7/22/2018 9:21 PM BRK3270 Building a Better Data Solution: Microsoft SQL Server and Azure Data Services Joey D’Antoni Principal Consultant Denny Cherry and Associates Consulting © Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

The Old Business Process On-Premises Data Warehouse Deliver Customized Flat Files Customer Time to Value from Data = Long

New Process On-Premises DW (Moving to IaaS) 7/22/2018 9:21 PM New Process On-Premises DW (Moving to IaaS) Load Data in SQL Data Warehouse Deliver Data to SQL Database (Per Customer) Analysis Services and Power BI for analysis Much faster Time to Value from Data © Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

Tools SQL Server 2016 AlwaysOn AG

Current Problems Customers have many different requirements This leads to multiple formats and requirements Customers need help with loading data and analysis

Choosing a Solution Azure SQL Data Warehouse was appealing because of ability to pause Data is processed a couple of times daily, but not constantly SQL Database is good target because each customer can have their own login, firewall rules, and schema Azure Active Directory B2B meets security requirements SSIS was chosen for ease of use

Loading SQL Data Warehouse Core Data is on-premises (moving to Azure IaaS) Customer has great deal of experience with SSIS Large amounts of data (5+ TB) Modified DW to support delta loading process

SQL DW Load Process On-Premises SQL Server SSIS (On-Premises) Bulk Copy (BCP

SQL Data Warehouse Concept External Tables linked to Blob Storage External Data Format Defines Tables ”Real Tables” get loaded in parallel and partitioned (by hash, replicated, round-robin) Heavy use of columnstore for large fact tables

Keeping Costs Contained Data Warehouse is only run during data load process Powered down using PowerShell and Azure Automation

Loading SQL DB SSIS was chosen over Azure Data Factory In this model, costs were lower, and simplicity won the day Team’s experience played large factor in decsions

SQL DB Loading Process

SQL DB Loading Running an SSIS VM for a couple of hours a day is minimal costs SSIS jobs have minimal transformation so fewer resources needed Several jobs can be run in parallel

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7/22/2018 9:21 PM © Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.