Microsoft provides several technologies in and around SQL Server which can be used for casual to serious data science. This presentation provides an authoritative overview of five major options: SQL Server Analysis Services, Excel Add-in for SSAS, Semantic Search, Microsoft Azure Machine Learning, and F#. Also included are tips on working with Python and R. These technologies have been used by the presenter in various companies and industries. This deck includes a sneak preview for SQL Server 2016.
4. Vision Analytics
Recommenda-
tion engines
Advertising
analysis
Weather
forecasting for
business planning
Social network
analysis
Legal
discovery and
document
archiving
Pricing analysis
Fraud
detection
Churn
analysis
Equipment
monitoring
Location-based
tracking and
services
Personalized
Insurance
Machine learning &
predictive analytics are core
capabilities that are needed
throughout your business
15. Magic Quadrant
for Business
Intelligence and
Analytics Platforms
Retrieved from http://www.microstrategy.com/us/about-us/analyst-reviews/gartner-magic-
quadrant
38. Full Text Keyword Index “FTI”
Semantic Key Phrase Index –
Tag Index “TI”
Semantic Document
Similarity Index “DSI”
http://msdn.microsoft.com/en-
us/library/gg492085.aspx#SemanticIndexing
48. Difference in Proportions Test
Lexicon Based Sentiment Analysis
Forecasting-Exponential Smoothing
Forecasting - ETS+STL
Forecasting-AutoRegressive Integrated
Moving Average (ARIMA)
Normal Distribution Quantile Calculator
Normal Distribution Probability Calculator
Normal Distribution Generator
Binomial Distribution Probability Calculator
Binomial Distribution Quantile Calculator
Binomial Distribution Generator
Multivariate Linear Regression
Survival Analysis
Binary Classifier
Cluster Model
datamarket.azure.com