From Unstructured to Structured Data using LLM & BDB Data Platform

PDF Data Extraction Flow

In today’s data-driven world, organisations handle vast amounts of information, much of which is stored in unstructured formats such as PDFs. Extracting and structuring data from these PDFs can be a daunting task.

In this article, we will explore a comprehensive data pipeline that covers the entire process, from reading PDFs stored in various locations to creating stunning visualisations using BDB Platform.

Step 1: Reading PDFs from Storage

The journey begins with the need to access PDF files from various storage locations. These can include cloud storage solutions like Amazon S3, on-premises systems, sandbox environments, SFTP servers, or even local files. To accomplish this, you'll need a versatile data ingestion system that can seamlessly connect to these sources.

Solution:

BDB pipeline supports many data readers and libraries, like AWS S3 , SFTP libraries, or specialized connectors, can retrieve PDFs from these sources. Choose the one that best suits your infrastructure and requirements. Once you have fetched the PDFs, you’re ready to move to the next step.

BDB Data Readers

Step 2: Text Extraction from PDFs

PDFs are notorious for containing unstructured data, making it challenging to extract meaningful information. In this step, we need to extract text content from these PDF documents accurately.

Solution:

To extract text from PDFs, you can employ BDB AI services for text data extraction. This will help you transform the PDFs into structured textual data that can be processed further

PDF Processing Pipeline

Raw Text Extracted from PDF

Step 3: BDB Assist for Proper Restructuring of Unstructured Text Data

Now that we have extracted textual data from the PDFs, it often remains unstructured and not directly usable for analysis or storage in databases. To transform this unstructured text into structured data, we turn to BDB Assist.

Solution:

BDB Assist is a powerful LLM tool offered by BDB.ai that specializes in structuring and organizing unstructured textual data. It can perform tasks like entity recognition, sentiment analysis, key phrase extraction, and more, providing a well-structured output that's easier to work with.

Output Structured Data

Step 4: Write Data to Database

With structured data in hand, the next logical step is to store it in a database for future reference and analysis.

Solution:

You can use a variety of databases depending on your needs, including SQL databases like PostgreSQL or MySQL, NoSQL databases like MongoDB, or cloud-based solutions like Amazon DynamoDB. BDB Assist can help you create database schemas that match the structured output, simplifying the data storage process

BDB Data Writers

Step 5: Create Visualisation Using BDB Self-Service Module

Now that your data is securely stored, it's time to gain insights and communicate findings through compelling visualizations. This step is crucial for data-driven decision-making within your organization.

Solution:

BDB offers a self-service visualization module that allows users to create interactive and insightful visualizations without the need for extensive coding or design skills. With drag-and-drop functionality, you can create charts, graphs, dashboards, and reports that present your data in a meaningful way. This module integrates seamlessly with the data stored in your chosen database, ensuring real-time updates and dynamic visualization options.

BDB Self-Service Report

In conclusion, the journey from reading PDFs to creating stunning visualizations is made possible through a well-orchestrated data pipeline. Leveraging the right tools and technologies at each step, such as BDB Assist for restructuring unstructured data and the BDB self-service module for visualization, empowers organizations to harness the power of their data efficiently. This streamlined process enhances decision-making, aids in compliance, and ultimately drives business growth.