Data had always been around- restricted, unrealized, undermined, or even unknown for thousands of years of human existence. However, digitalization brought a paradigm shift as it connected everybody to anybody, even humans and machines, unrestricted by any physical challenges like distance, language or form, harnessing technology to create new value. Digitalization plays an even more significant role in driving digital transformation as companies are transforming the way they do business in the digital age, as customers and data are at the core of those transformations.

Especially the digital economy, mobile and big data technologies, are letting companies find entirely new ways of creating value and shifting the focus on what data analytics solutions can do to their business decisions and actions. The focus is turning from products and services to outcomes and possibilities are being created for service development, operating models, and Collaborative creation.

A fundamental imperative for organizations aspiring to transform themselves digitally is the necessity to store, manage, and analyze vast volumes of unstructured data captured from distinct sources. The data is gaining more relevance considering with a growing population, unprecedented urbanization, evolving economy, and spiraling consumption. The overall connected devices ecosystem is expected to grow to 2.2 billion by 2022, and an estimated 40 trillion gigabytes or 40 zettabytes of data is expected to be generated by 2020.^{(1) (2)}

Also, the rapid advancements in the IoT and AI-enabled data analytics, from ingesting data to visualizing results, and integrating data and insights into periodic workflows is helping heterogeneous, disconnected data in silos to converge into massive pools creating a virtual model of our real world.

Thus, Big Data through Big Data Analytics is emerging as an asset of crucial significance in the modern business environment, empowering enterprises to leverage the power of analytics, machine learning, and AI. Companies are embracing a three-pronged strategy in the digital transformation business. First, concentrate on customer relationship management as it is the foundation of any enterprise, second, integrates data sources for a more inclusive representation of the customer, and the third is extensive data analytics to become more efficient and innovative with new data intelligence.

The analytics paradigm has been downshifting to the cloud, and the current state of AI indicates this shift as machine learning. Governments, Businesses, and Organizations are now in the complete digital transformation mode, traversing the power of data through IT infrastructure and data science tools in the cloud and investigating with advanced machine learning or deep learning creating primary growth opportunities for cloud architecture. No doubt, 97.2% of organizations are investing in Big Data, and AI, expecting Big Data Analytics market to reach $103 billion by 2023.⁽¹⁾

Big data analytics solutions have enabled exceptional and accelerated progress in machine vision and natural language processing abilities over the last few years through heaps of tagged and labeled online data. The technology has stretched to a limit where companies have more than ample anonymized data to discipline the methods to implement the AI to derive the maximum value from data. The drift is shifting to deep learning, and Big Data is now evolving as Big Data AI.