Artificial intelligence run on data. More the quality of data, more efficient will be the process of AI decision making. With business organisations living the dream of an easy working environment with the aid of powerful AI techniques, big data take the role of a catalyst to amplify the process. As the name implies, big data refers to massive, complex and high-velocity data sets. It can be analysed and explored for information. The use of big data in AI decision making can be an asset for organisations as it increases revenue and profit.

Big data took over the world before even it was realised that it exists. It grew hand-in-hand with the enhancement of AI across the globe. By the time the term big data was coined, it had accumulated a sea of information, by which if analysed properly it revealed valuable insights into the industry that it belonged to. Driving the intuitions from such enormous data is a herculean task as far as humans are concerned, and hence take charge the AI algorithms. With a rise in demand for AI in foreseeable future, there is a birth of a synergistic relationship between data and AI, where AI will be useless without data and mastering data will be invincible without AI.

Providing big data as a service helps companies to organise, manage, and analyse large data sets which succour to generate understanding to improve business operations and leap forward in a competitive market. Big data as a service (BDaas) is the delivery of data platforms and tools by the cloud provided. Given there are numerously structured, unstructured and semistructured data generated by many companies BDaas free up the organisational resources for which it takes advantage of the data management system. It uses the skillset of an outside service provided rather than placing an in-house staff for such function. 

Business Analytics

According to Forbes, “a combination of AI and big data can automate nearly 80% of all physical work, 70% of data processing work, and 64% of data collection tasks”. As per their calculations, big data and AI can influence the workplace apart from their contributions in marketing and business. Sectors that are already known for working with AI-based systems, including finance, healthcare, banking, insurance etc., has been using big data to boost their organisational success and ensure risk management, performance and profitable growth with the help of data analytics. Professionals in the field of healthcare are using BDaas solutions to get patient data as and when required to ease action and in case of emergencies. Furthermore, there has been increasing emphasis on research and development activities to introduce enhanced security and improved data quality. Innovation in the field might be a great leap in the AI sphere. 

Sculpting the future

AI and big data can achieve more when they work hand in hand. According to the latest report by IMARC Group, titled “Big Data as a Service Market Share: Global Industry Trends, Size, Growth, Opportunity and Forecast 2022-2027,” the global big data as a service market reached a value of US$ 30.63 Billion in 2021. Looking forward, the market expects to reach US$ 103.31 Billion by 2027, exhibiting at a CAGR of 22.14% during 2022-2027.

The data which is used to train the machine makes the AI smarter. This leads to the lesser need for human intervention which will reduce the processing time. In a later stage, AI would need lesser people to function it and thus the society will realise the potential and scope of the AI-big data cycle. However to reach this stage, presently we require exceptional individuals trained in data analytics. All the goals of AI such as Reasoning, Automated Learning and Scheduling, Machine Learning, Natural Language Processing, Computer Vision, Robotics and General Intelligence will reach their peak with their AI algorithm running massive amounts of data. Big data will continue to enhance, with AI being viable for automating more tasks.