How intelligent automation can bridge the gap between unstructured data and effective information

How intelligent automation can bridge the gap between unstructured data and effective information

Unsplash/Markus Spiske 

Paul Hudson of Automated Intelligence explains how enterprises can make the most of innovations around low-code/no code application development, intelligent automation and natural language processing for better collaboration and governance

Guest contributor |

Information management has grown with the innovation of low-code/no-code technologies, intelligent automation and natural language processing (NLP). These tools are growing in prevalence and presenting significant opportunities to improve the use of information management platforms such as Microsoft 365 to better enable collaboration and governance.

As a data management solution provider, our cloud-native, application programming interface-first solution combines low-code/no-code application development with Azure Cognitive Services capabilities to provide intelligent automation with multiple unstructured data sources.

Low-code/no-code application development involves the creation of a software that engages model-driven processes with visual tools to avoid using a code-based programming approach. Unlike previous programming methods, it no longer requires users to have specialist IT knowledge, meaning multiple employees within an organisation can access the data that it holds.

Meanwhile, NLP processes natural language text and transforms it into a standardised structure. Natural language understanding (NLU) – a brand of NLP – then interprets, determines meaning, identifies context and derives insights from the given text. Machine learning algorithms can be used to identify sentiment, process semantics, perform name entity recognition and word sense disambiguation.

Although these technologies are not new, the increasing quality and value that they provide to businesses has improved significantly and are playing a major role in understanding management information. By building a bridge for unstructured data between low-code/no-code technologies as well as cognitive services within the enterprise, information management can be delivered effectively to build automation processes that manage information flow and compliance both internally and externally.

For example, an organisation can organise its data with low-code/no-code technologies supported by NLP and NLU solutions to understand gaps and develop improved products and services in a safe and compliant way.

The future management of information needs to leverage these advantages, effectively merging through an integrated ecosystem of services and technologies. This is exactly where we see key future developments evolving within our platform.

Information takes multiple forms and is processed in different ways. Where it is stored should not restrict businesses, so our platform provides safe passage for insights derived from a growing field of expertise, harmonising structured and unstructured data management while also facilitating interoperability.

As such, the development of the future model of information governance is able to take shape for organisations wrangling with how to digitally transform without impeding the creation, collaboration and flow of information.

Paul Hudson is chief strategy officer at Automated Intelligence

This article was originally published in the Winter 2022 issue of Technology Record. To get future issues delivered directly to your inbox, sign up for a free subscription

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