Making data useful is an essential part of driving decisions for enterprises. The measure of successful business productivity and adaptability lies in utilizing dormant data in the face of rapid changes. Empowering the front-line of business through AI and analytics will create ample opportunities for growth and long-term stability.‘

Adapting to changing consumer requirements is a primary goal for any organization to sell better and progress in managing their business from the sales point of view. When a business fails to recognize the customer’s choice and preferences, catering to the relevant market becomes more and more of a stressful scenario.

As conversational AI technologies gain traction, they substitute hard processes, becoming valuable assets to businesses that are seeking to gain a competitive advantage among peers. Automated processes reduce the burden on employees in every office space by taking away the most time-consuming and mundane activities that plug creativity.

As businesses are growing, serving customer queries is no longer restricted to direct and personal employee interactions but has instead moved to digital channels through interactive displays and service chat bots.

For every organization, innovation and resilience is the only thing that keeps them motivated to keep going amidst a global pandemic.

In the absence of a planned cloud strategy, adopting a multicloud approach may lead to higher spending. A long-term value vs cost perspective will help enterprises realize higher benefits.

IoT application testing is an essential part of smart device development. Just like any other system, the IoT systems have to work seamlessly well in the desired environment during their deployment. Hence, it demands rigorous testing as they are often deployed in heterogenous application platforms with various infrastructural dependencies. The devices are also mostly located far from any

Centralized servers were established as the be all and end all of computing until it started to change as this form of computing is costly, hard to scale and resource intensive. Cloud computing emerged as the most flexible model of computing that could cater to a wider range of networking requirements. But computing needs have grown to the peripherals of the network with devices called as edge

At the core of the advanced AI, IoT, big data and analytics-based solutions for smart farming is the collection and analysis of data for generating real-time relevant insights at scale and speed, leading to phenomenally higher yield and better utilization of resources.

Boosted by the growing adoption of advanced technologies, sensors, and the Internet of Things (IoT), could servitization become the default business model for smart manufacturers?