Analytics Best Practices:
A One Day Course
Using Clouds to Provide
Scalable and On-Demand Analytics
Future Courses
We'll be giving courses and tutorials in cloud computing and analytics in the Fall. If you are interested in attending a course before then, it is also possible to arrange an in-house training course or tutorial. If you are interested, please contact us.
General Information
Cloud computing doesn't yet have a standard definition, but a good
working definition is to define clouds as racks of commodity
computers that provide on-demand resources and services over a
network, usually the Internet, with the scale and the reliability of a
data center. This one day course gives a quick introduction to cloud
computing and analytics. It covers several different types of clouds,
describes what is new about cloud computing, and discusses some of the
advantages and disadvantages that clouds offer when building and
deploying analytic models. It includes three case studies, a survey
of vendors, and information about setting up your first cloud.
There are two different, but related, types of clouds: the
first category of clouds provide computing instances on demand,
while the second category of clouds provide computing capacity
on demand. Both use the same underlying hardware, but the first is
designed to scale out by providing additional computing instances,
while the second is designed to support data- or compute-intensive
applications by scaling capacity. Amazon's
EC2 and S3 services are an
example of the first type of cloud. The
Hadoop system is an example
of the second type of cloud. In this course we cover both types of clouds
and how they are best used in analytic projects.
Course Benefits
- Learn about the different types of clouds.
- Learn the benefits of using clouds for analytics.
- Learn how to structure your first analytic project using clouds.
- Learn how to speed up the development of analytic models and the deployment
of analytics into operational systems using clouds.
Who Should Attend?
- Managers and executives interested in an introduction to cloud
computing and its applications to analytics.
- Statisticians, modelers and data mining professionals interested
in learning how to do analytics using cloud computing.
- Anyone thinking about using clouds for analytics.
Course Description
This one day course will cover the following topics:
- Introduction to clouds
- Strategies for deploying analytics over clouds
- Benefits of using clouds for analytics
- What is available: Survey of cloud vendors
- Standards and the lack of standards for cloud computing
- Building your first cloud
- Case Study 1: Scoring data using analytic models
and Amazon's EC2 cloud
- Case Study 2: Identifying compromised web sites using
Hadoop
- Case Study 3: Processing financial times series using cloud
computing
Schedule
| Time | Topic |
|---|
| 8-9 am | Continental Breakfast (included) |
| 9-10 am | Introduction to Clouds |
| 10-11 am | Strategies for Deploying Analytics Over Clouds |
| 11-12 pm | What is Available? A Vendor Survey |
| 12-1 pm | Lunch (included) |
| 1-2 pm | Case Study 1:
Scoring Data Using Amazon: A Case Study in Data Quality |
| 2-3 pm | Case Study 2:
Identifying Compromises in Log Files Using Hadoop
|
| 3-4 pm | Your First Cloud: Building your own, using
Amazon, trying other vendors... |
| 4-5 pm | Case Study 3:
Analyzing Financial Time Series |
| 5 pm | Adjourn |
