Exploring Data: Lessons 1 - 3

Data

Any piece of information that can be collected, analyzed, and interpreted to make decisions.

Primary Data

Data collected firsthand for a specific research purpose.

Secondary Data

Data that is collected from existing sources or studies, rather than gathered firsthand.

Quantitative Data

Numerical data; Measurable data.

Qualitative Data

Categorical data; Descriptive data that can be observed but not measured

Rigid Format

A structured and inflexible way of presenting data, typically requiring adherence to specific guidelines or templates.

Flexible Format

A flexible way of presenting data that allows for variations in structure and organization, adapting to different contexts and uses.

Structured Data

Information that is organized in a clear and defined manner. Usually rows and columns.

Unstructured Data

Any information that does not follow a predefined format.

Schema

Rules that defines the organization and structure of a database, including tables, fields, and relationships, and what type of data can be stored.

Semi-Structured Data

Data that isn't organized in a fixed format but still contains tags or labels to separate elements.

Data Overload

When volume of the data exceeds the system’s ability to handle it.

Database

Organized collection of data stored in a computer system.

Subjective Data

Information formed by a person’s beliefs or opinions. Differs from qualitative since subjective data doesn’t typically include observations.

For example, a person’s eye color has an objective value (qualitative), it’s either true or false that eyes are a certain color. However, the data itself is not numerical and can’t be measured numerically.

DBMS

A system that allows users to create, modify, and query databases while ensuring data integrity, security, and efficient data access.

What is the difference between Primary and Secondary Data?

Primary data is data that the researcher themselves collected. Secondary Data is data that is gathered from a secondary source like

How is primary data collected?

Through methods such as surveys, experiments, observations, interviews.

How is secondary data collected?

Through sources like government reports, online databases, and private business.

What is the difference between Quantitive and Qualitative Data?

Quantitive data is numerical data that can be observed and measured while Qualitative data is observed data based off of a person’s belief or opinion

What is an example of quantitive data?

“The temperature is 90 degrees Fahrenheit.”

What is an example of qualitative data?

“The food was delicious.”

What are the four V’s of Big Data?

Volume - Amount of data generated

Velocity - Speed of data being generated

Variety - Different types of data

Veracity - Accuracy, reliability, and trustworthiness of the data

What are the benefits of Data?

Informed decision making - Evidence based decision making

Enhanced operational efficiency - Identifies inefficiencies in processes

Competitive advantage - Offers insights to be able to stay ahead in an industry

Performance management - Establishes clear metrics for tracking progress

Accountability and transparency - Provides clear and accessible information

What are the different ways of classifying data?

Nature: Descriptive or Numerical

Mode of Collection: Primary or Secondary Source

Structure: Structured or Unstructured

What does it mean to classify data based on its nature?

Identifying what type of information the data represents

What is another name for qualitative data?

Categorical data

What are the pros of qualitative data?

• Rich in detail

• Provides context

What is the difference between subjective data and qualitative data?

Qualitative data doesn’t always mean subjective data. For example, a person’s eye color has an objective value, it’s either true or false that eyes are a certain color. However, the data itself is not numerical and can’t be measured numerically.

What are the pros of quantitative

• Detailed with precision

• Useful in situations where numbers help make decisions.

What does it mean to classify data based on its mode of collection?

Determining how you gather information, whether you collect data firsthand or obtain data from existing sources.

What are the pros of Primary Data?

• Can tailor your collection methods to your goal

• Can control the data’s quality

What are the cons of Primary Data?

• Well designed collection methods take time and money

What are the pros of Secondary Data?

• Saves time and effort

• Larger and more diverse collection of data

What are the cons of Secondary Data?

• Can’t tailor results

• May return irrelevant information

What is the purpose of a schema?

A schema ensures that each record follows the same format making the data consistent and predictable

What is an example of structured data?

A table. Rows and columns.

What is an example of unstructured data?

An image.

What does Semi-structured Data typically have?

Labels or tags

What is an example of Semi-structured Data?

ex:

• Project name: Photosynthesis model

• Group members: Alex, Poorvi, Michel

• Materials used: Cardboard, paint, string

HMTL code

Why do companies struggle with data overload?

They deal with a lot of data

What do databases do?

Handle large volumes of information and keeps the data easily accessible and manageable.

What are the benefits of a database?

Organizes data efficiently

Retrieves data efficiently

Keeps data secure

Supports multiple users

Scales data storage

What does a DBMS do?

Helps manage and manipulate databases. Acts as a connection between users and the database

Steps a DBMS takes for processing a request

1) User inputs a query

2) SQL ensures there aren’t any syntax or grammatical errors

3) SQL searches and filters the database for records that are true

4) SQL returns results for records that agree with your query