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Introduction to Data Analytics
Coursera
Course
Unknown

Introduction to Data Analytics

Meta

This course offers a practical framework for basic analytics tasks including data extraction, cleaning, manipulation, and analysis, introducing the OSEMN cycle for managing analytics projects.

Unknown5 weeksKK, German, HI, PS

About this Course

This course provides a practical understanding and framework for basic analytics tasks, including data extraction, cleaning, manipulation, and analysis. It introduces the OSEMN cycle for managing analytics projects and you'll examine real-world examples of how companies use data insights to improve decision-making. By the end of this course you will be able to: • Formulate business goals, KPIs and associated metrics • Apply a data analysis process using the OSEMN framework • Identify and define the relevant data to be collected for marketing • Compare and contrast various data formats and their applications across different scenarios • Identify data gaps and articulate the strengths and weaknesses of collected data You don't need marketing or data analysis experience, but should have basic internet navigation skills and be eager to participate. Ideally you have already completed course 1: Marketing Analytics Foundation in this program

What You'll Learn

  • Apply the OSEMN data analysis process to marketing data
  • Compare and contrast various data formats and their applications
  • Identify data gaps and assess strengths and weaknesses of collected data

Prerequisites

  • Basic computer and internet skills
  • Ability to read course instructions in English and complete practice activities

Instructors

A

Anke Audenaert

CEO & Co-Founder Aptly, Adj. Professor, UCLA Anderson School of Management

Topics

Marketing
Business
Data Analysis
Data Science
Data Visualization
Business Metrics
Business Analysis
Data Quality
Data Presentation
Analytics

Course Info

PlatformCoursera
LevelUnknown
PacingUnknown
PriceFree

Skills

التسويق
الأعمال
تحليل البيانات
علوم البيانات
تصوير البيانات
مؤشرات الأعمال
تحليل الأعمال
جودة البيانات
Data Presentation
Analytics

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