how to protect the data
  • How to use Azure Data Factory to import, transform, and transfer data between repositories and services
  • The purpose of Azure Data factory, and explain how it works
  • How to create Azure Data Factory pipelines that can transfer data efficiently
  • How to perform transformations using an Azure Data Factory pipeline
  • How to monitor Azure Data Factory pipelines and how to protect the data flowing through these pipelines

Prerequisites

It is recommended that students interested in this course have previous knowledge or experience with:

  • Azure Data Services
  • Microsoft Windows Operating system and its core functionality
  • Relational databases
  • Programming using R, and familiarity with common R packages
  • Common statistical methods and data analysis best practices

Curriculum

20775: Perform Data Engineering on Microsoft HDInsight

Module 1: Getting Started with HDInsight
Lessons

  • What is Big Data?
  • Introduction to Hadoop
  • Working with MapReduce Function
  • Introducing HDInsight

Lab: Working with HDInsight

  • Provision an HDInsight cluster and run MapReduce jobs


Module 2: Deploying HDInsight Clusters
Lessons

  • Identifying HDInsight cluster types
  • Managing HDInsight clusters by using the Azure portal
  • Managing HDInsight Clusters by using Azure PowerShell

Lab: Managing HDInsight clusters with the Azure Portal

  • Create an HDInsight cluster that uses Data Lake Store storage
  • Customize HDInsight by using script actions
  • Delete an HDInsight cluster


Module 3: Authorizing Users to Access Resources
Lessons

  • Non-domain Joined clusters
  • Configuring domain-joined HDInsight clusters
  • Manage domain-joined HDInsight clusters

Lab: Authorizing Users to Access Resources

  • Prepare the Lab Environment
  • Manage a non-domain joined cluster


Module 4: Loading data into HDInsight
Lessons

  • Storing data for HDInsight processing
  • Using data loading tools
  • Maximizing value from stored data
  • Lab: Loading Data into your Azure account
  • Load data for use with HDInsight


Module 5: Troubleshooting HDInsight
Lessons

  • Analyze HDInsight logs
  • YARN logs
  • Heap Dumps
  • Operations management suite

Lab: Troubleshooting HDInsight

  • Analyze HDInsight logs
  • Analyze YARN logs
  • Monitor resources with Operations Management Suite


Module 6: Implementing Batch Solutions
Lessons

  • Apache Hive storage
  • HDInsight data queries using Hive and Pig
  • Operationalize HDInsight

Lab: Implement Batch Solutions

  • Deploy HDInsight cluster and data storage
  • Use data transfers with HDInsight clusters
  • Query HDInsight cluster data


Module 7: Design Batch ETL solutions for big data with Spark
Lessons

  • What is Spark?
  • ETL with Spark
  • Spark performance

Lab: Design Batch ETL solutions for big data with Spark

  • Create an HDInsight Cluster with access to Data Lake Store
  • Use HDInsight Spark cluster to analyze data in Data Lake Store
  • Analyzing website logs using a custom library with Apache Spark cluster on HDInsight
  • Managing resources for Apache Spark cluster on Azure HDInsight


Module 8: Analyze Data with Spark SQL
Lessons

  • Implementing iterative and interactive queries
  • Perform exploratory data analysis

Lab: Performing exploratory data analysis by using iterative and interactive queries

  • Build a machine learning application
  • Use zeppelin for interactive data analysis
  • View and manage Spark sessions by using Livy


Module 9: Analyze Data with Hive and Phoenix
Lessons

  • Implement interactive queries for big data with an interactive hive.
  • Perform exploratory data analysis by using Hive
  • Perform interactive processing by using Apache Phoenix

Lab: Analyze data with Hive and Phoenix

  • Implement interactive queries for big data with an interactive Hive
  • Perform exploratory data analysis by using Hive
  • Perform interactive processing by using Apache Phoenix


Module 10: Stream Analytics
Lessons

  • Stream analytics
  • Process streaming data from stream analytics
  • Managing stream analytics jobs

Lab: Implement Stream Analytics

  • Process streaming data with stream analytics
  • Managing stream analytics jobs


Module 11: Implementing Streaming Solutions with Kafka and HBase
Lessons

  • Building and Deploying a Kafka Cluster
  • Publishing, Consuming, and Processing data using the Kafka Cluster
  • Using HBase to store and Query Data

Lab: Implementing Streaming Solutions with Kafka and HBase

  • Create a virtual network and gateway
  • Create a storm cluster for Kafka
  • Create a Kafka producer
  • Create a streaming processor client topology
  • Create a Power BI dashboard and streaming dataset
  • Create an HBase cluster
  • Create a streaming processor to write to HBase


Module 12: Develop big data real-time processing solutions with Apache Storm
Lessons

  • Persist long-term data
  • Stream data with Storm
  • Create Storm topologies
  • Configure Apache Storm

Lab: Developing big data real-time processing solutions with Apache Storm

  • Stream data with Storm
  • Create Storm Topologies


Module 13: Create Spark Streaming Applications
Lessons

  • Working with Spark Streaming
  • Creating Spark Structured Streaming Applications
  • Persistence and Visualization

Lab: Building a Spark Streaming Application

  • Installing Required Software
  • Building the Azure Infrastructure
  • Building a Spark Streaming Pipeline

 

20776A: Performing Big Data Engineering on Microsoft Cloud Services

Module 1: Architectures for Big Data Engineering with Azure

Lessons

  • Understanding Big Data
  • Architectures for Processing Big Data
  • Considerations for designing Big Data solutions

Lab: Designing a Big Data Architecture

  • Design big data architecture

Module 2: Processing Event Streams using Azure Stream Analytics

Lessons

  • Introduction to Azure Stream Analytics
  • Configuring Azure Stream Analytics jobs

Lab: Processing Event Streams with Azure Stream Analytics

  • Create an Azure Stream Analytics job
  • Create another Azure Stream job
  • Add an Input
  • Edit the ASA job
  • Determine the nearest Patrol Car

Module 3: Performing custom processing in Azure Stream Analytics

Lessons

  • Implementing Custom Functions
  • Incorporating Machine Learning into an Azure Stream Analytics Job

Lab: Performing Custom Processing with Azure Stream Analytics

  • Add logic to the analytics
  • Detect consistent anomalies
  • Determine consistencies using machine learning and ASA

Module 4: Managing Big Data in Azure Data Lake Store

Lessons

  • Using Azure Data Lake Store
  • Monitoring and protecting data in Azure Data Lake Store

Lab: Managing Big Data in Azure Data Lake Store

  • Update the ASA Job
  • Upload details to ADLS

Module 5: Processing Big Data using Azure Data Lake Analytics

Lessons

  • Introduction to Azure Data Lake Analytics
  • Analyzing Data with U-SQL
  • Sorting, grouping, and joining data

Lab: Processing Big Data using Azure Data Lake Analytics

  • Add functionality
  • Query against Database
  • Calculate average speed

Module 6: Implementing custom operations and monitoring performance in Azure Data Lake Analytics

Lessons

  • Incorporating custom functionality into Analytics jobs
  • Managing and Optimizing jobs

Lab: Implementing custom operations and monitoring performance in Azure Data Lake Analytics

  • Custom extractor
  • Custom processor
  • Integration with R/Python
  • Monitor and optimize a job

Module 7: Implementing Azure SQL Data Warehouse

Lessons

  • Introduction to Azure SQL Data Warehouse
  • Designing tables for efficient queries
  • Importing Data into Azure SQL Data Warehouse

Lab: Implementing Azure SQL Data Warehouse

  • Create a new data warehouse
  • Design and create tables and indexes
  • Import data into the warehouse.

Module 8: Performing Analytics with Azure SQL Data Warehouse

Lessons

  • Querying Data in Azure SQL Data Warehouse
  • Maintaining Performance
  • Protecting Data in Azure SQL Data Warehouse

Lab: Performing Analytics with Azure SQL Data Warehouse

  • Performing queries and tuning performance
  • Integrating with Power BI and Azure Machine Learning
  • Configuring security and analyzing threats

Lessons

  • Introduction to Azure Data Factory
  • Transferring Data
  • Transforming Data
  • Monitoring Performance and Protecting Data

Lab: Automating the Data Flow with Azure Data Factory

  • Automate the Data Flow with Azure Data Factory

 

What's included?
 

  • Authorized Courseware
  • Intensive Hands on Skills Development with an Experienced Subject Matter Expert
  • Hands on practice on real Servers and extended lab support 1.800.482.3172
  • Examination Vouchers  & Onsite Certification Testing- (excluding 1-day Adobe, 1-day MS Office and PMP Boot Camps) 
  • Academy Code of Honor: Test Pass Guarantee
  • Optional: Package for Hotel Accommodations, Lunch and Transportation

Training Formats

With several convenient training delivery methods offered, The Academy makes getting the training you need easy. Whether you prefer to learn in a classroom or an online live learning virtual environment, training videos hosted online, and private group classes hosted at your site. We offer expert instruction to individuals, government agencies, non-profits, and corporations. Our live classes, on-sites, and online training videos all feature certified instructors who teach a detailed curriculum and share their expertise and insights with trainees. No matter how you prefer to receive the training, you can count on The Academy for an engaging and effective learning experience.

Methods

Instructor Led (the best training format we offer)
Live Online Classroom – Online Instructor Led
Self-Paced Video

Speak to an Admissions Representative for complete details

By far the most competitve price we found, which included exam vouchers, hands on labs, practice test and a true Master of Cyber Security concepts as our Instructor. Franklin Mesa was the best trainer I have ever had and i walked out certified on the last day of my CompTIA Security+ certification bootcamp. 

Marc Alfonso - CompTIA Security + Student

 

The Academy is one of the best educational values for today's job market.  I studied hard and got certified (A+ and N+).  Even though I had no prior IT experience, I now have a good job replacing obsolete computers in hospitals throughout the country.  At my job interview, I just slid my test scores and certification across the table to the interviewer, who is now my boss.  I was hired the next day.  

Not bad for a 65 year old.

John Arnett- Student 

"I congratulate The Academy for a great facility and good lab computers. The Academy is great and I will definitely be taking more courses and utilizing the services available. Omer Palo is an excellent instructor that truly knows his material. I never felt bored in his class which is a first for me. Thank You."

IT Director, Burger King Corporation

"The instructor Frank Martinez is excellent – he covered so much material in 2 weeks that was unbelievable! He definitely knows what he does and it shows in the way that he conducts each lecture. He is the greatest!"
"Thanks Academy for allowing me to experience the MCSA / MCSE + Security Boot camp."

IT Professional, Florida International University

 

Schedules

Contact Us


THE ACADEMY

1.800.482.3172

FTL: 954.351.7040

MIA: 305.648.2000


Request More Information

 

Current Promotions!

 

  _____________________________________

 

 

 

Email Newsletter icon, E-mail Newsletter icon, Email List icon, E-mail List icon Sign up for our Email Newsletter!

          

 

Students - Orbund Log-In