1. This document and the information contained herein is confidential and proprietary to Allegient LLC and shall not be duplicated, used or disclosed in whole or in part for any purpose other than review. All trademarks and/or service marks contained within this document are the property of their respective owners. Allegient does not in any way warrant the use of their products and/or services offerings. WHAT IS THIS AND HOW CAN I USE IT?  2015 Allegient. All rights reserved. Warren Sifre

2. Managing Consultant at Allegient. In the IT Industry since 1998. Developed system integration solutions against many different database platforms for various applications across many industries. Passion in Solutions Architecture at both hardware and software levels. Interests in SQL Server, MongoDB, Hadoop, Python/C#/Java/Powershell and Information Security (Hacking)  2013 Allegient. All rights reserved.

3. What is Streaming Analytics? How it works? Use Cases Configuration and Dependencies SAQL Demo  2015 Allegient. All rights reserved.

4.  2013 Allegient. All rights reserved.

5. Real-Time Analytics o Many Steps in between the Source Data and the Visualization/Reporting Output. Environment Scalability o Months/Years of planning is needed to plan out equipment procurement and scale out to meet increasing demand. Resource Cost Management o Ideal configuration would require the purchasing of enough equipment to handle peak performance requirements. Although those peak requirements may only be for a few hours of any given day. Disaster Recovery Strategy o Architecting and maintaining a DR strategy where performance, RTOs, and RPOs are met can be challenging and leave the organization with a lot of underutilized resources.

6.  2015 Allegient. All rights reserved. WHAT? A way to evaluate data before it has reached its final repository destination. Why? Hours to weeks can be the time it takes for data to be transmitted, received, processed, aggregated, then visualized in the traditional Data Warehouse architecture. Business requirements have changed and the desire to glean insights from this data sooner is now becoming a requirement, not a nice to have.

7.  2015 Allegient. All rights reserved. Transmit Data Event Hub Queues data for processing Streaming Analytics Job Process and Deliver data to multiple end points Power BI Visualize real-time data stream Azure SQL Store data Data Factory Gather and process data for Predictive Analytics Process Machine Learning Predictive Analytics Processing

8.  2015 Allegient. All rights reserved.

9. Transportation o Reduce the need to pull vehicles from service for routine inspections by using sensors to determine when actual anomalies are occurring. Energy o Monitor equipment from central locations such as Wind Turbines and Power Generators, thus reducing time spent on manual/physical inspection or replacement of parts just because of time instead of actual degraded performance. Manufacturing o Monitor equipment and plant conditions for optimal performance. Medical Device o Through remote monitoring expensive replacement parts can be order closer to the end-of-life of an equipment than by a schedule. This can reduce the cost of having an overstock of parts on-hand

10.  2015 Allegient. All rights reserved. Add Input(s) o Data Stream Event Hub Blob Storage IoT Hub o Reference Data Blob Storage Add Output(s) o SQL Database o Blob Storage o Event Hub o Power BI o Table Storage o Service Bus Queue o Service Bus Topic o DocumentDB Add Query o Streaming Analytic Query Language (SAQL) - Similar to T- SQL Scale/Exception o Scale – How much processing power desired for SA Job? o Exception Handling– What is the definition of Late Data? What to do with late or out of order data? o Alerts – When do you want to receive a notification?

11.  2015 Allegient. All rights reserved. DML SELECT FROM WHERE GROUP BY HAVING CASE WHEN THEN ELSE INNER/LEFT OUTER JOIN UNION CROSS/OUTER APPLY CAST INTO ORDER BY ASC, DSC Windowing Extensions TumblingWindow HoppingWindow SlidingWindow Date and Time Functions DateName DatePart Day Month Year DateTimeFromParts DateDiff DateAdd Temporal Functions Lag IsFirst CollectTop Scaling Extensions With Partition By Over Aggregate Functions Sum Count Avg Min Max StDev StDevP Var VarP String Functions Len ConCat CharIndex Substring PatIndex

12.  2015 Allegient. All rights reserved.

13. More Information on Streaming Analytics o SAQL https://msdn.microsoft.com/en-us/library/azure/dn834998.aspx o Power BI Implementation Sample https://azure.microsoft.com/en-us/documentation/articles/stream-analytics-power-bi- dashboard/ https://azure.microsoft.com/en-us/documentation/articles/stream-analytics-power-bi- dashboard/ Azure Portal Link o Azure Portal Azure Portal Azure Storage Explorer Link o https://azurestorageexplorer.codeplex.com/ https://azurestorageexplorer.codeplex.com/  2015 Allegient. All rights reserved.

14.  2013 Allegient. All rights reserved. Warren Sifre Email: wsifre@allegient.com Twitter: @WAS_SQL LinkedIn: www.linkedin.com/in/wsifre