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We're here to help you find itThe 40529: Microsoft Cloud Workshop: High Performance Computing (HPC) course is designed to provide a comprehensive understanding of deploying and managing HPC solutions on Azure. It focuses on leveraging Azure's capabilities to solve complex computation tasks and perform large-scale computations.
Module 1: Whiteboard Design Session covers the conceptual phase, where learners review a customer case study, design a proof of concept solution, and learn to present their solution, emphasizing Real-time data processing with Azure Database for PostgreSQL Hyperscale.
Module 2: Hands-on Lab offers practical experience, guiding learners through Setting up databases, Securing credentials with Key Vault, Integrating Azure Databricks, processing data with Kafka, performing Data rollups in PostgreSQL, and Creating visualizations in Power BI.
Participating in these HPC training courses will equip learners with the skills necessary to design and implement HPC solutions, making the HPC course invaluable for professionals aiming to excel in high-performance computing environments.
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♱ Excluding VAT/GST
Classroom Training price is on request
You can request classroom training in any city on any date by Requesting More Information
To ensure a successful learning experience in the 40529: Microsoft Cloud Workshop: High Performance Computing course, participants should possess the following minimum prerequisites:
Please note that while these prerequisites are recommended for the best learning outcome, learners with a keen interest and willingness to engage with the course material may also benefit from the workshop. Our instructors are equipped to provide guidance and support to all participants, regardless of their initial skill level.
The 40529: Microsoft Cloud Workshop: High Performance Computing course is tailored for IT professionals seeking expertise in Azure-based real-time data processing.
The 40529: Microsoft Cloud Workshop: High-Performance Computing course focuses on designing and implementing a real-time data processing solution using Azure Database for PostgreSQL Hyperscale, integrating services like Azure Databricks, Kafka, and Power BI.
High Performance Computing (HPC) involves using powerful computers to solve advanced computation problems that can't be handled by standard computers. HPC systems, comprising of supercomputers or clusters of computers working together, are crucial in scientific research, engineering, and large data analysis. By rapidly processing and analyzing massive amounts of data, HPC aids in making complex computations and simulations, like climate predictions or genomic sequencing. For professionals looking to master these capabilities, HPC training courses offer specialized knowledge and skills to efficiently use these high-tech systems.
Azure Database for PostgreSQL Hyperscale is an advanced service from Microsoft Azure that allows users to scale PostgreSQL databases horizontally. This means you can increase your database capacity by adding additional servers to handle large or growing datasets effectively. It's particularly useful for businesses that need to manage vast amounts of data without compromising performance. The service automates complex database administration tasks such as scaling out resources and managing replicas, making it easier to focus on business applications rather than database management. This simplifies operations and enhances efficiency, especially for dynamic data demands in real-time applications.
Real-time data processing involves the continuous input, processing, and output of data immediately as it is generated, without delay. This type of processing is crucial for applications that require instantaneous response and action on streaming data, such as financial trading platforms, live monitoring systems, and interactive web applications. By analyzing and acting on data in real-time, businesses and organizations can make quicker decisions, respond proactively, and enhance operational efficiency. This processing capability is essential in environments where timing and the speed of data analysis are critical to success.
Setting up databases involves creating a structured environment where data can be stored, managed, and retrieved efficiently. You start by choosing a database type, such as SQL or NoSQL, depending on your data needs and scalability requirements. Next, install the database software and configure it to define how data will be organized and how different parts of the data relate to each other. You'll then create tables and establish relationships between them to facilitate data integrity and query efficiency. Finally, set up security measures to protect your data, ensuring only authorized users can access or modify it. This setup is crucial for reliable, scalable data management.
Securing credentials with Key Vault involves using Microsoft's cloud service to safeguard cryptographic keys and other sensitive information. Key Vault helps restrict access, ensuring only authorized systems and users can retrieve these secrets. It helps automate tasks related to security, like renewing certificates without downtime. This process mitigates risks of data exposure and strengthens overall security by managing and storing credentials securely in a centralized location, thus supporting compliance and efficient management of confidential data in applications.
Integrating Azure Databricks involves connecting Azure's cloud-based data service, Databricks, with other Azure services for enhanced data analysis and collaboration. Azure Databricks simplifies big data processing using optimized Apache Spark clusters, providing a platform for data storage, processing, and analysis. By integrating, teams can seamlessly move data across systems, enabling more complex analytics and machine learning projects. This integration supports improved data sharing and security, making it easier for professionals to build, scale, and manage projects effectively within the Azure ecosystem.
Data rollups in PostgreSQL involve summarizing or aggregating detailed data into a compressed form, typically for easier analysis and faster performance in querying. This technique helps manage large volumes of data by transforming lengthy and detailed records into simpler, summarized versions. The process is commonly used in reporting and data analysis to provide clear insights over periods, such as daily sales totals or monthly transaction averages, without querying the entire dataset each time, thus improving efficiency and response times in database management.
Creating visualizations in Power BI involves using the software to transform data into interactive charts and graphs. This process helps professionals understand trends, outliers, and patterns by presenting data in a visually appealing and easy-to-digest format. In Power BI, you can select from a variety of visualization types, customize them to meet your needs, and compile them into dynamic reports and dashboards that update in real time as data changes. This tool is crucial for data-driven decision-making, enabling users to quickly glean insights and make informed business decisions based on complex datasets.
The 40529: Microsoft Cloud Workshop: High Performance Computing course is tailored for IT professionals seeking expertise in Azure-based real-time data processing.
The 40529: Microsoft Cloud Workshop: High-Performance Computing course focuses on designing and implementing a real-time data processing solution using Azure Database for PostgreSQL Hyperscale, integrating services like Azure Databricks, Kafka, and Power BI.
