Understanding the Life Cycle of Data Science

Data Science Steps

• Asking: Start by posing a curious question about the world or a problem to solve.
• Hunting (Data Collection): Gather clues and observations relevant to the question, such as noting down numbers and occurrences.
• Cleaning: Organize and tidy up the collected data to ensure accuracy and clarity, removing errors and confusion.
• Exploring: Analyze and visualize the clean data to look for patterns, trends, and interesting findings.
• Modeling: Build a model to predict outcomes or explain the observations, using the patterns found in the data.
• Testing: Check whether the model’s predictions hold true by observing real-world outcomes and comparing them to expectations.
• Sharing: Communicate and present the findings, insights, and journey to others through accessible means like posters or explanations.