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Data Professional
Skill Me Up expert on-demand training for Security Professional. Modernize your skills with cloud computing from providers such as Microsoft Azure, Amazon Web Services and much more along with core foundational IT training.
8 Results
Learning Path
4 (49)
4 Lectures
3 Labs
7h 44m
Beginner

In this learning path, you will find courses and hands-on labs that will help you prepare you to pass exam AZ-900 Microsoft Azure Fundamentals.

Learning Path
4 (4)
1 Lectures
1 Labs
5h 3m
Intermediate

In this learning path, you will learn how to use services such as Power BI and Spark to surface, process and analyze data to generate intelligence to make more well informed business decisions.

Learning Path
4 (37)
3 Lectures
7 Labs
15h 6m
Advanced

In this learning path, you will learn how to implement Azure Database. Topics will include understanding to design and deploy databases using SQL DB and SQL Datawarehouse along with more advanced topics of performance and troubleshooting for SQL.

Learning Path
4 (46)
5 Lectures
5 Labs
17h 22m
Intermediate

In this learning path, you will learn how to build and architect big data solutions in Microsoft Azure. Topics will include architecting solutions using HD Insight, machine learning, visualizing data with Power BI, understanding lambda architecture patterns and IoT data ingestion. This path will help you prepare for exam Designing and Implementing Big Data Platform Solutions - exam 70-475 and will help you prepare for your MIcrosoft certification.

Learning Path
4 (73)
4 Lectures
6 Labs
19h 49m
Advanced

In this learning path, you will learn how to build and architect SQL focused solutions in Microsoft Azure. Topics will include SQL Server in Azure IaaS, SQL Database and SQL Data warehouse. This course will help you prepare for exam 70-473 Implementing Cloud Data Platform Solutions and prepare for your Microsoft certification.

Learning Path
5 (19)
1 Lectures
9 Labs
1 day, 1h 2m
Intermediate

In this learning path you will find courses and Real Time Labs to help you learn Microsoft Azure Cosmos DB.

Learning Path
5 (6)
1 Lectures
6 Labs
8h 49m
Advanced

In this learning path, you will learn the fundamentals of Azure DataBricks and as new courses are added to the path you will progressively learn more advanced topics.

Learning Path
4 (18)
3 Lectures
5 Labs
11h 6m
Intermediate

This path contains courses and labs designed to help you learn about performing data science using services in Microsoft Azure such as Azure ML.

41 Results
Lecture
3 (11)
Feb 15 2018
Beginner
1h 39m
Peter De Tender

In this module, attendees will learn how to design solutions using Azure Infrastructure as a Service Components. This module will focus on core capabilities, use cases, and general best practices as well as discuss peripheral services such as Azure Backup and Site Recovery.

Lecture
3 (8)
Mar 6 2017
Intermediate
2h 48m
Jen Stirrup

This course gives you an introduction to Azure Machine Learning (ML) and associated technologies, such as R, Power BI and RStudio. This course begins by covering an introduction to Azure ML, and then we walk through Azure ML as if we were working our way through a Data Science Project. Once the Data Science project is complete, we will look at how you can set up and report on the Azure ML modelling process with Power BI.

Lecture
5 (3)
Sep 15 2017
Advanced
4h 42m
Paul Burpo

This course will be a deep dive into Azure SQL Database performance. We will look at designing an Azure SQL Database architecture for performance. We will look at performance specific features of Azure SQL Database. We will also cover monitoring and troubleshooting.

Lecture
5 (10)
Apr 17 2017
Intermediate
2h 2m
Paul Burpo

This module will cover all aspects of big data storage and batch processing. We will start by making the case for big data in Azure. Then we will look at Azure service topics to include Blob Storage, Azure Data Lake Store, Azure Data Lake Analytics, and HDInsight clusters running Hadoop, Hive, Interactive Hive (LLAP) and Spark. Storage topics will focus on choosing the right storage, configuring storage and storage optimization. We will also cover Big Data scenarios including batch processing, interactive clusters, multi-cluster deployments and on-demand clusters.

Lecture
Jul 27 2018
Intermediate
Opsgility

In this course, you will explore the Spark Internals and Architecture of Azure Databricks. The course will start with a brief introduction to Scala. Using the Scala programming language, you will be introduced to the core functionalities and use cases of Azure Databricks including Spark SQL, Spark Streaming, MLlib, and GraphFrames.

Lecture
Jan 1 2017
Intermediate
Opsgility

The Architecting Azure Big Data and Analytics course is designed to give students a clear architectural understanding of the application of big data patterns in Azure. Students will participate in team based architectural planning and hands-on implementation sessions. Students will be taught basic Lambda architecture patterns in Azure, leveraging the scalability and elasticity of Azure in Big Data and IoT solutions as well as an introduction to cognitive services, machine learning, and artificial intelligence (AI).An introduction to data science techniques in Azure will also be covered. Individual case studies will focus on specific real-world problems that represent common big data patterns and practices. Students will also experience several hands-on labs to introduce them to some of the key services available.

Lecture
Aug 7 2017
Intermediate
Opsgility

The Azure Big Data and Analytics Boot camp is designed to give students a clear architectural understanding of the application of big data patterns in Azure. Students will participate in team based architectural planning and hands-on implementation sessions. Students will be taught basic Lambda architecture patterns in Azure, leveraging the scalability and elasticity of Azure in Big Data and IoT solutions.An introduction to data science techniques in Azure will also be covered. Individual case studies will focus on specific real-world problems that represent common big data patterns and practices. Students will also experience several hands-on labs to introduce them to some of the key services available.

Lecture
Apr 20 2018
Intermediate
Opsgility

This course explores Microsoft Azure’s AzureML service offering for students that are either new to machine learning or new to Azure. The course starts with an introduction to various aspects of building experiments in AzureML and using MLStudio to create cohesive machine learning workflows.Each topic looks at different aspects of AzureML as well as introduces different concepts in machine learning such as regression, clustering and classification and when to use each. The course moves onto more advanced topics such as how the R language can be used to enrich AzureML as well as being able to define neural networks and lastly how to integrate into more complex data orchestrations involving other services in Azure.Learning format:• 40% presentation• 40% hands-on labs• 20% whiteboard design

Lecture
Sep 15 2017
Advanced
Opsgility

This course covers all aspects of Azure SQL Database performance. This course will cover the performance monitoring and troubleshooting tools available in Azure SQL Database. We will cover designing performant databases in Azure SQL Database, leveraging in-memory and columnstore technologies. Finally, we will wrap up by discussing elastic database pools and the special challenges they bring to monitoring and tuning performance

Lecture
Apr 20 2018
Intermediate
Opsgility

The Azure Big Data and Machine Learning Bootcamp is designed to give students a clear architectural understanding of the application of big data patterns in Azure. Students will participate in team based architectural planning and hands-on implementation sessions. Students will be taught basic Lambda architecture patterns in Azure, leveraging the scalability and elasticity of Azure in Big Data and IoT solutions.An introduction to data science techniques in Azure will also be covered. Individual case studies will focus on specific real-world problems that represent common big data patterns and practices. Students will also experience several hands-on labs to introduce them to some of the key services available.Format:Instructor-led with hands-on labs and whiteboard design sessions

Lecture
Jan 14 2018
Advanced
Opsgility

A cloud workshop is a 1-day event that consists of an overview of the technology, a deep dive whiteboard design session and Hands-on lab where participants will a subset of the solution.In this Workshopyou willlearn how to upgrade from Oracle Databases and earlier SQL Server Databases to SQL Server 2016 and Azure SQL DB. SQL Server 2016 on Windows Server 2016 (and now also available on Linux) will offer higher availability, greater performance and faster analytics. SQL Server 2016 and Azure DB supports virtually any data, of any size, with any application on any platform. SQL Server 2016 also boasts the fastest In-Memory technology on the planet across workloads helping customers to take performance and throughput to another level. It is also possible to build a hybrid data platform with frequently accessed data in SQL Server 2016 and less frequently accessed data in Azure’s SQL Database. Attend this workshop to upgrade to these latest versions to take advantage of these benefits to increase protection from security vulnerabilities. This workshop includes: Whiteboard design session and Hands-on lab

Lecture
Jan 14 2018
Advanced
Opsgility

A cloud workshop is a 1-day event that consists of an overview of the technology, a deep dive whiteboard design session and Hands-on lab where participants will a subset of the solution.In this workshop, attendees will learn real-time analytics without IoT. Enable intelligent conversation in a machine learning-enabled, real-time chat pipeline and apply analytics to visualize customer sentiment in real-time for hospitals to allow guests to chat with one another, and to communicate directly with the concierge. This workshop includes: Whiteboard design session and Hands-on lab

Lecture
Jan 14 2018
Advanced
Opsgility

A cloud workshop is a 1-day event that consists of an overview of the technology, a deep dive whiteboard design session and Hands-on lab where participants will a subset of the solution.In this workshop, attendees will implement an IoT solution for intelligent vending machines leveraging Facial feature recognition and Machine learning to drive on-demand pricing, enable real-time analytics, and cloud to device messaging flows. Learn how to create Machine Learning models in R, train the models at scale using R and Spark on HDInsight, then expose the model as a web service through R Server Operationalization. You will use IoT Hub to facilitate vending machine device registration and communication for product promotions, and enable real-time analytics with SQL Database in-memory and columnar indexing. This workshop includes: Whiteboard design session and Hands-on lab

Lecture
Jan 14 2018
Advanced
Opsgility

A cloud workshop is a 1-day event that consists of an overview of the technology, a deep dive whiteboard design session and Hands-on lab where participants will a subset of the solution.In this workshop, attendees will migrate a retail chain to from an existing data warehouse from an on-premises SQL Server into Azure SQL Data Warehouse. Prepare a detailed migration plan including data preparation, importing data into Azure SQL Data Warehouse, and architecting a data orchestration strategy to move data from the existing on-premises source systems to Azure SQL Data Warehouse. This workshop includes: Whiteboard design session and Hands-on lab

Lecture
Jan 14 2018
Advanced
Opsgility

A cloud workshop is a 1-day event that consists of an overview of the technology, a deep dive whiteboard design session and Hands-on lab where participants will a subset of the solution.In this workshop, students will work with a media publishing company to design a hybrid cloud disaster recovery solution. Students will design the solution to handle large spikes in load and harden the security to include encryption of PCI data. Additionally students will implement an archival strategy to keep databases sizes in check. This workshop will include: Whiteboard design session.

Lecture
Jan 1 2017
Intermediate
Opsgility

In this hands-on course, students will learn about running SQL Server in Azure. This course will review basic Azure networking and storage using the Azure Resource Manager architecture to prepare students for building SQL Server solutions in Azure. The primary focus of this course is SQL Server cloud and hybrid-cloud solutions on both Azure Platform as a Service (PaaS) and Azure Infrastructure as a Service (IaaS). This course will cover best practices for deploying SQL Server on Azure Virtual Machines including standalone SQL Servers and hybrid Availability Groups. The course will look at SQL Server features that take advantage of Azure Storage such as SQL Server Managed Backup, Azure Snapshot Backups, and SQL Server data files hosted on Azure Storage. Finally this course will provide you with an introduction to Azure SQL Database and archiving cold data with SQL Server Stretch Database.

NEW
Lecture
Apr 23 2019
Beginner
Opsgility

In this course student will learn how to define and prepare the development environment, prepare data for modeling, perform feature engineering and develop models.Azure Data Scientists apply Azure’s machine learning techniques to train, evaluate, and deploy models that solve business problems.This course will prepare you for DP-100: Designing and Implementing a Data Science Solution on Azure exam.

Lecture
Apr 4 2019
Intermediate
Opsgility

In this course, the students will implement various data platform technologies into solutions that are in line with business and technical requirements including on-premises, cloud, and hybrid data scenarios incorporating both relational and No-SQL data. They will also learn how to process data using a range of technologies and languages for both streaming and batch data.The students will also explore how to implement data security including authentication, authorization, data policies and standards. They will also define and implement data solution monitoring for both the data storage and data processing activities. Finally, they will manage and troubleshoot Azure data solutions which includes the optimization and disaster recovery of big data, batch processing and streaming data solutions.

Lecture
Apr 4 2019
Intermediate
Opsgility

In this course, the students will design various data platform technologies into solutions that are in line with business and technical requirements. This can include on-premises, cloud, and hybrid data scenarios which incorporate relational, No-SQL or Data Warehouse data. They will also learn how to design process architectures using a range of technologies for both streaming and batch data.The students will also explore how to design data security including data access, data policies and standards. They will also design Azure data solutions which includes the optimization, availability and disaster recovery of big data, batch processing and streaming data solutions.

Lecture
Apr 12 2018
Intermediate
Opsgility

This course introduces you to Microsoft Cognitive Services and takes you through a gradual journey of features through search, audio, computer vision and language processing services. Along with it’s capabilities, this course explains how to get started developing applications that take advantage of Microsoft Azure Cognitive Service offerings. Once you have clear understanding of all the offerings you can make better decisions on when and how to incorporate Cognitive Services into Enterprise server, desktop, mobile, web, IoT and extended reality (xR/VR/AR/MR) applications.This course will introduce you how to all offerings of Azure Cognitive Services in many different environments, server, web, UWP Store and xR applications.Overview of all Microsoft Azure Cognitive ServicesHow the industry is taking advantage of Azure Cognitive ServicesWhat are the Search Based ServicesHow to invoke Search Based ServicesWhat are the Audio Based ServicesWhat are the Computer Vision/Image based servicesHow to invoke the Computer Vision and Image based servicesWhat are the Text/Language based servicesWhat are the Generic Machine learning based services

Lecture
Apr 13 2017
Intermediate
Opsgility

In this hands-on course, students will learn about running SQL Server in Azure. This course will review basic Azure networking and storage using the Azure Resource Manager architecture to prepare students for building SQL Server solutions in Azure. The primary focus of this course is SQL Server cloud and hybrid-cloud solutions on both Azure Platform as a Service (PaaS) and Azure Infrastructure as a Service (IaaS). This course will cover best practices for deploying SQL Server on Azure Virtual Machines including standalone SQL Servers and hybrid Availability Groups. The course will look at SQL Server features that take advantage of Azure Storage such as SQL Server Managed Backup, Azure Snapshot Backups, and SQL Server data files hosted on Azure Storage. Finally, this course will provide you with an introduction to Azure SQL Database and archiving cold data with SQL Server Stretch Database. This course can help prepare you for the exam: 70-473 Designing and Implementing Cloud Data Platform Solutions.

Lecture
Aug 8 2018
Intermediate
Opsgility

The main purpose of the course is to give students the ability to use Microsoft R Server to create and run an analysis on a large dataset, and show how to utilize it in Big Data environments, such as a Hadoop or Spark cluster, or a SQL Server database.

Lecture
Jan 12 2018
Intermediate
Opsgility

The main purpose of the course is to give students the ability to analyze and present data by using Azure Machine Learning, and to provide an introduction to the use of machine learning with big data tools such as HDInsight and R Services.

Lecture
Jan 12 2018
Intermediate
Opsgility

The main purpose of the course is to give students the ability plan and implement big data workflows on HDInsight.

Lecture
Jan 12 2018
Intermediate
Opsgility

This five-day instructor-led course describes how to process Big Data using Azure tools and services including Azure Stream Analytics, Azure Data Lake, Azure SQL Data Warehouse and Azure Data Factory. The course also explains how to include custom functions, and integrate Python and R.

Lecture
Oct 24 2018
Intermediate
Opsgility

This three-day instructor-led course is aimed at database professionals who are looking to implement a Cosmos DB solution.

Lecture
Aug 30 2017
Intermediate
Opsgility

The main purpose of the course is to give students a good understanding of data analysis with Power BI. The course includes creating visualizations, the Power BI Service, and the Power BI Mobile App.Audience profileThe course will likely be attended by SQL Server report creators who are interested in alternative methods of presenting data. At course completion

Lecture
Oct 13 2017
Intermediate
Opsgility

The focus of this three-day instructor-led Microsoft Training course is on designing and implementing cloud data platform solutions with the Microsoft Data Platform by using SQL Server on-premises, hybrid and cloud data platform solutions. It describes how to design and implement and optimize workloads in hybrid scenarios with both on-premises and Microsoft Azure cloud-based solutions, and how to implement high availability and disaster recovery solutions.

Lecture
Oct 16 2017
Beginner
Opsgility

55224A-1 is a two-day instructor-led course is intended for data professionals who want to expand their knowledge about creating big data analytic solutions on Microsoft Azure. Students will learn how to design solutions for batch and real-time data processing. Different methods of using Azure will be discussed and practiced in lab exercises, such Azure CLI, Azure PowerShell and Azure Portal. 55224A-1 labs and exercises cover the first two objectives of exam 70-475 (Designing Big Data batch, interactive real-time solutions). The other two objectives (Designing Machine Learning and cloud analytics solutions) are covered in 55224A-2.

Lecture
Mar 22 2018
Intermediate
Opsgility

This course builds on your Power BI skills and walks you through the interfaces of both the Online and Desktop offerings before embarking on a journey that will show you how to ingest data, transform data, create reports and dashboards before publishing and using your data sets, reports and dashboards in the Power BI online tenant.The course will prepare students to take the Microsoft 70-778, Analyzing and Visualizing Data with Power BI certification exam.

Lecture
5 (9)
Sep 21 2017
Beginner
57m
Chris Pietschmann

This course explores the NoSQL storage options available within the Microsoft Azure Cosmos DB database service. Formerly DocumentDB, Azure Cosmos DB is no longer just a Document-based NoSQL store, and it includes support for all 4 primary NoSQL data models (Document, Graph, Key/Value, Column). In addition to learning about NoSQL with Cosmos DB, students will also learn about the cloud-native features that make Cosmos DB a great NoSQL database-as-a-service in the Microsoft Azure cloud.

Lecture
5 (7)
Aug 24 2016
Beginner
23m
Paul Burpo

In this hands-on course, students will learn about Azure SQL Data Warehouse. This course will review basic architecture of Azure SQL Data Warehouse. We will cover tools used with Azure SQL Data Warehouse, loading SQL Data Warehouse and basic workload management in SQL Data Warehouse.

Lecture
5 (11)
Sep 17 2016
Beginner
1h 15m
Paul Burpo

In the course Introduction to Azure SQL Database we will discuss the configuration, performance, security, availability, recovery and automation of Azure SQL Database. We will also review hybrid solutions with SQL Server Stretch Database. This course will partially help prepare you for exam 70-473 Designing and Implementing Cloud Data Platform Solutions.This course will help you prepare for Microsoft Exam 70-533 - Implementing Azure Infrastructure Solutions and 70-532 Developing Azure Solutions as well.

Lecture
5 (1)
Oct 30 2018
Beginner
50m
Paul Burpo

This course introduces students to Azure Data Factory V2. Students will learn about the different phases of a Data Factory Pipeline. Students will then cover Data Factory Architecture, terminology, the copy activity, file formats, integration runtimes, scheduling and triggers, and data factory management.

Lecture
5 (2)
Jan 14 2019
Beginner
45m
Shep Sheppard

This course covers the necessary tools and concepts used in the data science industry to include machine learning, statistical inference, working with data at scale and much more.

Lecture
5 (4)
Jul 4 2018
Intermediate
54m
Paul Burpo

This training provides an overview of Azure Databricks and Spark. In this course you will learn where Azure Databricks fits in the big data landscape in Azure. Key features of Azure Databricks such as Workspaces and Notebooks will be covered. Students will also learn the basic architecture of Spark and cover basic Spark internals including core APIs, job scheduling and execution. This class will prepare developers and administrators for more advanced work in Azure Databricks such as Python or Scala development.

Lecture
5 (1)
Oct 30 2018
Intermediate
32m
Paul Burpo

This course looks at services and tools used for machine learning with Azure. This course will introduce students to Machine Learning Server, SQL Server Machine Learning Services, Cognitive Toolkit, the Data Science Virtual Machine, and the Azure AI Gallery.This course will assist you in preparing for the "Using Other Services for Machine Learning" section of the "Perform Cloud Data Science with Azure Machine Learning" Microsoft Exam 70-774.

Lecture
5 (10)
Apr 23 2017
Intermediate
1h 8m
Paul Burpo

This module will provide an overview of big data, IoT and machine learning solutions in Azure. We will define the meaning of big data and look at the reasons why you might need a big data solution. We will then move on to a discussion of the analytics maturity model to understand how machine learning extracts value from big data. Next, we will review the lambda architecture which is the dominant architecture for big data solutions. We will look at the Azure components used in big data solutions and how they fit together to build an end-to-end lambda architecture in Azure. Finally, we will wrap up with a discussion of the Cortana Intelligence Suite and the value that it brings to big data and analytics solutions in Azure.

Lecture
4 (3)
May 9 2018
Beginner
1h 33m
Paul Burpo

This course builds on your Power BI skills and walks you through the interfaces of both the Online and Desktop offerings before embarking on a journey that will show you how to ingest data, transform data, create reports and dashboards before publishing and using your data sets, reports and dashboards in the Power BI online tenant.The course will help prepare students to take the Microsoft 70-778, Analyzing and Visualizing Data with Power BI certification exam.

Lecture
5 (9)
Jan 4 2017
Intermediate
43m
Chris Pietschmann

The Real-Time Ingestion and Processing in Azure course covers information about implementing real-time event stream ingestion and processing within Microsoft Azure. The course starts with an overview of the Lambda Architecture and what a Message Broker is used for. The course continues to cover the Azure Event Hubs and Azure IoT Hub services used for event stream ingestion, and Azure Stream Analytics and HDInsight for integrating real-time event processing. Finally, the course finishes with an overview of a few example architectures to give a better perspective on architecting Real-Time Ingestion and Processing solutions within the Microsoft Azure cloud. This course should help in preparation for the 70-534 exam, Architecting Microsoft Azure Solutions.

Lecture
5 (7)
May 9 2017
Intermediate
2h 19m
Paul Burpo

In this hands-on course, students will learn about running SQL Server in Azure. This course will review basic Azure networking and storage using the Azure Resource Manager architecture to prepare students for building SQL Server solutions in Azure. The primary focus of this course is SQL Server cloud and hybrid-cloud solutions on Azure Infrastructure as a Service (IaaS). This course will cover best practices for deploying SQL Server on Azure Virtual Machines including standalone SQL Servers and hybrid Availability Groups. The course will look at SQL Server features that take advantage of Azure Storage such as SQL Server Managed Backup, Azure Snapshot Backups, and SQL Server data files hosted on Azure Storage.

34 Results
Real-Time Lab
5 (1)
Feb 4 2018
Intermediate
3h 30m
Opsgility

In this lab, you will learn to build powerful dashboards and reports in Power BI. You will learn to take advantage of advanced data analytics features of Power BI such as DAX queries, KPIs and R scripts.

Real-Time Lab
0 (0)
Apr 4 2019
Beginner
1h 15m
Opsgility

In this lab, you will provision how to provision a Databricks workspace, an Azure storage account, and a Spark cluster. You will learn to use the Spark cluster to explore data using Spark Resilient Distributed Datasets (RDDs) and Spark Dataframes.

Real-Time Lab
0 (0)
Feb 20 2019
Intermediate
4h
Opsgility

In this lab, you will author and execute multiple stored procedures within your Azure Cosmos DB instance. You will explore features unique to JavaScript stored procedures such as throwing errors for transaction rollback, logging using the JavaScript console and implementing a continuation model within a bounded execution enviornment.

Real-Time Lab
0 (0)
Jan 17 2019
Advanced
2h 40m
Opsgility

In this workshop, you will deploy a web app using Machine Learning Services to predict travel delays given flight delay data and weather conditions. Plan a bulk data import operation, followed by preparation, such as cleaning and manipulating the data for testing, and training your machine learning model.At the end of this workshop, you will be better able to build a complete machine learning model in Azure Databricks for predicting if an upcoming flight will experience delays. In addition, you will learn to store the trained model in Azure Machine Learning Model Management, then deploy to Docker containers for scalable on-demand predictions, use Azure Data Factory (ADF) for data movement and operationalizing ML scoring, summarize data with Azure Databricks and Spark SQL, and visualize batch predictions on a map using Power BI.

Real-Time Lab
0 (0)
Feb 21 2019
Intermediate
1h 45m
Opsgility

In this lab, you will create an Azure Data Lake Store Gen2 account. You will learn to lock down and manage access of the Data Lake Store, taking advantage of both role-based access control and Data Lake Store Azure AD integration. Finally, you will process a bulk ingest using Hadoop distcp utility.

Real-Time Lab
5 (1)
Sep 26 2018
Intermediate
2h 55m
Opsgility

In this lab, you will learn techniques for troubleshooting and turning performance with a Cosmos DB database.

Real-Time Lab
0 (0)
Feb 20 2019
Intermediate
4h
Opsgility

In this lab, you will create multiple Azure Cosmos DB containers. Some of the containers will be unlimited and configured with a partition key, while others will be fixed-sized. You will then use the SQL API and .NET SDK to query specific containers using a single partition key or across multiple partition keys.

Real-Time Lab
4 (6)
Apr 2 2019
Beginner
1h 15m
Opsgility

In this lab you will create an Azure SQL Database using the Azure Portal and connect to it using SQL Server Management Studio. You will then migrate a SQL Server database hosted on a virtual machine to an Azure SQL Database.

Real-Time Lab
5 (2)
May 4 2018
Beginner
1h 15m
Opsgility

Today, data is being collected in ever-increasing amounts, at ever-increasing velocities, and in an ever-expanding variety of formats. This explosion of data is colloquially known as the Big Data phenomenon.In order to gain actionable insights into big-data sources, new tools need to be leveraged that allow the data to be cleaned, analyzed, and visualized quickly and efficiently. Azure HDInsight provides a solution to this problem by making it exceedingly simple to create high-performance computing clusters provisioned with Apache Spark and members of the Spark ecosystem. Rather than spend time deploying hardware and installing, configuring, and maintaining software, you can focus on your research and apply your expertise to the data rather than the resources required to analyze that data.Apache Spark is an open-source parallel-processing platform that excels at running large-scale data analytics jobs. Spark’s combined use of in-memory and disk data storage delivers performance improvements that allow it to process some tasks up to 100 times faster than Hadoop. With Microsoft Azure, deploying Apache Spark clusters becomes significantly simpler and gets you working on your data analysis that much sooner.In this lab, you will experience HD Insight with Spark first-hand. After provisioning a Spark cluster, you will use the Microsoft Azure Storage Explorer to upload several Jupyter notebooks to the cluster. You will then use these notebooks to explore, visualize, and build a machine-learning model from food-inspection data — more than 100,000 rows of it — collected by the city of Chicago. The goal is to learn how to create and utilize your own Spark clusters, experience the ease with which they are provisioned in Azure, and, if you're new to Spark, get a working introduction to Spark data analytics.

Real-Time Lab
5 (1)
Aug 22 2018
Intermediate
2h 20m
Paul Burpo

In this lab, you will learn to build, monitor, manage and troubleshoot data pipelines with Azure Data Factory V2. You will learn to use the Copy Data wizard to build pipeline with no coding. You will build a custom pipeline to copy data from Blob storage to a table in Azure SQL Database. You will build a tumbling window pipeline to pick up data on a daily basis. Finally, you will learn to use the Management Monitoring tools to troubleshoot pipeline failures.

Real-Time Lab
5 (3)
Oct 10 2018
Intermediate
2h
Real-Time Lab
5 (1)
Apr 17 2018
Intermediate
50m
Paul Burpo

In this lab, you will use AzureML to set up a model to forecast prices. We will also use R and RStudio in order to learn more R programming. Predicting the increase in sales from a number of factors is an example of regression, or you could simply call it scoring, which is a more familiar term. If you want to know how small variations in input variables affect outcome, then you likely want to use a regression method. If you’re trying to predict scores, regression is likely a good choice for this business requirement. There are different types of regression, and the selection of regression method depends on the business problem that you are trying to solve. For example, if you want to work out the probability that an object is in a given class, then you could use logistic regression, which is aimed at estimating class probabilities. In practical terms, what does that actually mean? Well, an example might be estimating the probability of fraud in a credit card purchase, where we might want to work out the probability that it is a fraudulent purchase. We are also going to use a new method to work with missing data. In the Missing Data task, the PCA option approximates the covariance for the full dataset to reconstruct the missing data. In practice, this means that AzureML will use the PCA method to ‘guess’ what the missing data will be. For each column, AzureML will add an additional column which will identify whether the data was originally missing, or whether it was present. Later on, this makes it easier to visualize the data since we can include or exclude data which was originally missing, in line with the user requirements or to promote further analysis.

Real-Time Lab
4 (27)
Feb 14 2019
Beginner
1h 50m
Opsgility

In this lab, you will create a virtual network that will allow the virtual machines you create to securely connect with each other. You will then create two virtual machines and specify the virtual network configuration and the availability set configuration along with storage for the virtual machine.

Real-Time Lab
5 (1)
Sep 19 2017
Advanced
1h 10m
Paul Burpo

In this lab, we will explore the use of columnstore indexes in Azure SQL Database. We will evaluate the performance improvements we get when we implement columnstore indexes on tables for with analytical workloads.

Real-Time Lab
0 (0)
Sep 19 2017
Intermediate
1h 10m
Paul Burpo

In this lab, you will explore real-time operational analytics using Azure SQL Database. You will evaluate the performance improvements you will get when you add updateable non-clustered columnstore indexes on top of standard tables as well as memory-optimized tables.

Real-Time Lab
0 (0)
Jan 4 2019
Beginner
1h
Opsgility

Spark structured streaming enables you to use the dataframe API to read and process an unbounded stream of data. This kind of processing is used in real-time scenarios to aggregate data over temporal intervals or windows. You can use Spark to process streaming data from a wide range of sources, including Azure Event Hubs, Kafka, and others. In this lab, you will run a Spark job to continually process a real-time stream of data.

Real-Time Lab
0 (0)
Sep 19 2017
Intermediate
1h 20m
Paul Burpo

In this lab, we will examine the use of In-Memory OLTP in Azure SQL Database. We will compare performance across standard and in-memory architectures including memory optimized tables and natively compiled stored procedures.

Real-Time Lab
5 (1)
Sep 23 2018
Intermediate
45m
Opsgility

In this lab you will leverage the Azure Portal to create an instance of Azure Cosmos DB with SQL API. You will use the Data Explorer feature to create a database, create a collection and add documents to your collection. Next you will configure a Java application to connect to your Cosmos DB instance, create databases, create collections and query documents in the collection.

Real-Time Lab
5 (1)
Apr 11 2018
Intermediate
2h 40m
Paul Burpo

In this lab, you will set up an Azure Machine Learning Studio account. You will then walk through the various features and capabilities of Azure Machine Learning Studio. You will load data from local and external sources. You will clean, manipulate and transform the data to make it usable for machine learning. Finally, you will create a binary classification model using two-class boosted decision trees to build a targeted mailing list.

Real-Time Lab
5 (3)
May 23 2018
Intermediate
2h 10m
Chris Pietschmann

In this lab, you will use Visual Studio and ASP.NET to learn how to use Cosmos DB as a backend for an MVC application. You will learn how to programmatically read and write data, create and call a user-defined functions as well as understand management capabilities such as users and permissions, monitoring and scalability options.

Real-Time Lab
5 (2)
Sep 13 2018
Intermediate
45m
Opsgility

In this lab, you will deploy and configure an on-premises gateway to work with Azure Logic Apps. The on-premises data gateway acts as a bridge, providing quick and secure data transfer between on-premises data (data that is not in the cloud) and the Power BI, Microsoft Flow, Logic Apps, and PowerApps services.

Real-Time Lab
0 (0)
Jan 4 2019
Beginner
1h
Opsgility

Spark includes an API named Spark MLLib (often referred to as Spark ML), which you can use to create machine learning solutions. Machine learning is a technique in which you train a predictive model using a large volume of data so that when new data is submitted to the model it can predict unknown values. The most common types of machine learning are supervised learning and unsupervised learning. In a supervised learning scenario, you start with a large volume of data that includes both features (categorical and numeric values that describe characteristics of the entity you’re trying to predict something about) and labels (the value your model will predict. Training the model involves applying a statistical algorithm that fits the features to the labels. Because your initial data includes known values for the labels, you can train the model and test its accuracy with these known label values – giving you confidence that the model will work accurately with new data for which the label values aren’t known. Unsupervised learning is a technique in which there are no known label values, and the model is trained to group (or cluster) similar entities together based on their features.In this lab, we’ll focus on supervised learning; and specifically a type of machine learning called classification in which you train a model to identify which category, or class an entity belongs to. You will train a classifier to use features of flights that are enroute to an airport, and predict whether they will be late or on-time.

Real-Time Lab
5 (4)
Oct 10 2018
Intermediate
2h 5m
Paul Burpo

In this lab, you learn about leveraging Azure storage with SQL Server. We will cover hosting data files directly from Azure Storage, backup to URL and snapshot backups.

Real-Time Lab
0 (0)
Nov 1 2018
Beginner
1h 30m
Cloud Trainer

In this lab, you will take advantage of Azure HDInsight to perform machine learning in big data scenarios

Real-Time Lab
5 (3)
Feb 15 2019
Intermediate
1h 40m
Opsgility

In this lab, you will use PowerShell to manage Azure SQL Database. You will create a logical Azure SQL Server via PowerShell. You will then manage the firewall to allow remote connectivity to allow for client access. You will restore a database from an existing BACPAC file. Finally, you will use PowerShell to scale the database performance and pricing tier.

Real-Time Lab
5 (4)
Feb 1 2019
Beginner
1h 15m
Opsgility

In this lab, you will learn how to configure and manage an Azure Cosmos DB Account (formerly Azure DocumentDB), including how to query and manage JSON documents within a Collection. Among the topics covered are using SQL language syntax to perform document queries that return JSON results, and implementing and testing global data replication and fail over.

Real-Time Lab
5 (4)
Oct 10 2018
Advanced
1h 25m
Paul Burpo

In this lab, we will walk through management and monitoring of an Elastic Pool. First, we will create an Elastic Pool and add our databases to the pool. Then we will monitor the performance of our pool using TSQL Scripts and the Azure Portal.

Real-Time Lab
5 (1)
Jan 4 2019
Beginner
1h
Opsgility

In this lab, you will provision how to provision a Databricks workspace, an Azure storage account, and a Spark cluster. You will then execute and manage a Spark Job.

Real-Time Lab
0 (0)
Feb 20 2019
Intermediate
4h
Opsgility

In this lab, you will query an Azure Cosmos DB database instance using the SQL language. You will use features common in SQL such as projection using SELECT statements and filtering using WHERE clauses. You will also get to use features unique to Azure Cosmos DB’s SQL API such as projection into JSON, intra-document JOIN and filtering to a range of partition keys.

Real-Time Lab
5 (1)
Sep 26 2018
Intermediate
1h
Cloud Trainer

In this lab you will learn to use Cosmos DB and Azure Databricks to build real-time stream processing solution. You will use a pre-built application to read the Twitter data stream into Cosmos DB. You will then configure Azure Databricks to be able to read the change feed of your Cosmos DB collection and you will use Scala to process the data and visualize the data stream in a Databricks Notebook.

Real-Time Lab
5 (1)
Apr 13 2018
Intermediate
2h 10m
Paul Burpo

In this lab, you learn about deploying SQL Server on Azure virtual machines. This lab will walk you through some common setup and configuration tasks for running SQL Server in Azure infrastructure as a service.

Real-Time Lab
0 (0)
Feb 20 2019
Intermediate
4h
Opsgility

In this lab, you will use the .NET SDK to tune an Azure Cosmos DB request to optimize performance of your application.

Real-Time Lab
5 (4)
Aug 3 2018
Beginner
1h
Paul Burpo

In this lab, you will build a machine learning experiment using Azure Machine Learning. You will start by creating a Machine Learning Workspace in the Azure Portal. You will then login to ML Studio where you will import an external dataset, clean the dataset, choose a machine learning algorithm and train your model. Finally, you will score and evaluate your model to determine its accuracy.

Real-Time Lab
5 (1)
Oct 31 2018
Beginner
1h
Cloud Trainer

In this lab, you learn to leverage Machine Learning Server and SQL Server Machine Learning Services to execute R code. You will use pre-installed tools of the Data Science Virtual Machine to execute Jupyter Notebooks and execute remote R code against Machine Learning Server. You will then leverage SQL Server Machine Learning Services to execute R code in SQL Server.

26 Results
Instructor-Led Course
3 Days
Intermediate
Opsgility

In this course, you will explore the Spark Internals and Architecture of Azure Databricks. The course will start with a brief introduction to Scala. Using the Scala programming language, you will be introduced to the core functionalities and use cases of Azure Databricks including Spark SQL, Spark Streaming, MLlib, and GraphFrames.

Instructor-Led Course
3 Days
Intermediate
Opsgility

The Architecting Azure Big Data and Analytics course is designed to give students a clear architectural understanding of the application of big data patterns in Azure. Students will participate in team based architectural planning and hands-on implementation sessions. Students will be taught basic Lambda architecture patterns in Azure, leveraging the scalability and elasticity of Azure in Big Data and IoT solutions as well as an introduction to cognitive services, machine learning, and artificial intelligence (AI).An introduction to data science techniques in Azure will also be covered. Individual case studies will focus on specific real-world problems that represent common big data patterns and practices. Students will also experience several hands-on labs to introduce them to some of the key services available.

Instructor-Led Course
5 Days
Intermediate
Opsgility

The Azure Big Data and Analytics Boot camp is designed to give students a clear architectural understanding of the application of big data patterns in Azure. Students will participate in team based architectural planning and hands-on implementation sessions. Students will be taught basic Lambda architecture patterns in Azure, leveraging the scalability and elasticity of Azure in Big Data and IoT solutions.An introduction to data science techniques in Azure will also be covered. Individual case studies will focus on specific real-world problems that represent common big data patterns and practices. Students will also experience several hands-on labs to introduce them to some of the key services available.

Instructor-Led Course
2 Days
Intermediate
Opsgility

This course explores Microsoft Azure’s AzureML service offering for students that are either new to machine learning or new to Azure. The course starts with an introduction to various aspects of building experiments in AzureML and using MLStudio to create cohesive machine learning workflows.Each topic looks at different aspects of AzureML as well as introduces different concepts in machine learning such as regression, clustering and classification and when to use each. The course moves onto more advanced topics such as how the R language can be used to enrich AzureML as well as being able to define neural networks and lastly how to integrate into more complex data orchestrations involving other services in Azure.Learning format:• 40% presentation• 40% hands-on labs• 20% whiteboard design

Instructor-Led Course
2 Days
Advanced
Opsgility

This course covers all aspects of Azure SQL Database performance. This course will cover the performance monitoring and troubleshooting tools available in Azure SQL Database. We will cover designing performant databases in Azure SQL Database, leveraging in-memory and columnstore technologies. Finally, we will wrap up by discussing elastic database pools and the special challenges they bring to monitoring and tuning performance

Instructor-Led Course
3 Days
Intermediate
Opsgility

The Azure Big Data and Machine Learning Bootcamp is designed to give students a clear architectural understanding of the application of big data patterns in Azure. Students will participate in team based architectural planning and hands-on implementation sessions. Students will be taught basic Lambda architecture patterns in Azure, leveraging the scalability and elasticity of Azure in Big Data and IoT solutions.An introduction to data science techniques in Azure will also be covered. Individual case studies will focus on specific real-world problems that represent common big data patterns and practices. Students will also experience several hands-on labs to introduce them to some of the key services available.Format:Instructor-led with hands-on labs and whiteboard design sessions

Instructor-Led Course
1 Day
Advanced
Opsgility

A cloud workshop is a 1-day event that consists of an overview of the technology, a deep dive whiteboard design session and Hands-on lab where participants will a subset of the solution.In this Workshopyou willlearn how to upgrade from Oracle Databases and earlier SQL Server Databases to SQL Server 2016 and Azure SQL DB. SQL Server 2016 on Windows Server 2016 (and now also available on Linux) will offer higher availability, greater performance and faster analytics. SQL Server 2016 and Azure DB supports virtually any data, of any size, with any application on any platform. SQL Server 2016 also boasts the fastest In-Memory technology on the planet across workloads helping customers to take performance and throughput to another level. It is also possible to build a hybrid data platform with frequently accessed data in SQL Server 2016 and less frequently accessed data in Azure’s SQL Database. Attend this workshop to upgrade to these latest versions to take advantage of these benefits to increase protection from security vulnerabilities. This workshop includes: Whiteboard design session and Hands-on lab

Instructor-Led Course
1 Day
Advanced
Opsgility

A cloud workshop is a 1-day event that consists of an overview of the technology, a deep dive whiteboard design session and Hands-on lab where participants will a subset of the solution.In this workshop, attendees will learn real-time analytics without IoT. Enable intelligent conversation in a machine learning-enabled, real-time chat pipeline and apply analytics to visualize customer sentiment in real-time for hospitals to allow guests to chat with one another, and to communicate directly with the concierge. This workshop includes: Whiteboard design session and Hands-on lab

Instructor-Led Course
1 Day
Advanced
Opsgility

A cloud workshop is a 1-day event that consists of an overview of the technology, a deep dive whiteboard design session and Hands-on lab where participants will a subset of the solution.In this workshop, attendees will implement an IoT solution for intelligent vending machines leveraging Facial feature recognition and Machine learning to drive on-demand pricing, enable real-time analytics, and cloud to device messaging flows. Learn how to create Machine Learning models in R, train the models at scale using R and Spark on HDInsight, then expose the model as a web service through R Server Operationalization. You will use IoT Hub to facilitate vending machine device registration and communication for product promotions, and enable real-time analytics with SQL Database in-memory and columnar indexing. This workshop includes: Whiteboard design session and Hands-on lab

Instructor-Led Course
1 Day
Advanced
Opsgility

A cloud workshop is a 1-day event that consists of an overview of the technology, a deep dive whiteboard design session and Hands-on lab where participants will a subset of the solution.In this workshop, attendees will migrate a retail chain to from an existing data warehouse from an on-premises SQL Server into Azure SQL Data Warehouse. Prepare a detailed migration plan including data preparation, importing data into Azure SQL Data Warehouse, and architecting a data orchestration strategy to move data from the existing on-premises source systems to Azure SQL Data Warehouse. This workshop includes: Whiteboard design session and Hands-on lab

Instructor-Led Course
1 Day
Advanced
Opsgility

A cloud workshop is a 1-day event that consists of an overview of the technology, a deep dive whiteboard design session and Hands-on lab where participants will a subset of the solution.In this workshop, students will work with a media publishing company to design a hybrid cloud disaster recovery solution. Students will design the solution to handle large spikes in load and harden the security to include encryption of PCI data. Additionally students will implement an archival strategy to keep databases sizes in check. This workshop will include: Whiteboard design session.

Instructor-Led Course
3 Days
Intermediate
Opsgility

In this hands-on course, students will learn about running SQL Server in Azure. This course will review basic Azure networking and storage using the Azure Resource Manager architecture to prepare students for building SQL Server solutions in Azure. The primary focus of this course is SQL Server cloud and hybrid-cloud solutions on both Azure Platform as a Service (PaaS) and Azure Infrastructure as a Service (IaaS). This course will cover best practices for deploying SQL Server on Azure Virtual Machines including standalone SQL Servers and hybrid Availability Groups. The course will look at SQL Server features that take advantage of Azure Storage such as SQL Server Managed Backup, Azure Snapshot Backups, and SQL Server data files hosted on Azure Storage. Finally this course will provide you with an introduction to Azure SQL Database and archiving cold data with SQL Server Stretch Database.

NEW
Instructor-Led Course
4 Days
Beginner
Opsgility

In this course student will learn how to define and prepare the development environment, prepare data for modeling, perform feature engineering and develop models.Azure Data Scientists apply Azure’s machine learning techniques to train, evaluate, and deploy models that solve business problems.This course will prepare you for DP-100: Designing and Implementing a Data Science Solution on Azure exam.

Instructor-Led Course
3 Days
Intermediate
Opsgility

In this course, the students will implement various data platform technologies into solutions that are in line with business and technical requirements including on-premises, cloud, and hybrid data scenarios incorporating both relational and No-SQL data. They will also learn how to process data using a range of technologies and languages for both streaming and batch data.The students will also explore how to implement data security including authentication, authorization, data policies and standards. They will also define and implement data solution monitoring for both the data storage and data processing activities. Finally, they will manage and troubleshoot Azure data solutions which includes the optimization and disaster recovery of big data, batch processing and streaming data solutions.

Instructor-Led Course
2 Days
Intermediate
Opsgility

In this course, the students will design various data platform technologies into solutions that are in line with business and technical requirements. This can include on-premises, cloud, and hybrid data scenarios which incorporate relational, No-SQL or Data Warehouse data. They will also learn how to design process architectures using a range of technologies for both streaming and batch data.The students will also explore how to design data security including data access, data policies and standards. They will also design Azure data solutions which includes the optimization, availability and disaster recovery of big data, batch processing and streaming data solutions.

Instructor-Led Course
3 Days
Intermediate
Opsgility

This course introduces you to Microsoft Cognitive Services and takes you through a gradual journey of features through search, audio, computer vision and language processing services. Along with it’s capabilities, this course explains how to get started developing applications that take advantage of Microsoft Azure Cognitive Service offerings. Once you have clear understanding of all the offerings you can make better decisions on when and how to incorporate Cognitive Services into Enterprise server, desktop, mobile, web, IoT and extended reality (xR/VR/AR/MR) applications.This course will introduce you how to all offerings of Azure Cognitive Services in many different environments, server, web, UWP Store and xR applications.Overview of all Microsoft Azure Cognitive ServicesHow the industry is taking advantage of Azure Cognitive ServicesWhat are the Search Based ServicesHow to invoke Search Based ServicesWhat are the Audio Based ServicesWhat are the Computer Vision/Image based servicesHow to invoke the Computer Vision and Image based servicesWhat are the Text/Language based servicesWhat are the Generic Machine learning based services

Instructor-Led Course
3 Days
Intermediate
Opsgility

In this hands-on course, students will learn about running SQL Server in Azure. This course will review basic Azure networking and storage using the Azure Resource Manager architecture to prepare students for building SQL Server solutions in Azure. The primary focus of this course is SQL Server cloud and hybrid-cloud solutions on both Azure Platform as a Service (PaaS) and Azure Infrastructure as a Service (IaaS). This course will cover best practices for deploying SQL Server on Azure Virtual Machines including standalone SQL Servers and hybrid Availability Groups. The course will look at SQL Server features that take advantage of Azure Storage such as SQL Server Managed Backup, Azure Snapshot Backups, and SQL Server data files hosted on Azure Storage. Finally, this course will provide you with an introduction to Azure SQL Database and archiving cold data with SQL Server Stretch Database. This course can help prepare you for the exam: 70-473 Designing and Implementing Cloud Data Platform Solutions.

Instructor-Led Course
3 days
Intermediate
Opsgility

The main purpose of the course is to give students the ability to use Microsoft R Server to create and run an analysis on a large dataset, and show how to utilize it in Big Data environments, such as a Hadoop or Spark cluster, or a SQL Server database.

Instructor-Led Course
5 Days
Intermediate
Opsgility

The main purpose of the course is to give students the ability to analyze and present data by using Azure Machine Learning, and to provide an introduction to the use of machine learning with big data tools such as HDInsight and R Services.

Instructor-Led Course
5 Days
Intermediate
Opsgility

The main purpose of the course is to give students the ability plan and implement big data workflows on HDInsight.

Instructor-Led Course
5 Days
Intermediate
Opsgility

This five-day instructor-led course describes how to process Big Data using Azure tools and services including Azure Stream Analytics, Azure Data Lake, Azure SQL Data Warehouse and Azure Data Factory. The course also explains how to include custom functions, and integrate Python and R.

Instructor-Led Course
3 Days
Intermediate
Opsgility

This three-day instructor-led course is aimed at database professionals who are looking to implement a Cosmos DB solution.

Instructor-Led Course
2 days
Intermediate
Opsgility

The main purpose of the course is to give students a good understanding of data analysis with Power BI. The course includes creating visualizations, the Power BI Service, and the Power BI Mobile App.Audience profileThe course will likely be attended by SQL Server report creators who are interested in alternative methods of presenting data. At course completion

Instructor-Led Course
3 Days
Intermediate
Opsgility

The focus of this three-day instructor-led Microsoft Training course is on designing and implementing cloud data platform solutions with the Microsoft Data Platform by using SQL Server on-premises, hybrid and cloud data platform solutions. It describes how to design and implement and optimize workloads in hybrid scenarios with both on-premises and Microsoft Azure cloud-based solutions, and how to implement high availability and disaster recovery solutions.

Instructor-Led Course
2 Days
Beginner
Opsgility

55224A-1 is a two-day instructor-led course is intended for data professionals who want to expand their knowledge about creating big data analytic solutions on Microsoft Azure. Students will learn how to design solutions for batch and real-time data processing. Different methods of using Azure will be discussed and practiced in lab exercises, such Azure CLI, Azure PowerShell and Azure Portal. 55224A-1 labs and exercises cover the first two objectives of exam 70-475 (Designing Big Data batch, interactive real-time solutions). The other two objectives (Designing Machine Learning and cloud analytics solutions) are covered in 55224A-2.

Instructor-Led Course
2 Days
Intermediate
Opsgility

This course builds on your Power BI skills and walks you through the interfaces of both the Online and Desktop offerings before embarking on a journey that will show you how to ingest data, transform data, create reports and dashboards before publishing and using your data sets, reports and dashboards in the Power BI online tenant.The course will prepare students to take the Microsoft 70-778, Analyzing and Visualizing Data with Power BI certification exam.