Lesson 1: Introduction To Data Analytics PDF

UNIT 1 INTRODUCTION TO DATA ANALYTICS  LESSON 1 What is Data Analytics? What is Data?  What is Data? rank gender name raw, unorganized that data is processed, organized, need to be processed...

UNIT 1 INTRODUCTION TO DATA ANALYTICS  LESSON 1 What is Data Analytics? What is Data?  What is Data? rank gender name raw, unorganized that data is processed, organized, need to be processed structured or presented in a given grade context What is Data? synthesizing/ conclusion analyzing summarizing organizing collecting What is Data? decision making synthesizing analyzing summarizing organizing collecting  Data Analysis Data Analysis is a process that begins with the collection of raw data. This data is then organized and summarized to extract meaningful information. Through detailed analysis, patterns and insights are derived, which are synthesized into actionable conclusions that drive decisions. The progression emphasizes how data transitions from raw form to meaningful insights, ultimately enabling informed actions. Data Analysis vs Data Analytics  Data Analysis Data Analytics A broader field that encompasses data analysis but also includes the vs The process of collecting, organizing, and interpreting raw data to identify use of tools, technologies, and patterns, relationships, and trends. It methodologies to collect, clean, focuses on extracting meaningful process, and analyze data. It often insights from data for specific involves predictive modeling, purposes. machine learning, and data visualization to derive actionable insights and support decision-making. Definition  Data Analysis Data Analytics Broader in scope, encompassing descriptive, diagnostic, predictive, vs More focused and specific. Typically deals with historical data to and prescriptive analytics. Answers answer questions like "What questions like "What will happen?" happened?" or "Why did it and "What should we do?" using happen?“ advanced methods. Example: Example: Calculating average sales Analyzing average sales trends to predict future demand. Scope  Data Analysis Data Analytics vs To understand and summarize the To generate insights and forecasts current or past state of data, that can guide future strategies helping to make immediate or and long-term decision-making. retrospective decisions. Goals  Data Analysis Data Analytics vs Used in research, academic To generate insights and forecasts studies, and one-time reporting that can guide future strategies tasks. and long-term decision-making. Example: Example: Summarizing survey responses for a Analyzing survey responses to identify customer market research report. preferences Application  Data Analysis Data Analytics Techniques: Advanced statistical methods, machine learning, data vs Techniques: Descriptive statistics, correlation analysis, hypothesis mining, predictive modeling, and testing. optimization. Tools: Excel, SPSS, R (basic statistical Tools: Python, R, Tableau, Power BI, functions), Python (e.g., Pandas). SQL, Hadoop, Spark, and cloud platforms like AWS or Google Cloud. Techniques and Tools Conclusion Data Analysis vs Data Analytics Data Analysis is a subset of Data Analytics. While data analysis focuses on examining and interpreting data, data analytics takes a broader approach by using advanced tools and methods to process data, uncover trends, and predict future outcomes. Conclusion Data Analysis vs Data Analytics “Insight” “Strategy” Focuses on interpreting Encompasses the entire existing data to uncover process, including planning, patterns, trends, and insights analyzing, and predicting about what happened. outcomes, to guide future actions and decision-making. The Detective vs The Investigator The Chef vs The Restaurant Manager The Chef vs The Chef The Detective vs The Detective