Data Private

Foundations of Data Analysis (DATA101)

2 days

Data

A hands-on introduction to the data analysis lifecycle, from framing the right question through data collection, quality assessment, and exploratory analysis.

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Course Overview

A hands-on introduction to the complete data analysis lifecycle, from framing the right business question through data collection, quality assessment, and exploratory analysis. Designed for professionals who want a structured, methodical approach to working with data. Topics include the four pillars of analytics (descriptive, diagnostic, predictive, and prescriptive), basic statistical concepts, data quality assessment, and an introduction to common analysis tools.

Course Benefits

Describe the four pillars of analytics (descriptive, diagnostic, predictive, and prescriptive) and determine which approach best fits a given organizational question.
Distinguish between primary and secondary data sources and evaluate the reliability of each using structured assessment criteria.
Navigate and perform initial exploration of datasets using Excel, SQL, or R to assess structure, quality, and analytical potential.
Calculate and interpret basic descriptive and inferential statistics, including measures of central tendency, variability, and simple hypothesis tests.
Identify common data quality issues such as missing values, duplicates, and bias, and recommend appropriate remediation strategies.
Articulate ethical principles for responsible data collection, analysis, and reporting in organizational settings.

Delivery Methods

Private Class
Delivered for your team at your site or online.

Class Materials

Each student receives a comprehensive set of materials, including course notes and all class examples.

Class Prerequisites

Experience in the following would be useful for this Data class:

No prior analytics or programming experience required. Basic computer literacy and basic knowledge of Excel assumed.

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