Data Analysis Boot Camp Classroom Live Boston, MA December 16, 2019

Price: $1,900

This course runs for a duration of 3 Days.

The class will run daily from 8:30 am EST to 4:30 pm EST.

Class Location: Boston, MA - Boston, MA.

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Description

Every day buzzwords like "analytics," "insights" and "big data," permeate the pages of our business journals. Companies and departments are well aware of their huge troves of data, and they have access to common tools for leveraging this data. However, much less available are the actual analysis skills to truly understand and realize the benefits of this information. The potential is very real, but comprehensive skills can be scarce, and outside consultants are expensive. If you have basic familiarity with Excel, this three-day course can teach you practical applied analysis techniques to leverage data for relatively common decision making methods.

This course, organized into key topic areas, leverages straightforward business examples to explain practical techniques for understanding and reviewing data quality and how to translate data into analysis of business problems to begin making informed, intelligent decisions. Get an overview of data quality and data management, followed by foundational analysis and statistical techniques. Throughout the course, you will learn to communicate about data and findings to stakeholders who need to quickly make the decisions that drive your organization forward.

At the end of the class, we provide an overview of the Certified Analytics Professional certification. We discuss business applications for professionals with the certification, the main focus areas behind the certification, test-preparation and test-taking anecdotes.

In–Class Exercises, Demos, and Real-World Case Studies

This data analysis training class is a lively blend of expert instruction combined with hands-on exercises so you can practice new skills. Leave prepared to start performing practical analysis techniques the moment you return to work. Every Data Analysis Boot Camp instructor is a veteran consultant and data guru who will guide you through effective best practices and easily-accessible technologies for working with your data. Through a combination of demonstrations and hands-on practice, you will learn to use data analysis techniques which are typically the domain of expensive consultants.

  • Identify opportunities, manage change and develop deep visibility into your organization
  • Understand the terminology and jargon of analytics, business intelligence and statistics
  • Learn a wealth of practical applications for applying data analysis capability
  • Visualize both data and the results of your analysis for straightforward graphical presentation to stakeholders
  • Learn to estimate more accurately than ever, while accounting for variance, error, and Confidence Intervals
  • Practice creating a valuable array of plots and charts to reveal hidden trends and patterns in your data
  • Differentiate between "signal" and "noise" in your data
  • Understand and leverage different distribution models, and how each applies in the real world
  • Form and test hypotheses – use multiple methods to define and interpret useful predictions
  • Learn about statistical inference and drawing conclusions about the population

Who Should Attend

  • Business Analyst, Business Systems Analyst, CBAP, CCBA
  • Systems, Operations Research, Marketing, and other Analysts
  • Project Manager, Program Manager, Team Leader, PMP, CAPM
  • Data Modelers and Administrators, DBAs
  • IT Manager, Director, VP
  • Finance Manager, Director, VP
  • Operations Supervisor, Manager, Director, VP
  • Risk Managers, Operations Risk Professionals
  • Process Improvement, Audit, Internal Consultants and Staff
  • Executives exploring cost reduction and process improvement options
  • Job seekers and those who want to show dedication to process improvement
  • Senior staff who make or recommend decisions to executives

Course Overview

 

  • 1. Data Fundamentals
  • Course Overview and Level Set
    • Objectives of the class
    • Expectations for the class
  • Understanding "real-world" data
    • Unstructured vs. structured
    • Relationships
    • Outliers
    • Data growth
  • Types of Data
    • Flavors of data
    • Sources of data
    • Internal vs. external data
    • Time scope of data (lagging, current, leading)
  • LAB: Getting started with our classroom data 
  • Data-related Risk
    • Common identified risks
    • Effect of process on results
    • Effect of usage on results
    • Opportunity costs, Tool investment
    • Mitigating common risks
  • Data Quality
    • Cleansing
    • Duplicates
    • SSOT
    • Field standardization
    • Identifying sparsely populated fields
    • How to fix some common issues
  • LAB: Data Quality
  • Relationships
    • Finding common attributes
    • 1:N, N:N, 1:1
  • LAB: Relationships in a dataset
  • 2. Analysis Foundations
  • Statistical Practices: Overview
    • Comparing programs and tools
    • Words in English vs. data
    • Concepts specific to data analysis
  • Domains of data analysis
    • Descriptive statistics
    • Inferential statistics
    • Analytical mindset
    • Describing and solving problems
  • 3. Analyzing Data
  • Averages in data
    • Mean
    • Median
    • Mode
    • Range
  • Central Tendency
    • Variance
    • Standard deviation
    • Sigma values
    • Percentiles
    • Using these concepts to estimate things
  • LAB: Hands-On – Central Tendency
  • LAB: Hands-On – Linear Regression
  • Overview of commonly useful distributions
    • Probability distribution
    • Cumulative distribution
    • Bimodal distributions
    • Skewness of data
    • Pareto distribution
  • Correlation
  • LAB: Distributions
  • Analytical Graphics for Data
    • Categorical – bar charts
    • Continuous – histograms
    • Time series – line charts
    • Bivariate data – scatter plots
    • Distribution – box plot
  • 4. Analytics & Modeling
  • ROI & Financial Decisions
  • Common uses of financial data
    • Earned Value
    • Actual Cost, BAC and EAC
    • Expected Monetary Value
    • Cost Performance/Schedule Performance Index
  • Common uses for random numbers
    • Sampling
    • Simulation
    • Monte Carlo analysis
    • Pseudo-random sequences
  • Demo / Lab – Random numbers in Excel
  • An introduction to Predictive Analytics
    • A discussion about patterns
    • Regression and time series for prediction
    • Machine learning basics
    • Tools for predictive analytics
  • Demo / Lab – Getting started with R
  • Understanding Clustering
    • Segmentation
    • Common algorithms
    • K-MEANS
    • PAM
  • Fundamentals of Data Modeling
    • Architecture and analysis
    • Stages of a data model
    • Data warehousing
    • Top-down vs. Bottom-up
  • Understanding Data Warehousing
    • Context tables
    • Facts
    • Dimensions
    • Star vs. Snowflake Schema
  • 5. Visualizing & Presenting Data
  • Goals of Visualization
    • Communication and Narrative
    • Decision enablement
    • Critical characteristics
  • Visualization Essentials
    • Users and stakeholders
    • Stakeholder cheat sheet
    • Common missteps
  • Communicating Data-Driven Knowledge
    • Alerting and trending
    • To self-serve or not
    • Formats & presentation tools
    • Design considerations

Prerequisites

If you have basic familiarity with Excel, this three-day course can teach you practical applied analysis techniques to leverage data for relatively common decision making methods.

Other Available Dates for this Course

Classroom Live
April 22, 2019

Austin, TX
$1,900.00
3 Days    8:30 am CST - 4:30 pm CST
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Virtual Classroom Live
April 22, 2019

$1,900.00
3 Days    8:30 am CST - 4:30 pm CST
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Classroom Live
April 29, 2019

Columbia, MD
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3 Days    8:30 am EST - 4:30 pm EST
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Classroom Live
May 20, 2019

Sacramento, CA
$1,900.00
3 Days    8:30 am PST - 4:30 pm PST
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Virtual Classroom Live
May 20, 2019

$1,900.00
3 Days    8:30 am PST - 4:30 pm PST
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Classroom Live
May 29, 2019

Omaha, NE
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3 Days    8:30 am CST - 4:30 pm CST
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Classroom Live
June 17, 2019

Chicago, IL
$1,900.00
3 Days    8:30 am CST - 4:30 pm CST
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Virtual Classroom Live
June 17, 2019

$1,900.00
3 Days    8:30 am CST - 4:30 pm CST
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Classroom Live
June 24, 2019

Dallas, TX
$1,900.00
3 Days    8:30 am CST - 4:30 pm CST
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Classroom Live
July 22, 2019

Reston, VA
$1,900.00
3 Days    8:30 am EST - 4:30 pm EST
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Virtual Classroom Live
July 22, 2019

$1,900.00
3 Days    8:30 am EST - 4:30 pm EST
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Classroom Live
July 29, 2019

Seattle , WA
$1,900.00
3 Days    8:30 am PST - 4:30 pm PST
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Classroom Live
August 19, 2019

Minneapolis, MN
$1,900.00
3 Days    8:30 am CST - 4:30 pm CST
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Virtual Classroom Live
August 19, 2019

$1,900.00
3 Days    8:30 am CST - 4:30 pm CST
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Classroom Live
August 26, 2019

San Diego, CA
$1,900.00
3 Days    8:30 am PST - 4:30 pm PST
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Classroom Live
September 09, 2019

Philadelphia, PA
$1,900.00
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Virtual Classroom Live
September 09, 2019

$1,900.00
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Classroom Live
September 16, 2019

Kansas City, KS
$1,900.00
3 Days    8:30 am CST - 4:30 pm CST
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Classroom Live
September 23, 2019

Raleigh, NC
$1,900.00
3 Days    8:30 am EST - 4:30 pm EST
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Virtual Classroom Live
September 23, 2019

$1,900.00
3 Days    8:30 am EST - 4:30 pm EST
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Classroom Live
October 02, 2019

Austin, TX
$1,900.00
3 Days    8:30 am CST - 4:30 pm CST
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Virtual Classroom Live
October 02, 2019

$1,900.00
3 Days    8:30 am CST - 4:30 pm CST
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Classroom Live
October 21, 2019

Chicago, IL
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3 Days    8:30 am CST - 4:30 pm CST
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Classroom Live
October 28, 2019

Jacksonville, FL
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Virtual Classroom Live
October 28, 2019

$1,900.00
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Classroom Live
November 04, 2019

San Jose, CA
$1,900.00
3 Days    8:30 am PST - 4:30 pm PST
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Classroom Live
November 11, 2019

Phoenix, AZ
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3 Days    8:30 am PST - 4:30 pm PST
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Virtual Classroom Live
November 11, 2019

$1,900.00
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Classroom Live
November 18, 2019

Columbia, MD
$1,900.00
3 Days    8:30 am EST - 4:30 pm EST
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Classroom Live
December 09, 2019

Houston, TX
$1,900.00
3 Days    8:30 am CST - 4:30 pm CST
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Virtual Classroom Live
December 09, 2019

$1,900.00
3 Days    8:30 am CST - 4:30 pm CST
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