Analytics Master Class-more exotic patterns in data
2016TL; DR
Analytics is all about having a good set of analytical tools. Last year at Sqlbits I outlined 4 such tools, this session will expand on that set. We’ll cover Dark Data, Probability calculations, RFI
Session Details
The analysis of raw data requires us to find and
understand complex patterns in that data.
We all have a toolbox of techniques and methodologies that we use; the
more tools we have, the better we are at the job of analysis. Some of these tools are well known, data
mining for example. This talk covers some of the less well-known techniques
that are still directly applicable to this kind of analytics.
Last year at Sqlbits I gave a two hour session on four
such topics:
- Monte Carlo simulations (MCS)
- Nyquist’s Theorem
- Benford’s Law
- Simpson’s paradox
- Dark Data
- Probability calculations
- RFI
3 things you'll get out of this session
Speakers
Mark Whitehorn's previous sessions
Graph databases - What, how and why
Graph databases – Origins, how they work, strengths and weaknesses
Inside the classic machine learning algorithms
Algorithms like Neural Nets, Deep Learning, SVM and KNN are dominating the Machine Learning world. You don’t need to know the maths behind them but you do need to know how they work in order to use them effectively. This talk will explain just that.
Evaluating Models: Get Ready to ROC
Introducing the ROC curve and its use in Azure ML.
Analytics Master Class-exploiting exotic patterns in data
There are some little-known but very useful ways of extracting information from data.
This session will cover:
• Monte Carlo simulations
• Nyquist’s Theorem
• Simpson’s paradox
• Benford’s Law
These will rock your world (they certainly rocked mine).
MDX and DAX-compare and contrast
This talk looks at MDX and DAX, examining their similarities and differences. It won’t turn you into an expert in either but it will help you to decide, given your particular career plans, if either or both are worth learning.