Data has become the lifeblood of any organization looking to be competitive in the digital era. Being connected and able to access information at one’s proverbial fingertips can empower decision-makers with better insights. However, this is not always the case. Speed and relevance are two of the most significant stumbling blocks that limit the potential of data.
According to some estimates, the entire digital universe would have reached 44 zettabytes (ZB, which is a trillion GB) by the end of 2020. This would translate to 40 times more bytes than there are stars in the observable universe. But perhaps even more significant is that research shows the volume of data created, captured, copied, and consumed worldwide will likely hit 149ZB by 2024, more than three times that currently available.
Of course, this vast amount of data at a company’s disposal can create its own set of problems. Trying to find the information pertinent to a search query as quickly as possible has become difficult. Anyone performing a search using the engine of their choice knows all too well that it is often not the first few results that deliver the expected outcome.
While this has resulted in the growth of search engine optimization services, a market expected to top $50bn by the end of the year, companies still face difficulties finding relevant results when it comes to complex search queries.
It is therefore critical for organizations to find ways to contextualize the information and make it relevant to employees. Optimizing search strings and upskilling people with the understanding of how to better find data have proven useful. However, as data becomes increasingly complex and widespread, employees are fighting a losing battle to consistently get the right and most up-to-date information.
Fortunately, the availability of artificial intelligence (AI) and machine learning (ML) technologies that can be injected into existing search processes have made this an easier proposition. AI and ML can scour, analyze, and group data across the web at breakneck speed, and can deliver near real-time intelligence and insights to businesses. Think of AI and ML empowering the business to access more precise and customized answers to queries in ways traditional search engines cannot.
These algorithms can be designed to search across social networks and other unstructured data sources, as well as bringing even more comprehensive results factoring in all possible sources than were possible before. So, whether it is a market intelligence, due diligence for fraud protection, or simply performing sentiment analysis on people’s view of a company’s brand, a new layer of opportunity is unlocked with these sophisticated technologies.
However, to leverage these new ways of categorizing and searching for information people must change the way they view data. Having access to a centralized dashboard that incorporates the AI component that ties everything together becomes essential.
It is no longer good enough to simply rely on traditional search procedures to get the job done. Companies, regardless of size or industry sector, need better business insights to build their knowledge and intelligence. Using solutions capable of unlocking this potential will be a critical competitive advantage.
This does not mean simply downloading an “enhanced” app and hoping for the best. Instead, it is about partnering with a trusted and experienced organization that can deliver a cloud-based solution able to continually adapt to changing requirements. Information on its own has little value if not delivered in the context in which it is required.
AI- and ML-driven, cloud-based technologies are critical to enabling this in a user-friendly manner that empowers decision-makers with the “right” information. Intelligent search that is more insights-driven, leverage these sophisticated technologies that are the building blocks of providing relevance at speeds unheard of. With data continually expanding and becoming more complex, these are the systems that will help drive business in the digital world.