
Explore Microsoft Azure Stream Analytics to capture data from internet sources and analyze it in near real-time, enabling integration with other systems and scalable, available solutions with reduced latency.
Prepare for the course by downloading core slides, resources, and source code from the website, sign up for services or launch a virtual machine, and post progress screenshots.
Discover Azure Stream Analytics to perform near real-time data processing from devices, sensors, and social sources, using the ASA portal and basic query setup for real-time analytics.
Download all the course resources, including the slides and other supplemental material, from the provided link and review them offline on your local machine.
Explore how Azure Stream Analytics captures and analyzes streaming and static data, sets up jobs with single or multiple data inputs, and yields clean, curated data for real-world use cases.
Explore Azure Stream Analytics for real-time data processing, integrating multiple streaming inputs and applying filters, joins, and windows to deliver outputs in near real time.
Explore Azure stream analytics jobs that curate and filter real-time data via inputs and outputs, scale with streaming units, and integrate with Power Buy and SQL Server 2016.
Configure inputs in an Azure Stream Analytics job, choosing a data stream source like Event Hubs, and write queries in the Azure Stream Analytics query language to output results.
Explore Azure Stream Analytics to curate real-time data with streaming units, inputs, outputs, and queries, using the portal and JavaScript user-defined functions to boost analytics.
Configure an Azure Stream Analytics job by adjusting streaming units for throughput, setting event ordering and error policy, and wiring data stream sources and reference data for real-time analytics.
Learn to inject real-time data into Azure Stream Analytics using Event Hubs and distinguish data stream from reference data inputs. Connect Event Hubs data to an Azure Stream Analytics job.
Connect an event hub as input to an Azure Stream Analytics job, then provision a Linux Azure VM and install Python and the Azure SDK to push test data.
Push real-time test data to the Event Hub by running a Python IoT data generator that streams JSON to Azure Service Bus, and use reference data for lookups.
Configure reference data inputs in Azure Stream Analytics by selecting blob storage, choosing a file, and joining it with streaming data from an event hub to correlate insights.
Configure outputs in Azure Stream Analytics, connecting ASA jobs to sinks such as Azure SQL Database, Blob storage, Event Hubs, and Power BI, with path patterns and subscription details.
Configure a blob storage output for NASA jobs, selecting the storage account and container, and use Jason with a line separator. Run and monitor the job.
Monitor input and output events in an Azure Stream Analytics job, customize the diagnostics graph, and configure a Power BI output to visualize streamed data as a tabular dataset.
Identify the key elements of an Azure Stream Analytics query and learn to write sql-like statements using select, from, and into to fetch and route specific fields, filtering input data.
Analyze how Azure Stream Analytics uses group by, timestamp fields, and two-second tumbling windows to count machine events and classify frequency with a case statement.
Integrate Azure Stream Analytics with Power BI to deliver real-time visualizations using Power BI tiles, outputs set up in ASA, and correlate live data with reference data from IoT sensors.
Visualize streaming data in Power BI by configuring Azure Stream Analytics to typecast incoming values from Event Hub, publish real-time dashboards, and build a line chart with a five-minute window.
Visualize real-time streaming data with Microsoft Power BI by exploring time window adjustments and visuals like voltage cards, temperature gauges, and bar charts, while noting latency in streaming data sets.
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As the old adage says:
information is power
For some time now, and with the boom of the Internet and social media, data is playing an increasingly bigger role in all organizations, which are continuously looking for solutions that will enable to capture data from different internet sources and analyze it in an as close to real-time rate as possible. This has caused organizations to invest in building solutions that not only can obtain and review data in depth and in real-time, but also save time in scheduling recurrent tasks and integrate with other systems seamlessly, allowing for scalability and availability while minimizing faults and latency.
Having the right information in time is a now a critical aspect to making strategic business decisions.This is where Azure Stream Analytics comes in, to provide an effective solution to this business need. Azure Stream Analytics, or ASA, is an independent, cost-effective, and near real-time processing agent that enables you to view and explore streaming data at a high-performance level. Using this portal, you can set up data streaming computations from devices, sensors, web sites, social media, applications, infrastructure systems, and more with just a few clicks.
These are some of the fundamental problems data analysts and data scientists struggle with on a daily basis.
This course teaches you how to design, deploy, configure and manage your real time scalable data analytics in the Azure cloud resources with Azure Stream Analytics.
The course will start with basics of ASA and query setup, and then moves deeper into details about ASA and its other integrated services so you can make the most out of the functionalities you have available in this tool.
If you’re serious about building scalable, flexible and robust data analytics With no infrastructure to manage, where you can process data on-demand, scale instantly, and only pay per job, then this course is for you.
These data analytics and Cloud Computing skills are in high demand, but there’s no easy way to acquire this knowledge. Rather than rely on hit and trial method, this course will provide you with all the information you need to get started with your Azure data analytics projects.
Startups and technology companies pay big bucks for experience and skills in these technologies. They demand data engineers to provide them real time actionable analysis - and in turn, you can demand top dollar for your abilities.
Did you answer, “Absolutely” to that question? If so, then our new training program "Azure Masterclass: Analyze your data with Azure Stream Analytics" is for you.
Look, if you're serious about becoming an expert data engineer and generating a significant income for you and your family, it’s time to take action.
Imagine getting that promotion which you’ve been promised for the last two presidential terms. Imagine getting chased by recruiters looking for skilled and experienced engineers by companies that are desperately seeking help.
We call those good problems to have