Data Analysis Bootcamp - What To Expect. Damian Herrick Founder, Principal Consultant Lake Hill Analytics, LLC

Transcription

1 Data Analysis Bootcamp - What To Expect Damian Herrick Founder, Principal Consultant Lake Hill Analytics, LLC

2 Why Are Companies Using Data and Analytics Today? Data + Predictive Ability + Optimization = More Money Competitive Advantage

3 Data-Driven Matters Data allows marketers to precisely drive investment decisions about their mix. Today we can identify exactly what drives sales and profits. Adjust marketing mix model accordingly Data allows evaluation of brand performance over the long term. Separate short term effects from the long term ones that build equity.

4 Getting Started In Analytics Find greatest economic advantage and focus on solving that problem: find 2-3 things of the 22 parts of a problem, solve those first. Make a tool that the frontline customer has confidence in and will use Generate insights about growth opportunity, and focus resources there Transformation of culture to become data / analytics driven is the hardest part.

5 Capturing Value Big Data: Be creative when you source internal and external data. Design an architecture to easily merge it all. Optimize: Focus on biggest performance drivers Transform the Organization: Simple, understandable tools.

6 Based on the CRISP-DM Model Pragmatic Data Analysis Identify strategic goals, tactical needs, and existing pain points How do these goals / needs / pains affect the balance sheet? Data comes next: What data is available today? How is it stored? What additional data would be useful to you? Data collection and preparation is most timeintensive step in process Process is iterative; test and refine models prior to project completion.

7 Unique Business and Technical Experience Software Development including but not limited to: Python for data gathering and analytics R for rapid prototyping Amazon Web Services for infrastructure MySQL and PostgreSQL for database management Data Management Identify data sources Integrate multiple sources into single database Data cleansing Analytics Segmentation Regression Simulation Project Management Marketing Market Analytics Market Research New Product Development Project management Experience in varied verticals: Energy Media E-Commerce Computer Hardware / Manufacturing Real Estate Healthcare Analytics

8 Data Analysis Bootcamp Three days of data and analytics focus. Pragmatic focus tailored to your individual problems and needs Lay the foundation of data understanding and analytics Discuss how to communicate your results Introduction to advanced analysis techniques Overview of Certified Analytics Professional examination Many practical examples of successful data projects included in the instruction

9 Who is the bootcamp for? Executives looking to create a data driven environment in their companies. Managers looking to better understand their analyst professionals Professional staff looking to broaden their horizons.

10 What verticals and functions use Verticals include: Healthcare Retail Manufacturing Software development Energy Many others data? Functions include: Marketing Sales Operations Finance Human Resources

11 Analytics Techniques And Use Cases Decision Tree Modeling: Grouping and prediction Clustering: Identify similar groups in a population Logistic Regression: Predict if a record is a member of the target group Neural Networks: Find complex relationships Segmentation Customer Care Pricing Resource allocation Optimization

12 Topics in the Bootcamp Day 1 Understanding Data Looking at Data Day 2 Modeling Data Mining Data Day 3 Using Data CAP Overview

13 Exercises in the Bootcamp Several hands-on exercises will be offered in the class. Students will be introduced to multiple analytics environments: Lightweight analytics with Excel Deeper statistical analysis with R and Rstudio Basic programming and scripting introduction with Python and supporting packages.

14 Statistics: Understanding Data Dive in to the basics of statistics - the foundation of the course. For some - a review of course material in college For others - an introduction to the power of statistics. Most of Day 1 will cover this topic, including: Descriptive Statistics Distributions Probability Hypothesis testing And more!

15 Graphics: Looking at Data Analysis isn t worth much unless you can communicate it! Examination of various data visualization and communication techniques Best practices from Tufte, Few, and others. Topics include: Plotting single variables Plotting two and more variables Time series analysis And more

16 Analytics: Modeling Data Basic statistics help with day-to-day work Great for rearward looking assessments and reporting. Analytics techniques broaden horizons and allow you to begin to predict future behavior and events Start with guesstimation (yes, really!) and build toward probability based models.

17 Computation: Mining Data Build on the basics of analytics techniques to computation intensive mining. Use your data for: Simulations Clustering Attribute Analysis

18 Applications: Using Data The instructional portion of the course concludes with a discussion of how to apply data and analytics in a business production environment. Important topics include: Reporting Dashboards Financial Modeling Predictive Analytics During this portion, we will attempt to tailor the discussion to the individual needs and challenges of the students in the class.

19 CAP Overview Discuss the seven INFORMS defined analytics domains: Business Problem Framing Analytics Problem Framing Data Methodology Selection Model Building Solution Deployment Model Lifecycle The importance of soft skills for the analytics professional. Details about experiences taking the test Tips and tricks for preparing for the test.

20 Upcoming Data Analysis Bootcamps Location Philadelphia, PA Onsite Classes Dates December 8-10, 2014 Raleigh, NC January 20-22, 2015 Philadelphia, PA Atlanta, GA February 17-19, 2015 February 23-25, 2015 Virtual Classes Dates January 13-16, 2015 February 10-13, 2015 March 10-13, 2015 April 14-17, 2015