PROCESS OF DATA SCIENCE

Slide Content

The slide depicts the various stages in data science leading to business application. Starting with "Gathering Data," which involves the collection of raw data from various sources. "Preparing Data" signifies the process of cleaning and organizing data for analysis. Then, "Data Analysis" refers to the examination and processing of data to extract useful information. "Predictive Analysis" is about using data to forecast future trends and outcomes. "Knowledge Extraction" involves deriving insights and patterns from the analyzed data. The final step, "Data Visualization," is about representing data in visual formats like charts or graphs. All these steps flow toward "Business Application," suggesting the practical implementation of data insights.

Graphical Look

• The background is a solid red.
• The title "PROCESS OF DATA SCIENCE" is displayed at the top in white font.
• Six white rounded cards, each with a shadow effect, representing different steps in the data science process.
• Each card contains an icon and a label in black, describing a phase of the process.
• Icons include database symbols, gears, graphs, and more abstract designs representing their respective phases.
• Arrows connect the cards, suggesting a sequential flow from one step to the next.
• On the right, a large briefcase icon with a downward arrow signifies the culmination into "Business Application."
• The slide uses a bold and minimalistic icon design, with a limited color palette mainly consisting of white, black, and shades of red.

The overall look is modern and clean, emphasizing process flow with a strong visual hierarchy that leads the viewer's eye from left to right, culminating in the practical application of data science in business.

Use Cases

• To explain the data science workflow in educational settings or data science courses.
• In business presentations to illustrate how data is converted into actionable insights.
• As part of a proposal for data analysis services to potential clients to outline the methodology.
• During internal company meetings to discuss data management strategies and improve decision-making processes based on data analysis.