Parseur.com
DocParser
Nanonets
Parsio.io
Docsumo
Parserr
Mailparser
DocuClipper
Google BigQuery
Databricks
Looker
Jupyter
Presto DB
Amazon EMR
Google Cloud Dataflow
Rakam
Parseur is a leading document processing software ranging from email parsing to PDF extraction. Use Parseur to automate text extraction from emails, PDFs, spreadsheets, attachments and documents and put your business on auto-pilot. Setup is easy as everything is point & click and intuitive. Send parsed data to thousands of applications in real time via our integrations with Google Sheets, Zapier, Microsoft Power Automate and Make or your custom application using webhooks.
Companies in finance, food delivery, real estate, e-commerce, marketing, logistics & delivery, travel, hospitality and more are saving thousands of work hours every month by automating their data entry process with Parseur.
Parseur.com Google BigQueryWhen dealing with entities that send lots of data in an unstructured way because they think a PDF is the end of their digitalization process, Parseur is a great tool to automate reading this PDF and converting its data into structured json and then from their you can send it to your endpoint.
Email may probably never die but that doesn't mean that business processes should be slowed or halted. Parseur enables us to create a lot more efficiencies by handling email data as though it was keyed in by a customer agent.
There are other services that do this but for the low cost and the ease of use, this service is the best.
For those of us working in the European Union, Parseur was also easy to assess and approve for GDPR requirements.
The support for post processing is very powerful and with a extensive export options, it is very easy to get data into the right funnel.
Based on our record, Google BigQuery should be more popular than Parseur.com. It has been mentiond 47 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
You can get an account with https://parseur.com/ and then a number with OpenPhone, and Zappier. Those 3 will let you do what you want (easily). Source: over 3 years ago
Iโm sure this is super cool, but have you considered https://parseur.com itโs built for stuff like this. Source: over 3 years ago
For more complex layouts, or if you have to deal with several layouts, it may be better to use third party document extraction tool that connects to like Parseur. Source: over 3 years ago
You could use a document parser tool, like Parseur to better automate the process. Source: almost 4 years ago
And if you ever are in need of an intelligent document processing software, have a look at Parseur.com (of which I'm the co-founder, sorry for the shameless plug ;-)). Source: over 4 years ago
We migrated the analytics layer to Google BigQuery. Same queries that timed out in PostgreSQL now run in under 2 seconds. But not everything belongs in BigQuery โ we initially moved too aggressively and actually reverted some queries back when the added complexity wasn't justified. Our rule of thumb: if a query scans hundreds of thousands of rows or involves complex time-series aggregations, BigQuery. Everything... - Source: dev.to / 4 months ago
Google BigQuery - For large-scale data processing and SQL-based analysis. - Source: dev.to / 5 months ago
Data Pipelines usually read from tables that change over time. Most of these tables are stored in a data warehouse like Amazon Redshift or Google BigQuery. Rows are added or removed. Backfills happen. A column gets renamed or its meaning changes. Even when teams snapshot data, those snapshots are often implicit, not recorded as part of the pipeline run itself. - Source: dev.to / 6 months ago
SQL endures because it's the non-negotiable interface for relational data. Enterprise data storage still relies heavily on relational databases despite new alternatives. What makes SQL valuable for learners is transferabilityโwhile dialects differ across PostgreSQL, SQL Server, and BigQuery, the fundamentals stay consistent. - Source: dev.to / 8 months ago
Within classic cloud data warehouses, Google BigQuery presents a different pricing model. Its on-demand, per-terabyte-scanned pricing can be cost-effective for sporadic forensic queries. But it carries the risk of a runaway query where a single mistake leads to a massive bill. - Source: dev.to / 9 months ago
DocParser - Extract data from PDF files & automate your workflow with our reliable document parsing software. Convert PDF files to Excel, JSON or update apps with webhooks.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.โWhat is Apache Spark?
Nanonets - Worlds best image recognition, object detection and OCR APIs. NanoNetsโ platform makes it straightforward and fast to create highly accurate Deep Learning models.
Looker - Looker makes it easy for analysts to create and curate custom data experiencesโso everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Parsio.io - No-code email & PDF parser
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.