Microsoft - Azure Academy: Data Deep Dive

Duration

Duration:

Only 2 Days

Method

Method:

Classroom / Online / Hybrid

Next date

Next date:

24.6.2024 (Monday)

Overview

Your accelerated 2-day Azure Academy course will deliver an Azure Data Deep Dive. You'll learn to use the Azure Analytics platform to transform your data into actionable insight. You'll also learn how to build advanced analytics and machine learning into your cloud-based big data applications.

Firebrand has worked closely with Microsoft and partners to develop this Azure Data Deep Dive course, which includes more than 80% in-depth technical content not found in Microsoft Official Curriculum.

You'll cover a range of exciting topics, as you learn how to:

  • Build and secure an Azure Data Lake Store
  • Create an Azure Machine Learning Workspace
  • Use Microsoft Azure HDInsight to process Big Data
  • Integrate Microsoft Azure HDInsight with Enterprise Data
  • Design a predictive analytics solution using Azure ML

You'll be immersed in these Azure technologies as you experience Firebrand's Lecture | Lab | Review technique, enabling you to learn faster. You'll do this by combining theory with hands-on labs, enhanced by review sessions to reinforce learning and accelerate the building of your knowledge.

This course includes practical labs designed to develop skills that you can quickly transfer into real world working scenarios.

Four reasons why you should sit your Azure Data Deep Dive course with Firebrand Training

  1. You'll be Azure Data Deep Dive trained and certified faster. Learn more on this 2-day accelerated course. You'll get at least 12 hours a day of quality learning time in a distraction-free environment
  2. Your Azure Data Deep Dive course is all-inclusive. One simple price covers all course materials, exams, accommodation and meals – so you can focus on learning
  3. Pass Azure Data Deep Dive first time or train again for free. Your expert instructor will deliver our unique accelerated learning methods, allowing you to learn faster and be in the best possible position to pass first time. In the unlikely event that you don't, it's covered by your Certification Guarantee
  4. Study Azure Data Deep Dive with an award-winning training provider. We've won the Learning and Performance Institute's "Training Company of the Year" three times. Firebrand is your fastest way to learn, with 134561 students saving more than one million hours since 2001

Benefits

Seven reasons why you should sit your course with Firebrand Training

  1. Two options of training. Choose between residential classroom-based, or online courses
  2. You'll be certified fast. With us, you’ll be trained in record time
  3. Our course is all-inclusive. A one-off fee covers all course materials, exams**, accommodation* and meals*. No hidden extras.
  4. Pass the first time or train again for free. This is our guarantee. We’re confident you’ll pass your course the first time. But if not, come back within a year and only pay for accommodation, exams and incidental costs
  5. You’ll learn more. A day with a traditional training provider generally runs from 9 am – 5 pm, with a nice long break for lunch. With Firebrand Training you’ll get at least 12 hours/day of quality learning time, with your instructor
  6. You’ll learn faster. Chances are, you’ll have a different learning style to those around you. We combine visual, auditory and tactile styles to deliver the material in a way that ensures you will learn faster and more easily
  7. You’ll be studying with the best. We’ve been named in the Training Industry’s “Top 20 IT Training Companies of the Year” every year since 2010. As well as winning many more awards, we’ve trained and certified over 135,000 professionals
  • * For residential training only. Doesn't apply for online courses
  • ** Some exceptions apply. Please refer to the Exam Track or speak with our experts

Curriculum

Module 1: Azure Data Factory

Introduction to Data Factory Concepts: In this topic you will learn what Azure Data Factory is and its key concepts.

Data Factory Operations: In this topic you will learn how to create datasets, understand data pipelines and activities to construct end-to-end data driven workflows, use the scheduling and execution aspects of Azure Data Factory application model, move data between stores.

Transform and Analyze Azure Data Factory: In this topic you will learn about data transformation activities in Azure Data Factory and how ADF transforms and processes raw data into predictions and insights using Hadoop, Azure Machine Learning, Stored Procedures, and Azure Data Lake Analytics.

Module 2: Azure Data Catalog

Introduction to Azure Data Catalog: In this topic you will learn what Azure Data Catalog is and how users can discover the data sources they need enabling Analysts, Data Scientists and Developers to discover, understand and consume data sources.

How to create an Azure Data Catalog: In this topic you will learn the how to provision and setup an Azure Data Catalog, Register Data Assets, Manage Data Assets configuring security, Annotating Data Assets and Removing Data Assets.

Discover and Manage Data Sources: In this topic you will learn how to use the Azure Data Catalog portal to discover data assets and connect to data assets using client tools such as Excel, SQL Server Data Tools and SQL Server Management Studio.

Azure Data Catalog and Big Data: In this topic you will learn how Azure Data Catalog supports the registration of Azure Blob Storage blobs and directories, and Hadoop HDFS files and directories.

Module 3: Azure Data Lake

Introduction to Data Lake Store: In this topic you will learn what Azure Data Lake Store is and its key concepts and capabilities making it easy for developers, data scientists and analysts to store data of any size, shape and speed, and do all types of processing and analytics across platforms and languages.

Create an Azure Data Lake Store: In this topic you will learn how to create an Azure Data Lake Store using the Azure Portal, PowerShell, .NET SDK, Java SDK, Visual Studio, and the Command-Line Interface (CLI), and how to enable diagnostic logs.

Data Lake Store Security: In this topic you will learn how Azure Data Lake Store provides industry-standard availability and reliability, redundant copies of data to guard against unexpected failures, Azure Active Directory for authentication and access control lists to manage access to data.

Data Lake Analytics: In this topic you will learn to write, run and manage on-demand analytics job using U-SQL Language.

Data Lake Store and Other Services: In this topic you will learn how about common use cases for Azure Data Lake Store such as Hadoop clusters, Data Lake Analytics, Stream Analytics, Data Catalog and Power BI.

Module 4: Azure HDInsight

Introduction to Big Data: In this topic you will be introduced to Big Data and some of the most common technologies that are used to build Big Data Solutions.

Microsoft Azure HDInsight: In this topic you will learn how to use Microsoft Azure HDInsight to process Big Data and consume the results in Microsoft Excel.

Managing HDInsight by using Microsoft Azure PowerShell: In this topic you will learn how to install and configure Microsoft Azure PowerShell, Manage files in HDFS and use PowerShell to run MapReduce jobs.

Processing Big Data by using Pig: In this topic you will learn how to process data by using Pig and run Pig jobs in Windows PowerShell.

Processing Big Data by using Hive: In this topic you will learn how to create Hive tables, load data into Hive tables, Query Hive tables, run Hive jobs in PowerShell, and use the Hive Open Database Connectivity (ODBC) Driver to query Hive table from Microsoft Excel.

Automating Big Data Processing Tasks: In this topic you will learn techniques for creating and automating robust Big Data processing solutions by using Microsoft Azure HDInsight.

Integrating Microsoft Azure HDInsight with Enterprise Data: In this topic you will learn various options for integrating Microsoft Azure HDInsight into an enterprise BI infrastructure for reporting and analysis

Module 5: Azure Machine Learning.

Introduction to Machine Learning and Azure ML Studio: In this topic you will learn about Azure Machine Learning and its strengths, an exploring the Azure Machine Learning Studio.

Create an Azure Machine Learning Workspace: In this topic you will learn how to use Storage Accounts and create an Azure Machine Learning Workspace.

Designing a Predictive Analytics Solution with Azure ML: In this topic you will learn how to define the problem you want to solve, create an experiment adding transformation and filters, save and run the model, publish and use the model.

Module 6: Power BI

Introduction to Power BI Desktop and Power BI Cloud Service

Learn how to create a Power BI report and publish it to Power BI cloud service.

What's Included

The following is included on your accelerated Azure Data Deep Dive course:

  • Firebrand Course Material

Your accelerated course includes:

  • Accommodation *
  • Meals, unlimited snacks, beverages, tea and coffee *
  • On-site exams **
  • Exam vouchers **
  • Practice tests **
  • Certification Guarantee ***
  • Courseware
  • Up-to 12 hours of instructor-led training each day
  • 24-hour lab access
  • Digital courseware **
  • * For residential training only. Accommodation is included from the night before the course starts. This doesn't apply for online courses.
  • ** Some exceptions apply. Please refer to the Exam Track or speak with our experts
  • *** Pass first time or train again free as many times as it takes, unlimited for 1 year. Just pay for accommodation, exams, and incidental costs.

Prerequisites

The Azure Data Deep Dive is an advance coursed. You are recommended to have achieved the following three Microsoft Specialist certifications, or have equivalent knowledge:

  • Specialist: Developing Microsoft Azure Solutions
  • Specialist: Implementing Microsoft Azure Infrastructure Solutions
  • Specialist: Architecting Microsoft Azure Solutions

If you don't possess the above certifications, the equivalent skills and knowledge requirements are below. You must be able to:

  • Design and implement Web Apps
  • Create and manage virtual machines and virtual networks
  • Design and implement cloud services
  • Design and implement a storage strategy
  • Manage application and network services
  • Design Microsoft Azure Infrastructure and networking
  • How to secure resources
  • Design an application storage and data access strategy
  • Design an advanced application
  • Design a management, monitoring and business continuity strategy

Unsure whether you meet the prerequisites? Don’t worry. Your training consultant will discuss your background with you to understand if this course is right for you.

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