Data Fluency - Data Skills

Topics covered

• define concepts essential to data science like dataset, database, data analytics, data aggregation, and time series
• define the relationship between big data and the value of data analytics
• describe how to add structure to raw data and name big data tools that aid this process
• describe the concept of big data and the history behind it
• describe the process of deciphering correlations, market trends, patterns
• distinguish between raw data, information, applicable knowledge, and general wisdom
• identify the benefits of big data to organizations
• identify the emerging trends in data analytics and their roles across industries
• identify the key elements of the actionable insight formula
• identify the right questions to ask to narrow down the problem
• identify the steps to create an initial problem statement
• identify the steps you take to ensure your decision making is data driven
• name the components and benefits of data governance
• outline the purpose and components of the data analytics maturity model
• recognize the benefits of building your analytics literacy
• recognize the importance of data visualization and reporting and tools commonly used for the same
• recognize the key activities for refining and finalizing problem statements
• recognize the key characteristics of big data
• recognize the purpose of using data collaboration and visualization tools
• recognize the steps for testing and validating assumptions