UNIT 1 Lesson1_What is Data Analytics

Data

Raw, unorganized facts that need to be processed.

Data Analysis

A process that involves collecting, organizing, and summarizing raw data to extract meaningful information.

Data Analytics

A broader field that includes data analysis and uses tools and methodologies to collect, clean, process, and analyze data.

Insight

Meaningful conclusions derived from data analysis that guide decision-making.

Collecting

The act of gathering data from various sources.

Organizing

Structuring data in a manageable format.

Summarizing

Condensing data to highlight the most important aspects.

Predictive Modeling

A technique in data analytics used to forecast future outcomes based on historical data.

Descriptive Analytics

A form of data analysis that describes what has happened in the past.

Diagnostic Analytics

Analyzes historical data to understand reasons behind past outcomes.

Prescriptive Analytics

Offers recommendations on what actions to take based on the analysis.

Data Visualization

The representation of data in graphical formats to easily convey insights.

Tools for Data Analysis

Includes software such as Excel, SPSS, R, and Python.

Tools for Data Analytics

Includes advanced platforms like Tableau, Power BI, Hadoop, and cloud services.

Correlation Analysis

A statistical method used to determine the relationship between two variables.

Hypothesis Testing

A method for testing a hypothesis to determine if there is enough evidence to reject it.

Machine Learning

A technique that enables computers to learn from data and make predictions.

Actionable Insights

Insights derived from data that can lead to direct actions or decisions.

Decision Making

The process of making choices based on data insights.

Trends

Patterns observed in data over time that can indicate future developments.

Statistical Functions

Mathematical functions used to describe and analyze data.