DP-900: Microsoft Azure Data Fundamentals Study Guide
Microsoft Azure provides an array of services that enable businesses and organizations to undergo digital transformation by making quick and informed decisions. The DP-900 Microsoft Azure Data Fundamentals exam evaluates learners' understanding of data concepts such as relational, non-relational, big data, and analytics. The exam requires learners to demonstrate their knowledge of core data concepts, relational and non-relational data, and Azure data services. Microsoft offers resources such as Microsoft Learn self-paced curriculum, an instructor-led course, and related documentation to help students prepare for the exam. Understanding Azure data principles is vital for more advanced Azure certifications like Azure Database Administrator Associate and Azure Data Engineer Associate.Stream data in real time from Azure Database for MySQL - Flexible Server to Power BI
Debezium, Kafka Connect, Azure Event Hubs, Azure Data Lake Storage, Azure Stream Analytics, Synapse SQL Serverless, and Power BI can work together to create a comprehensive data pipeline that captures data changes from relational databases, stores them in Azure Data Lake Storage, performs real-time analytics on the data stream using Azure Stream Analytics, and provides insights through Power BI.
ADX is now supported as output for Azure Stream Analytics job
Today we are announcing that Azure Stream Analytics can directly output data to Azure Data Explorer, simplifying architecture where customers need both hot and warm path analytics on streaming data. This feature will be added to all Stream Analytics regions progressively
Real-Time Processing with Data Vault 2.0 on Azure
In the last article, we discussed the Data Vault 2.0 architecture with regards to batch processing. However, Data Vault 2.0 is not limited to batch processing: it is possible to load data at any speed, in batches, CDC, near real-time or actual real-time. This article is based on the previous article but extends the architecture with real-time processing. We discussed several options on how real-time data can be ingested and how we, at Scalefree, typically implement a real-time Data Vault 2.0 architecture on the Azure cloud.Azure Stream Analytics: real-time analytics for Big Data, made easy
At the Microsoft Build Conference, we announced several new features extending the capabilities of Azure Stream Analytics, a managed service enabling real-time streaming analytics. With the new innovations announced today, Azure Stream Analytics brought down time-to-insight for Big Data streaming. These new capabilities will be demonstrated during the session “From cloud to the intelligent edge: Drive real-time decisions with Azure Stream Analytics”.Azure Stream Analytics releases slew of improvements at Ignite 2022: Output to Delta Lake and more!
Today we are excited to announce numerous new capabilities that unlock new stream processing patterns that work with your modern lakehouses. We are announcing native support of Delta Lake output, no code editor GA, improved development & troubleshooting experience and much more!Agile Data Vault 2.0 Projects with Azure DevOps
Having discussed the value of Data Vault 2.0 and the associated architectures in the previous articles of this blog series, this article will focus on the organization and successful execution of Data Vault 2.0 projects using Azure DevOps. It will also discuss the differences between standard Scrum, as used in agile software development, and the Data Vault 2.0 methodology, which is based on Scrum but also includes aspects from other methodologies. Other functions of Azure DevOps, for example the deployment of the data analytics platform, will be discussed in subsequent articles of this ongoing blog series.
