๐ Data science is the field of study that involves extracting knowledge and insights from noisy data and turning them into actions for businesses or organizations.
๐ค Data science is the intersection of computer science, mathematics, and another important discipline.
๐ Data science is the intersection of business expertise, math, and programming.
๐ There are different types of data science methods based on the complexity and value of the questions asked.
๐ Descriptive analytics focuses on understanding what is happening in a business through accurate data collection.
๐ Diagnostic analytics: understanding why sales go up or down.
๐ฎ Predictive analytics: using historical patterns to predict future sales performance.
๐ Prescriptive analytics: recommending actions to achieve specific outcomes.
๐ Data science starts with business understanding and asking the right questions.
๐ป Data mining is the process of procuring relevant data for analysis.
๐งน Data cleaning is necessary before further analysis and interpretation.
๐ก Data preparation and cleaning are necessary before analysis.
๐ Exploration involves using analytical tools to answer questions.
๐ Advanced analytics, such as machine learning, enable predictive and prescriptive actions.
๐ Data visualization is important for communicating insights.
๐ There are different roles in the data science lifecycle, including business analysts, data engineers, and data scientists.
๐ก Data scientists contribute to exploring and applying advanced machine learning techniques.
๐ Collaboration is critical in data science as there is overlap between different roles.
๐ The data science life cycle helps transform noisy data into actionable insights.
๐ Visualization is important in understanding and analyzing data.
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