Data Management and Visualization
Data management and visualization are essential tools for businesses of all sizes to gain insights and make informed decisions. By leveraging data, organizations can optimize operations, increase efficiency, and gain a competitive edge. ▼
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Course Feature
Cost:
Free
Provider:
Coursera
Certificate:
No Information
Language:
English
Start Date:
Self Paced
Course Overview
❗The content presented here is sourced directly from Coursera platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [March 06th, 2023]
This course, Data Management and Visualization, provides an overview of the steps in data analysis. It begins by exploring what is meant by data and how to interpret datasets and codebooks. Students will then learn how to develop a research question and use data to answer it. Finally, the course will cover how to visualize data in order to effectively communicate results.
[Applications]
After this course, participants can apply the concepts learned to their own data analysis projects. They can use the steps in data analysis to develop a research question and create datasets and codebooks. They can also use the data to create visualizations to better understand the data and draw conclusions.
[Career Paths]
1. Data Analyst: Data Analysts are responsible for collecting, organizing, and analyzing data to help inform business decisions. They use a variety of tools and techniques to identify trends and patterns in data, and then present their findings in a meaningful way. As the demand for data-driven decision making increases, the need for Data Analysts is expected to grow.
2. Data Scientist: Data Scientists are responsible for extracting insights from large datasets. They use a variety of techniques, such as machine learning, to uncover patterns and trends in data. They also develop predictive models to help organizations make better decisions. The demand for Data Scientists is expected to continue to grow as organizations become increasingly data-driven.
3. Business Intelligence Analyst: Business Intelligence Analysts are responsible for collecting, organizing, and analyzing data to help inform business decisions. They use a variety of tools and techniques to identify trends and patterns in data, and then present their findings in a meaningful way. As the demand for data-driven decision making increases, the need for Business Intelligence Analysts is expected to grow.
4. Data Visualization Specialist: Data Visualization Specialists are responsible for creating visual representations of data to help organizations better understand their data. They use a variety of tools and techniques to create interactive visualizations that can be used to explore data and uncover insights. As organizations become increasingly data-driven, the demand for Data Visualization Specialists is expected to grow.
[Education Paths]
1. Bachelor of Science in Data Science: This degree path focuses on the development of skills in data analysis, data management, and data visualization. Students will learn how to use various software tools to analyze data, create visualizations, and develop predictive models. Additionally, they will gain an understanding of the ethical implications of data management and analysis. This degree path is becoming increasingly popular as businesses and organizations rely more heavily on data-driven decisions.
2. Master of Science in Business Analytics: This degree path focuses on the application of data analysis and visualization techniques to business problems. Students will learn how to use data to inform decisions, develop strategies, and optimize operations. They will also gain an understanding of the ethical implications of data management and analysis. This degree path is becoming increasingly popular as businesses and organizations rely more heavily on data-driven decisions.
3. Master of Science in Data Science: This degree path focuses on the development of skills in data analysis, data management, and data visualization. Students will learn how to use various software tools to analyze data, create visualizations, and develop predictive models. Additionally, they will gain an understanding of the ethical implications of data management and analysis. This degree path is becoming increasingly popular as businesses and organizations rely more heavily on data-driven decisions.
4. Doctor of Philosophy in Data Science: This degree path focuses on the development of advanced skills in data analysis, data management, and data visualization. Students will learn how to use various software tools to analyze data, create visualizations, and develop predictive models. Additionally, they will gain an understanding of the ethical implications of data management and analysis. This degree path is becoming increasingly popular as businesses and organizations rely more heavily on data-driven decisions.
Course Syllabus
Defining exploratory data analysis
SAS coding conventions
Running your program and examining frequency distribution
Refining your research question by selecting rows
Defining Exploratory Data Analysis
Python Coding Conventions
Running your program and examining frequency distributions
Refining your research question by selecting rows
Pros & Cons
Clear and straightforward content
Conceptually sound
Excellent slides and instructions
Limited student feedback
Too basic
Unfamiliar with process
Course Provider
Provider Coursera's Stats at AZClass
Discussion and Reviews
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Quiz
Submitted Sucessfully
1. What do we mean by data?
2. What is a codebook?
3. What is the first step in data analysis?
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