How Machine Learning can transform your data into valuable outcomes.

Updated: Oct 12

The world is crazy about data.


There has been much talk lately about the possession of data, quality and quantity. Data is a prerequisite for sensible automation and analytics. Data is at the heart of every AI solution. Artificial intelligence, like machine learning, is data processing into specific results like predictions, recommendations, or summarization.


But possessing data is not enough to receive valuable results.

What is data?


Data is everything. And everywhere. Data is emails, phone call logs, textual documents, budgets, invoices, contracts, Internet searches, pictures, and graphs. Every piece of information you work with retains data. Some of it is structured, clearly understandable and easy to use (e.g., budgets, excel sheets, invoices, and quantitative information in the form of tables), but most of it is not. 80% of your data is unstructured and contained in your emails, customer claims, and legal forms.


To fully understand structured and unstructured data, machine learning models, based on various techniques and approaches, like natural language processing, are required (see our article: What is NLP?).



Can data be turned into gold?


If you are a scientist or just involved in R&D processes, you know how difficult it is to find that specific information in your files. With only manual research, you will have to review all your documents referring to the topic or issue you are researching. Even minor omissions may lead to unexpected and negating effects.

The rapid development of AI-based tools gives many opportunities for data mining, extraction, and search-based tasks.

With well-trained models, you can scrape all resources you have or would like to have and find relevant information in an accessible manner. Such tools can find phrases, keywords, or parts of the text, link them with other resources, and give you a global overview.



Learn how to use your data.

Machine learning models (also called deep learning models) can find correlations, causes for effects and sometimes surprising dependencies between what appear to be unrelated data. With such support, scientists and workers can spend more time on their research and companies can organize their work more effectively, draw parallels where needed and save time and money.


If you are interested in learning more about Docmatic's innovative technology or want to test our solutions live on your documents, please contact us at: office@docmatic.ai.
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