How is your data captured?
As your organization captures data from external sources such as social media, RFID and wireless technology, and combines it with the internal data you’re storing, you must ensure that it is blended properly and being utilized appropriately so that it advances the objectives.
Aggregating data from mobile phones, your organization’s software applications, IoT sensors, partner streams, social media streams and so on, can be incredibly difficult. So it’s not surprising that siloed data is often listed as a major contributor to the inability to gain meaningful insights and the failure of big data projects.
There’s plenty of technology available to support the integration of data between silos, so the problem doesn’t lie in the technology. Most often, the biggest challenge in capturing data effectively is the lack of understanding of the critical role that data integration plays in achieving the goals of the objective.
While adoption of an AI tool certainly sounds appealing, and may soon become a necessity for many businesses to remain competitive, it won’t be nearly as effective if it’s working from siloed, or incomplete data. In this way, it’s much more important for your organization to ensure data is integrated appropriately and captured effectively first, before exploring AI adoption.
In order to maximize the potential of data and its analysis, you need to ensure a solid foundation by making certain you’re working with up-to-date data that’s been captured appropriately from every relevant source.