Skip to content

Latest commit

 

History

History
38 lines (23 loc) · 2.41 KB

entity_summary.md

File metadata and controls

38 lines (23 loc) · 2.41 KB

Entity Summary


Entity summary refers to a concise and informative description of an entity/object within a dataset.
It provides an overview of the essential characteristics, attributes and features associated with the entity
It facilitates understanding, exploration and analysis of data.

Features of an entity summary:-

  1. Identification : It should clearly identify the entity being described.
  2. Attributes : It should outline the relevant attributes/variables associated with the entity.
  3. Descriptive statistics : Depending on the nature of the variables, entity summaries might include
    summary statistics such as mean, median etc.
  4. Relationships : If the entity has relationships with other entities in the dataset, the summary may highlight these connections
  5. Contextual Informaton : It can include additional contexxt or metadata relevant to the entity
  6. Visualizations : visual representations are used to illustrate important aspects of the variable

Gathering Business Insights


Gathering Business Insights is a cucial aspect that involves extracting valuable information and knowledge from data to drive informed decision-making and strategic planning with an organization.

  1. Define your objectives : Clearly articulate the specific business questions or problems you aim to address through data analysis. This will guide your exploratory data analysis towards obtaining relevant insights.

  2. Identify and gather relevant data : Determine the data sources that are required to answer your business questions.

  3. Clean and preprocess the data : Data cleaning is essential to handle missing values, outliers, inconsisteces and format inconsistencies.

  4. Explore and visualize the data : Use exploratory data analysis techniques to gain a deeper understanding of the data

  5. Apply statistical and analytical techniques : utilize appropriate and analytical methods to extract insights from the data

  6. Interpret the results : Analyze the output from your statistical models/ analysis and interpret the findings in the context of your business objectives.

  7. Communicate and visualize the insights : Present your insights in clear, concise and visually appealing manner to make them easily understandable by stakeholders.

  8. Validate and Iterate: Continuously validate your insights against real-world observations and feedback from stakeholders