Artificial intelligence (AI), encompasses the broad fields of data capture, storage, preparation, and advanced analytics technologies. In other words, AI systems are not limited to a single aspect of Data Management; instead, it has to continue penetrating every aspect of the business through allied data technologies like machine learning (ML), deep learning (DL), and neural networks.
Data is the new oil. The global consultancy IDC projects that “the Global DataSphere will balloon to 175 zettabytes by 2025”. This oft-repeated concept, first coined by British mathematician Clive Humby, highlights the inherent value of data in the post-industrial era and the one that powers the transformative technology of the digital age, like artificial intelligence (AI), predictive analytics, and machine learning. The adoption of AI enables diverse solutions that find applications in businesses as well as in governance and also carries us into an era focused on data – the exponential growth in volume, the analysis, and the management of it. Given that successful AI implementation depends on relevant and useful quality data as a fundamental building block, the collection, analysis, and storage of that data will be increasingly critical to the individuals and businesses that leverage it.