Commit 158ba9b6 authored by Carp's avatar Carp

Updates NonBookContent/

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1. Why you should care?
* This will cover the traditional data scientist/DBA impedence mismatch and how the product solves this.
* History of R, SQL Server, RevoR, and integration
c. Security
d. Performance
2. Basic Data Science terms/overview
a. Supervised/unsupervised
b. Features, labels, feature engineering, overfitting etc
3. Installation recipes
a. this is a bit tricky so let’s have a chapter that reviews it.
b. Let’s do some pre-installation planning. You probably don’t want to install this on your prod reporting server or OLTP instance
c. Some quick query recipes to ensure everything is working.
4. Basic querying recipes
a. We show the template recipe that the DBA needs to use
b. We show the data scientist what the data contract recipes need to be
c. We show recipes for using inputs/outputs, R specific code, data type conversion recipes
5. Software Development Lifecycle Recipes
a. Recipe for how a data scientist should begin their data science journey
b. R code that needs to change under RevoR
c. Recipe for how to begin integrating directly with a stored procedure
d. Recipe for how to continue to do using iterative CRISP-DM
6. Performance
a. When to use R and when to use SQL
b. DBA features around performance engineering
7. Real-world recipes
a. Taking a business problem and working it from start to finish using R client/RStudio, then R server/RStudio, then finally SQL Server R services.
b. We’ll monitor performance at each step of the way
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