Unleash the power of data & analytics with AI | 7wData

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The fast-paced age of computer connectivity is blurring the lines among physical, digital, and biological spheres. Tech is everything and tech is everywhere. Most organizations have somehow gone through a digital transformation journey. Today, almost every company is a technology company.

As automation technology matures and becomes an integral part of business operations, it’s time for organizations to pivot from process automation to intelligent automation, and from data-driven organizations to AI-powered organizations.

However, many organizations are still struggling with digital transformation to become data-driven.

So, how should they approach this new challenge?

IoT (Internet of Things) is the source of big data; cloud computing facilitates the storage and processing of large data sets; AI (Artificial Intelligence) enables advanced analytics; ML (Machine Learning) learns and identifies data patterns and makes predictive analytics to perform operations without human intervention, and cognitive computing mimicking the function of the human brain helps to improve human decision making.

Cognitive computing is the next generation of information systems that understand, reason, learn and interact with the business ecosystem. It is continually learning from past experience, building knowledge, understanding natural language, and reasoning, and interacting more naturally with human beings than traditional programmable systems.

Cognitive computing is the third era of computing. We went from the first era with computers that tabulate sums (the 1900s) and the second era with programmable computer systems (1950s).

Advancements in technology, especially in data & analytics, enable a range of unforeseen opportunities to amplify, automate and optimize business operations and decision making.

After embarking on a digital transformation journey in the last decades. Now, data and analytics have become widespread, well understood, and used successfully in many organizations. Therefore, this would be a good starting point for organizations to embark on their AI transformation journey.

A recipe from data and analytics to AI is a natural and pragmatic progression. Winning with data, analytics, and AI requires a holistic approach to data-driven, analytics-enabled, and AI-powered technology strategy.

Artificial Intelligence (AI) seems to be the buzzword presenting both distracting hype and powerful opportunities to leap the business forward. Today, AI remains elusive, misunderstood, and captured the imaginations of many.

What exactly is AI, how can we get there, what are the opportunities, what are the challenges, and what are the benefits, in practical terms?

The exhibit below is the typical AI technology roadmap with its branches and approaches.

While data analysis is the process of turning raw data into clear, meaningful, and actionable insights, artificial intelligence (AI) is a data science field that uses advanced algorithms to allow computers to learn on their own from experience, adjust to new inputs and perform human-like tasks. It seeks to mimic human abilities and simulate human intelligence in a machine.

Businesses produce massive amounts of data that are impossible for humans to keep up with. However, if we can analyze data by leveraging the power of artificial intelligence, then we can produce results far beyond what humans are capable of doing, in terms of speed, reliability, and accuracy. In other words, AI makes big data appear small. It automates and simplifies many humans’ tasks.

AI is a broad field of study that includes many theories, methods, and technologies. The following are the major subsets of AI:

Machine Learning is a subset of AI that trains a machine how to learn. It is a data analysis method that automates the building of an analytical model and makes necessary adjustments to adapt to new scenarios independently.