MOC 20777 kursus: Implementing Microsoft Azure Cosmos DB Solutions kursus

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Business Intelligence
Big Data og AI
MOC 20777 kursus: Implementing Microsoft Azure Cosmos DB Solutions kursus

Det lærer du

Dette kursus i Big Data er rettet mod dig, der ønsker at lære at arbejde med Big Data i Microsoft Azure værktøjer. Du vil på kurset bl.a. lære at anvende Azure Stream Analytics, Azure Data Lake, SQL Data Warehouse og Azure Data Factory.

Efter kurset vil du være i stand til at:

Anvende og beskrive Azure Cosmos DB arkitektur
Oprette brugerdefinerede funktioner, stored procedures og triggers
Optimere og overvåge databaser
Oprette Graph data modeller med Azure Cosmos DB
Analysere data i Azure Cosmos DB med Azure Search, HDInsight, Azure Databricks og Power BI
Anvende Azure Cosmos DB og data streaming

Det får du

Før kurset

Mulighed for at tale med en instruktør, der kan hjælpe dig med at finde det helt rigtige kursus.

På kurset

Undervisning af Danmarks mest erfarne instruktørteam i hyggelige og fuldt opdaterede kursuslokaler i centrum af København.
Et kursus bestående af en vekslen mellem teori og praktiske øvelser. Vi ved, hvor vigtigt det er, at du får tid til at arbejde med opgaverne i praksis, og derfor har vi altid fokus på hands-on i undervisningen.
Adgang til Microsofts digitale kursusmateriale (DMOC) samt Microsoft Labs Online.*
Fuld forplejning, som inkluderer morgenmad, friskbrygget kaffe, te, frugt, sodavand, frokost på en italiensk restaurant på Gråbrødretorv, kage, slik, og naturligvis Wi-Fi til dine devices.
Et kursuscertifikat med bevis på dine nye kvalifikationer.

Efter kurset

Adgang til vores gratis hotline, som betyder, at du op til et år efter kurset kan ringe eller skrive til os, hvis du har spørgsmål til de emner, der er blevet gennemgået på kurset.
Vores unikke tilfredshedsgaranti, som er din tryghed for at få fuldt udbytte af dit kursus.

Kurset bliver afholdt på dansk, men vi benytter Microsofts digitale materiale (DMOC), som er på engelsk. På kurset bliver der stillet en Surface tablet til rådighed, som kan anvendes til læsning af materialet. Du vil efterfølgende have adgang til materialet både online og lokalt. I tilfælde af at Microsoft laver en ny version af kursusmaterialet, vil du automatisk få adgang til det. Derudover vil du have adgang til øvelser via Microsoft Online Labs i 19 dage i alt, og du kan derfor fortsætte eller starte forfra på en øvelse hjemmefra, under eller efter kurset, alt efter behov.

Få det optimale ud af kurset

Få det optimale ud af kurset

Dette Big Data kursus indgår som en del af vores samlede udbud af Business Intelligence kurser og forudsætter kendskab til Microsoft Azure Services og indgående kendskab til [link=/kurser/business-intelligence/datamodellering-og-design/1129/grundlæggende-business-intelligence-(bi)[/link].

Kursusindhold

Module 1: Introduction to Azure Cosmos DB

Describe the purpose and architecture of Cosmos DB.

Lessons

Review of NoSQL database structures
Migrating data and applications to Cosmos DB
Managing data in Cosmos DB

Lab : Creating and using a SQL API database in Cosmos DB

Creating and configuring a Cosmos DB database
Migrating data from a Mongo DB database to Cosmos DB
Using the SQL API to access data
Protecting data in a Cosmos DB database

After completing this module, students will be able to:

Create and configure a Cosmos DB.
Migrate data from a Mongo DB database to a Cosmos DB database.
Describe accessing data using the SQL API.
Describe how to protect data in a Cosmos DB.

Module 2: Designing and Implementing SQL API Database Applications

This module describes how to design documents and collections to meet business requirements, and how to use the SQL API to build applications that use these documents.

Lessons

Document models in Cosmos DB
Querying data in a SQL API database
Querying and maintaining data programmatically

Lab : Designing and implementing SQL API database applications

Design the document structure & partitioning strategy for the product catalog for the retail system
Importing product catalog data
Querying product catalog information
Maintaining stock levels in the product catalog

After completing this module, students will be able to:

Design NoSQL document structures that support business requirements and enable efficient operations.
Describe how to perform SQL queries against a SQL API database.
Explain how to insert, modify, delete, and query data in a SQL API database programmatically.

Module 3: Implementing Server Side Operations

Describe how to create user-defined functions, stored procedures, and triggers.

Lessons

Server-side programming with Cosmos DB
Creating and using stored procedures
Using triggers to maintain data integrity

Lab : Writing user-defined functions, stored procedures and triggers

Design and implement the document and collection structure
Implement the shopping cart functionality in the online retail system.
Extend the online retail system to create orders from the items in a shopping cart.
Extend the online retail system further to enable customers to view orders and backorders.

After completing this module, students will be able to:

Describe how Cosmos DB enables you to implement server-side operations by writing JavaScript code.
Describe how use the JavaScript Query API to implement transactional operations with stored procedures.
Describe how use create triggers that you can use to maintain integrity when inserting, updating, and deleting documents.

Module 4: Optimizing and monitoring performance

Describe how to optimize a database, and how to monitor performance.

Lessons

Optimizing database performance
Monitoring the performance of a database

Lab : Tuning a database and monitoring performance

Gathering execution statistics
Examining how the different consistency models can impact throughput and latency
Investigate the effects of triggers on performance
Monitoring performance and tuning the partition key

After completing this module, students will be able to:

Describe how to tune the configuration of a database and collections for best performance.
Describe how to assess the performance of a document database and identify options for improving throughput.

Module 5: Designing and Implementing a Graph Database

This module describes how to create efficient graph database models using Cosmos DB.

Lessons

Graph database models in Cosmos DB
Designing Graph database models for efficient operation

Lab : Designing and implementing a Graph database

Implementing a recommendations engine for customers
Recording product purchase information
Query a Graph database to obtain analytics

After completing this module, students will be able to:

Describe the features that Cosmos DB provides for implementing graph databases.
Design NoSQL graph structures that support business requirements and enable efficient operations.

Module 6: Querying and Analyzing Big Data with Cosmos DB

This module describes how to use Azure Search and HDInsight with Cosmos DB to query and analyze big data.

Lessons

Integrating Cosmos DB with Azure search to optimize queries
Analyzing data in a Cosmos DB database using Apache Spark
Visualizing data in a Cosmos DB database

Lab : Querying and Analyzing Big Data with Cosmos DB

Extending product search capabilities
Performing end-of-month processing
Visualizing sales data
Exploring sales data

At the end of this module, students will be able to:

Describe how to integrate Cosmos DB with Azure Search to perform efficient query processing over big data.
Describe how to analyze big data held in Cosmos DB using Apache Spark.
Describe how to visualize data in Cosmos DB using Jupyter notebooks, Power BI, and Azure Databricks.

Module 7: Implementing Stream Processing with Cosmos DB

This module describes how to use Cosmos DB as a source and sink for streaming data.

Lessons

Working with the Cosmos DB change feed
Integrating Cosmos DB into streaming solutions

Lab : Using Cosmos DB with stream processing

Handling orders
Maintaining stock analytic data
Displaying rolling revenue for a given time period

After completing this module, students will be able to:

Describe the Cosmos DB change feed, and how to use it to process data efficiently.
Explain how to incorporate Cosmos DB into streaming solutions such as Apache Kafka, Apache Spark, and Azure Stream Analytics.