Enabling Real-Time Data Warehousing for Modern Analytics with Azure
In this video, you’ll learn how to enable real-time data warehousing for modern analytics through Streaming Integration with Striim to Azure SQL Data Warehouse.
This demonstration shows how Striim can provide continuous data integration into Azure SQL Data Warehouse, via Azure Data Lake Store through a pipeline for the ingestion, storage, preparation and serving of enterprise data.
To learn more about Striim for Microsoft Azure, visit our Azure partner page.
Enabling real-time data warehousing for modern analytics through streaming integration with Striim to Azure SQL Data Warehouse. Azure SQL Data Warehouse provides a fully managed, fast, flexible, and scalable cloud analytics platform. It enables massively parallel processing and elasticity working with the Azure data lake store and others who are services to load raw and process data. However much of your data may currently be elsewhere locked up on-premise or a variety of clouds in Oracle Exadata, Teradata, Amazon Redshift, operational databases and other locations, and you want to continuously integrate data into Azure Cloud analytics so you’re always acting on current information. You need a new hybrid cloud integration strategy for the continuous movement of enterprise data to from and between clouds providing continuous ingestion, storage preparation and serving of enterprise data in real-time, not batch data from on-premise and cloud sources needs to be delivered into multiple Azure endpoints including a onetime load and continuous change delivery within flight processing to ensure up to the second information for analytics Striim is a next-generation streaming integration and intelligence platform that supports your hybrid cloud initiatives, and has integration with multiple Azure Cloud technologies. We will demonstrate how Striim can provide continuous data integration into Azure SQL Data Warehouse via Azure Data Lake Store through a pipeline for the ingestion, storage, preparation, and serving of enterprise data.
Ingest – Striim makes it easy to continuously and non-intrusively ingest all your enterprise data from a variety of sources in real time. In this case, Striim will collect live transactions from Oracle Exadata orders table.
Store – Striim can continuously deliver data to a variety of Azure targets including the Azure Data Lake Storage. Striim can be used to preprocess your data in real time as it has been delivered into the store to speed downstream activities.
Prep and Train – Azure Databricks uses the data that Striim writes to a data lake store for machine learning and transformation. Results can be loaded into Azure SQL Data Warehouse and a machine learning model could be used by Striim for live scoring
Model and Serve – Striim orchestrates the process to ensure a fast, reliable, and scalable polybase delivery to Azure SQL Data Warehouse from Azure data lake store enabling analytics applications to always be up to date.
You have seen how Striim can enable your hybrid cloud initiatives and accelerate the adoption of Azure SQL Data Warehouse for flexible and scalable cloud analytics. Get started with Striim now using a trial download on our website and Striim integration offerings in the Azure marketplace.