Data Analysis & Interpretation Flashcards
What is the first step in data analysis, and why is it important?
Defining the objectives guides the analysis and ensures a focused approach.
Why is data cleaning essential before analysis?
It removes errors, inconsistencies, and missing values, ensuring reliable results.
What techniques are used in data exploration?
Statistical summaries, visual representations, and identifying patterns, trends, and outliers.
How does data interpretation differ from data analysis?
Interpretation translates findings into meaningful insights, while analysis applies statistical methods to examine relationships and trends.
What is the purpose of data communication?
To present findings clearly to stakeholders using visualizations and reports.
What are the four types of data reports?
Operational, Analytical, Strategic, and Research reports.
How do operational reports differ from analytical reports?
Operational reports track routine activities, while analytical reports use data analysis for decision-making.
What is a strategic report used for?
To support long-term planning and decision-making using performance trends and forecasts.
What is a research report, and where is it commonly used?
It documents research methodologies, data analysis, and conclusions, often in academic and market research.
What are the four common data report formats?
Tabular, Text-based, Graphical, and Dashboard reports.
Why is a dashboard report useful?
It visually presents key performance indicators (KPIs) for quick insights
How does a graphical report improve data communication?
It uses charts, graphs, and maps to make complex data easier to understand.
How do Descriptive, Diagnostic, and Discovery Analytics differ in terms of their focus?
Descriptive Analytics: Summarizes past events (What happened?).
Diagnostic Analytics: Explains why something happened (Why did it happen?).
Discovery Analytics: Identifies unknown patterns or insights (What happened that we don’t know about?).
What is the key difference between Predictive and Prescriptive Analytics?
Predictive Analytics: Forecasts what is likely to happen using past data.
Prescriptive Analytics: Recommends the best course of action based on predictions.
Which types of analytics provide hindsight, insight, and foresight?
Hindsight → Descriptive & Diagnostic Analytics (looking at past events and causes).
Insight → Discovery Analytics (finding unknown patterns).
Foresight → Predictive & Prescriptive Analytics (forecasting future events and deciding actions).
If a retail company wants to optimize stock levels, which types of analytics should they use and why?
Predictive Analytics: To forecast demand based on past sales trends.
Prescriptive Analytics: To determine the best stocking strategy to maximize sales and minimize waste.
