A little bit of knowledge about how SQL Server works can go a long way towards making large data engineering queries run faster.
Businesses today require real-time information to make better-informed decisions, this requires a new set of tools. In this session you will learn about Azure Stream analytics and how it can help address real-time data scenarios
If you are a DBA and want to get started with Data Science, then this session is for you. This demo-packed session will show you an end-to-end Data Science project covering the core technologies in Microsoft Data + AI stack.
We will showcase the latest feature of SSIS 2017 such as connectors for Azure Data Lake Store (ADLS), Azure SQL Data Warehouse (SQL DW), SSIS Scale-Out at package level for the box product as well as the SSIS package execution on Azure Data Factory
This session takes a closer look at Azure Stream Analytics, and how you can make it work in your Projects.
Selecting the right PaaS components in Azure
Common performance issues with clustered columnstore index experienced by customers and strategies to address them.
See the Magic of high-end analytics on any device, on any data source, using any database. Built in machine learning makes sophisticated analytics simple. Collaborate across the enterprise with easy implementation and real self-service analytics.
Deep learning is an essential component of an analytical toolbox. There are considerable challenges in training deep learning models and this presentation explores how to overcome these using Microsoft’s scalable ML offering, Azure Batch AI.
Text analysis of financial documents using R & Power BI.
I walk through the database services in Azure and how to characterize a workload to make the right DBaaS selection for your use case.