There is a growing trend towards migrating from on-premises systems to the cloud. Migrating your content can be tricky. It requires a lot of planning and preparation. There are some aspects that need to be considered before the process even starts.
Documents have been processed for a long time… manually! Thanks to the advancements in technology this task has become faster and automated. Nowadays, AI can automatically process various types of documents, in a much timelier manner and with less error than humans are able to.
We’ve wrote before about the advantages of using AI to automate data extraction. In this article, we’ll explore deeply into it.
Document data extraction is the process of extracting meaningful data from semi-structured and/or unstructured documents for later use or storage. When referring to the use of AI or Machine Learning to perform that task, it’s called Automated Document Data Extraction.
Data is one of the most important aspects of any business. Almost every decision taken in a business is empowered by informed data analysis. By using data, precise decisions are made using trends and facts, not speculation, leading an optimized decision process.
Data enrichment is the process of combining data from internal sources with data from external sources. By doing this, the data already owned is enhanced and more informed decisions can be made.
You’ve probably heard about metadata many times before, but do you know what it is? Metadata summarizes basic information about data, making it easier to find, and to use particular instances of data. Some basic examples of document metadata are, date created, date modified, file size, etc. Other than documents, metadata is used in:
A load balancer is a type of software or hardware device that prevents a server from becoming overloaded. A load balancing algorithm is the logic used by the load balancer to distribute network traffic between multiple servers. But how many types of load balancing algorithms there are, and does each algorithm work? Well, let’s see…