The San Francisco Azure DataFest, sponsored in part by Menlo Technologies, is a wrap. Attendees of the sold-out event May 29 learned about new and exciting Azure advanced analytics and big data technologies, including:

SQL Data Warehouse: A cloud-based Enterprise Data Warehouse (EDW) that leverages Massively Parallel Processing (MPP) to quickly run complex queries across petabytes of data.

Event Hubs: A highly scalable data streaming platform and event ingestion service, capable of receiving and processing millions of events per second. Event Hubs can process and store events, data, or telemetry produced by distributed software and devices. Data sent to an event hub can be transformed and stored using any real-time analytics provider or batching/storage adapters.

Azure Data Lake Store: An enterprise-wide hyper-scale repository for big data analytic workloads. Azure Data Lake enables you to capture data of any size, type, and ingestion speed in one single place for operational and exploratory analytics.

Azure Cosmos DB: Microsoft’s globally distributed, multi-model database. With the click of a button, Azure Cosmos DB enables you to elastically and independently scale throughput and storage across any number of Azure’s geographic regions. It offers throughput, latency, availability, and consistency guarantees with comprehensive service level agreements (SLAs), something no other database service can offer.

More in-depth information about the above in future blogs.

The Menlo break-out session

The event was kicked off by Corey Sanders the Head of Product for Azure Compute at Microsoft and was followed by speakers from Microsoft and Microsoft partners, including Menlo Technologies.

Dave Hickman, VP of Global delivery, and Mani, Harihara, CTO, conducted a fantastic breakout session about Menlo’s Azure Application Development projects that included demos, discussions, and papers describing the work in Azure Development, Analytics, Machine Learning, and IoT. Highlights of the breakout session:

Azure Functions: A case study showing how Menlo used Azure Functions to receive real time data from all POS systems at Vintners Loop, a chain of convenience stores, (90k transactions per day) and ingest into a database. Menlo Technologies created a web application to enable the staff of Vintners Loop to filter transactions stored on the Azure database to identify faulty transactions. Vintners Loop will use this system to improve theft prevention.

Cortana: Menlo showed a demo of a custom solution that was built for Azure Datafest where Cortana responded to questions about the event, such as schedule, speakers, etc.

Image and Face Recognition: With Azure’s cloud-based Computer Vision API, Menlo produced a demo showing how developers can access advanced algorithms for processing images and returning information. Menlo developed POC’s for facial recognition on a photo and developed unique bar code recognition.

Azure Log Analytics: Menlo demonstrated the central role of Azure Log Analytics in data management and how Log Analytics provides insights into the operation of applications and resources:

AzureSQL and Syncing:  A Travel and Hospitality’s mobile app contained a backend architecture which was problematic and constantly breaking. Menlo re-architected the application to eliminate multiple points of failure and syncing issues on AzureSQL and the Azure app services. Offline data synchronization is a client/server SDK feature of Azure Mobile Apps that allows for syncing and offline mobile features needed in many mobile apps. Menlo eliminated the syncing issues and significantly reduced the complexity of the architecture.

And finally, no Azure presentation would be complete without a Power BI Visualization. 

Menlo Technologies looks forward to incorporating these new technologies into solutions going forward.

Learn more about Azure from Menlo Technologies.