A Day of Data Science with SQL Server, Azure ML, Spark, Hadoop, and R

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Hello Dear Reader!  Next week in Jacksonville, Friday August 11th,  I will be presenting a Day of Data Science: With SQL Server 2016/2017, Azure ML, Spark, Hadoop, & R.  We will also be working in some Power BI, and may even be building something like what you see on the page.  Here's the abstract.

The world of data is changing.  It used to be enough to collect data and report off of it.  ‘Business’ people would make ‘business’ decisions based off of reports, historical experience, and their gut. ‘Business’ people may go into meetings and say things like, “We will change our business and stop doing A.  We used to do A, and we got profit!  Now we do A, and profit is down.  Therefore we stop doing A, and now we will do B!”  They may have data to back up their decision, they may not have data.  Sometimes they got it wrong, sometime they got it right.  One day someone figured out that they could use math and science to calculate the odds of making a good decision.  In Las Vegas they call it gambling, in the business world we call it Data Science.  Data Science is not some mysterious solution that fixes everything.  It is the process of using a series of calculations to make many micro-informed-decision.  This leads to informed decision making.  Those calculations are what we would call models, and they store the algorithm that we will use to calculate our odds.  There are many different ways to create, store, and utilize models.  In this pre-con we will discuss some of the architectures and ways this can be accomplished.  We will then focus on the newest advanced analytics capabilities in SQL Server and in R to discuss on premise architectures.  Including the advantages to storing data and models in SQL Server as well as how to use Predictive and Prescriptive analytics.  We will then end the day shifting our focus to the cloud with an end to end Lab focusing on Azure ML, Spark, Hadoop, Power BI, and Modern Applications.
*Note to participate in the Lab you will need access to Microsoft Azure and an Azure account.

What does the agenda look like?
8:30 AM – Speaker & Course Introductions
8:45 AM – Data Science concepts
9:45 AM – Begin Introduction to R – Using Baseball Analytics
10:00 AM – Break
10:10 AM – Continue Introduction To R
11:00 AM – R and SQL Server 2016/2017
12:00 PM – Lunch
1:00 PM – Azure ML Overview
2:00 PM – Begin Hands on Lab Walk Through
4:30 PM – End of Class
Will I live blog it like last year?  Only time will tell Dear Reader, only time will tell.
As always Thanks for stopping by, and I hope to see you there!!
Thanks,
Brad

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