Grooper Tools for the Data Science Workbench
Cut Data Prep Time Drastically. Inject All Data Quickly for Better Data Science.
Manual data prep and extraction are expensive. So are data scientists.
Yet, they spend at least 60% of their time cleaning and organizing data.
Why? The answer is simple. Information is tough to access because of where it’s stored or how it’s labeled.
It’s logical to assume that machine-created data is also machine-readable, but it’s not. There would have to be one universal, standard data structure for all organizations to follow.
If you solved the accessibility problem, you would cut the costs to advance big data analytics, resulting in improved decision-making and problem solving.
Check out how to enable fast and effective data science tasks:
Data Cleansing Tools
The Grooper platform wasn’t built by combining products together through APIs. Because image processing, cleanup, and OCR tools are built into one system, you can do more with original data sources.
In addition, by not jumping between tools, you can automate high quality data cleansing and integration more quickly.
As you may know, accurate text extraction is hard to achieve, even with modern OCR engines. This is because OCR needs perfect images of pages – without any defects, images, borders, stamps, bar codes, etc.
Grooper’s layered AI ensures extremely accurate text recognition along with an understanding of the information in the text.
Meaningful analytics and business intelligence requires accurate data from as many sources as possible.
With Grooper, unlock difficult data from obscure sources like paper and electronic transactions and expand your decision-making processes to more functional and front-line roles for your employees.
Deliver Valuable Business Insight and Deploy Models Faster through Grooper’s Data Science Workbench Tools
Boost your data science tasks, such as:
Tools such as Python, NumPy, Apache Spark, and TensorFlow can transform the way you work with data, but have frustrating limits at extracting large document sets. While it is not open source, Grooper’s open cockpit design provides transparency and fine-tune control over settings.
Basically, Grooper combines the power of open source tools with native data and document processing tasks to function as a highly efficient data science workbench.
Featured Case Studies
Thousands of companies choose BIS to enrich products and services with unique data-centric solutions. Here are some of their stories.