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Data Analytics

Develop practical analytics competence. Learn the complete data lifecycle, exploratory analysis methods, outlier detection, and data cleaning best practices.

2 tutorials published•Updated monthly by the technical editorial team

Published Guides in Data Analytics

2 articles

Beginner8 min read

Introduction to Data Analytics: The Complete Lifecycle

Understand the core discipline of data analytics. Explore the 4 types of analysis, the 6-step analytics lifecycle, and the essential tooling ecosystem.

Key Highlights:

Distinguish between the 4 types of analytics: Descriptive, Diagnostic, Predictive, Prescriptive

Master the 6 stages of the Data Analytics Lifecycle (Ask, Prepare, Process, Analyze, Share, Act)

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Intermediate9 min read

Data Cleaning Techniques: Handling Missing Values & Outliers

Learn essential data hygiene practices. Master how to handle missing data with Pandas, detect statistical outliers with IQR, and standardize categorical values.

Key Highlights:

Understand the direct business costs of dirty data ('Garbage In, Garbage Out')

Learn strategies for handling missing values: dropping vs statistical imputation

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Applied Practice

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Reinforce what you study with our client-side utilities.

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