March 15, 2023

How to Extract Insights From Your Data

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In this article, you will learn how to manage and access your data using HarperDB, and then automate EDA with data using the Sweetviz python library.

  1. The world generates a vast amount of data stored in databases on servers across the globe, which influences various aspects of our lives.
  2. Extracting insights from data is crucial for gaining a competitive advantage and making data-driven decisions.
  3. Exploratory data analysis (EDA) helps understand the structure, patterns, and properties of a dataset before using it for machine learning models.
  4. Automated EDA can quickly provide a comprehensive overview of large datasets, identify outliers, missing values, correlations, and distributions.
  5. Analyzing data from databases has benefits such as centralized storage, structured data management, and robust security.
  6. HarperDB is a flexible SQL/NoSQL data management platform that allows rapid application development, distributed computing, and other services.
  7. Steps to manage data on HarperDB:
  8. Create a HarperDB account.
  9. Create a HarperDB cloud instance to store and fetch data.
  10. Configure the HarperDB schema and table.
  11. Import data to the table.
  12. Access data from HarperDB using Custom Function, which provides an API endpoint to retrieve data for exploratory data analysis.
  13. Custom Function allows adding API endpoints to HarperDB, and Fastify facilitates data interaction.
  14. Steps to use Custom Function:
  15. Enable Custom Functions in HarperDB Studio.
  16. Create a project, including defining routes to retrieve data from the database.
  17. Define a route to fetch loan data from the customers' table.
  18. Use the API URL to access the data.
  19. Perform automated EDA with Sweetviz, an open-source Python library that generates visualizations and insights with minimal code.
  20. Steps to perform automated EDA with Sweetviz:
  21. Install Sweetviz library.
  22. Collect data from the API endpoint using the requests package.
  23. Load data into a Pandas DataFrame.
  24. Use Sweetviz to analyze the dataset and generate an HTML report.
  25. The generated HTML report provides detailed insights and visualizations for each attribute in the dataset.
  26. The complete code integrates data access, data loading, and automated EDA in just a few lines of code.
  27. By executing the code, a new EDA report can be generated as new data is added to the HarperDB database.
  28. The article concludes by summarizing the learnings and encourages sharing the knowledge.