Convert Arrow to PDF Table

Apache Arrow is a cross-language platform for in-memory data. It defines a standard columnar memory format for flat and hierarchical data that works across different programming languages. This format is optimized for efficient analytics on modern hardware like CPUs and GPUs.

Arrow can handle complex nested data structures and lets you query and work with specific columns without reading the entire dataset.

Key Features

• Columnar memory format for flat and hierarchical data
• Works with any programming language
• Optimized for analytics and modern hardware
• Supports complex nested data structures
• Enables efficient zero-copy reads

Use Cases

Apache Arrow shines in scenarios like:

• Big data processing and analytics
• Machine learning and AI pipelines
• Data exchange between different systems and languages
• High-performance computing applications

Its efficient memory layout and standardized format make it a great choice for applications that need fast data processing and compatibility between different tools and languages.

Adobe created PDF (Portable Document Format) to show documents the same way across different devices and platforms.

PDFs have some cool features:

• They keep formatting intact, including fonts, images, and layout
• You can add interactive elements like forms and links
• They can be password protected for security
• Almost any device or operating system can open them

PDFs are great for keeping documents looking the same, but they can be tricky to edit compared to other formats.

Getting Data from PDFs

Konbert is really good at pulling structured data from PDFs. We can handle complex documents like invoices, bank statements, and financial reports. Our system uses advanced OCR, large language models, and smart algorithms to extract high quality data.

Here are some things our PDF data extraction can do:

• Find and extract tables accurately, even from tricky layouts
• Understand semi structured documents like invoices and receipts
• Handle many different bank statement formats
• Pull out key value pairs and form fields
• Work with multi page documents and process batches

People often use it for:

• Automating data entry from invoices and purchase orders
• Looking at financial data from bank and credit card statements
• Getting table data from research papers and scientific documents
• Digitizing old documents and archives
• Processing legal documents and contracts

Our system is very accurate and reliable. It works well for both personal use and big companies that need to extract lots of data.