Enterprises are often told that artificial intelligence (AI) is the key to unlocking insights from unstructured data, but why?

Firstly, data that is not structured is harder to analyse and process than structured data because it isn’t organised or stored the same way. If the data lacks structure, it is not crunchable by conventional machine algorithms. When enterprises collect unstructured data, it is indexed separately in a jumble, logged with only basic tags and markers (if that!).

Additionally, unstructured data greatly outnumbers structured data – and when we say greatly, we mean it. 80 to 90 per cent of data generated by enterprises is unstructured, and that sheer volume is overwhelming.

Throw in that unstructured data requires a human to wade through it because traditional algorithms can’t make sense of it – it is too chaotic and voluminous to process – and the need for artificial intelligence becomes clear.

AI to the data rescue!

Asking humans to analyse unstructured data is like asking cashiers to process the items on conveyor belts that throw thousands of items at them simultaneously. The barrage of data is too great for humans to analyse. The problem is that this data holds significant value, so it is a mistake to pile up without any analysis and value extraction.

While structured SQL databases and NoSQL key-value stores have algorithms to process data, unstructured data has AI. With AI, the algorithm adapts in real-time, learning how to process unstructured data with rules and code.

Features of AI for data analysis include a query language to orchestrate database retrieval (exact search), pattern search using machine learning (approximate search), and user-defined functions (domain-specific search). Additionally, the AI can run cross-platform on emerging and legacy server architectures.

AI identifies data types and connections among datasets, recognising language and knowledge with natural language processing. The information within data is extracted and processed, creating a stream of valuable data.

Simply put, AI Automates repetitive learning and discovery through data, creating datasets and algorithms that get the job done. The processing capability is enormous, and the more data you feed the machine, the smarter it becomes.

As enterprises collect more data, AI is critical to creating algorithms that can analyse and extract value from it. Traditional algorithms are incompatible, and humans are not suitable. If it was ever AI’s time, this is it

Feel free to contact us to discuss your data challenges.