Big Data in Artificial Intelligence - Part 1

Data is the backbone for building AI systems. We live in a digital era, so our world is built on information and data. We see data of all kinds being collected by the organizations from everywhere these days. While data was at one time structured and fairly easy to process, the sheer volume of information now available has resulted in data that is raw, unstructured, and complex.

 

The data flows constantly from social media interactions, smart technologies, sensors, gauges, mobile devices, videos, texts, and countless other sources. Since much of this data is generated through personal habits, behaviours, and activities, it contains valuable and actionable insights that can influence decisions and help companies formulate more targeted and personalized business strategies.

For the organizations to make use of this huge data, we use Big Data as a tool for collecting, managing, and analysing massive amounts of unstructured data and that is where big data analytics platforms do best. With big data analytics platforms, all corporate data can be shared across every channel within an organization. This means that, for example, the marketing department has access to data from the sales department, and vice versa. As a result, each department can work collaboratively, sharing data and insights that can be used to formulate strategies that are more unified and better focused on achieving corporate goals.

 

 

AI’s ability to work so well with data analytics is the primary reason why AI and Big Data are now seemingly inseparable. AI machine learning and deep learning are learning from every data input and using those inputs to generate new rules for future business analytics. Data and AI are merging into a synergistic relationship, where AI is useless without data and data is insurmountable without AI. Big Data is going to continue to grow larger as AI becomes a viable option for automating more tasks, and AI will become a bigger field as more data is available for learning and analysis.

According to a Salesforce study, Big data tools allow businesses to collect massive amounts of raw, real-time customer data. But the major strategic benefit lies in the ability to analyse that data, using predictive models and machine learning to gain insights into future customer buying behaviours - insights that can be used to formulate business strategies and optimize business outcomes.

 

Another study by McKinsey tells us that companies that have adopted data-driven strategies enjoy 5 percent higher productivity and 6 percent higher profits than their competitors. Integrating data alone does not generate value. Advanced analytic models are needed to enable data-driven optimization (for example, of employee schedules or shipping networks) or predictions (for instance, about flight delays or what customers will want or do given their buying histories or Web-site behaviour).

(To be continued..)