Artificial Intelligence (AI) is rapidly transforming our world and is becoming increasingly crucial in commercial operations. According to Deloitte’s research, 73 percent of IT and line-of-business executives perceive AI as an essential aspect of their present operations. It’s evident that AI has enormous promise in practically every aspect of our lives, but AI systems can only ever be as powerful as the data they’re based on. We’ll look at the important elements behind the data necessary and how it’s sourced, as enormous amounts of extremely specialised data are required to properly train systems in the right way
The goldmine that is public web data
Let’s start by looking at where data comes from, which is more readily available than you may think. That’s because it comes from the vastest pool of information that has ever existed – publicly available web data. One example is public social media data, which is being used by organisations as a source of information in regards to consumer sentiment and behaviour. Businesses in fields as diverse as insurance, market research, consumer finance, and real estate are using this data to construct AI systems in order to acquire a competitive advantage.
In many cases, data from Twitter tweets and online reviews is used to produce AI insights that help businesses stay afloat in a dynamic business environment. Hiring announcements for openings in the automotive business, for example, on Twitter or other job portals could suggest an economic comeback in that area, or that the company itself predicts an increase in demand.
Getting past data obstacles
Although the data is widely available, accessing public web data at this mammoth scale is not without its challenges. Organisations are often blocked by competitors in the process of retrieving data, or they encounter difficulties accessing data in every region they are looking to target globally. As a result, it’s critical for organisations to invest in a web data platform that can provide them with the data they require on a constant basis. It will have to be a worldwide network capable of handling massive data volumes.
Being able to access the correct data is essential as teaching AI systems properly is impossible without following the proper data retrieving protocols. Only “clean” accurate data can create the right level of ROI for businesses. Often, requests seen as coming from data centers are blocked by websites, or fed incorrect information, as businesses want to prevent accessing data by their competition to gain a competitive advantage. Using a flexible web platform solves this problem, as it provides a transparent view of the internet – just like it was initially intended when it was created.
The value of accurate data
Of course, while organisations can benefit from this, they must ensure that the appropriate technology and processes are in place to deliver actual value. When looking at building an AI system, it’s akin to building a house. You can have the best architect or the best team of builders available, but if there are flaws with the raw materials, they are the wrong type, or there are simply not enough of them, there are going to be serious issues with the final product. If you build on a foundation consisting of clean and accurate web data sources, you will have a robust base that you can build powerful AI systems on top of. These systems will be able to provide effective, dependable, and relevant business insights despite the unprecedented volatility in market trends.