Insights

Hyper-Automation is an end to end automation process which includes the power of multiple technologies, from Robotic Process Automation (RPA) to Machine Learning (ML) and Artificial Intelligence (AI).

Tools like RPA, Machine Learning and Artificial Intelligence operating to automate complex business processes, Including where subject matter experts were once required. Hyper-Automation is a means for real digital transformation.

The Need to Transform Now

Millennials, Gen z, or Covid-19 all have disrupted the retail industry across sub-segments, still, the demand is purely driven by consumer expectations. Today, companies with innovations are defining the boundaries and standards in the industry. Leaders in various segments rely on technology that enables them to deliver what consumers want, at a scale, and provide the ability to quickly innovate.

Oil & Gas is an extremely wide and resource challenged industry with critical operational challenges. Precious time can be compared to black gold itself; substantial competitive advantage can be achieved by improved efficiency. The Oil & Gas industry having many operational challenges and they manifest themselves through lengthy order to cash cycles, low utilization and revenue per field resource numbers, high bill contestability and difficulties delivering and supporting customer commitments.

Digital technologies are driving the paradigm shift in the commodity market. Adoption of Intelligent platforms in commodity sourcing has been growing since the last decade. 

Manufacturers and traders are increasingly adopting modern technologies like Artificial Intelligence, Machine Learning and Blockchain to have better control over the volatile commodity markets

Digitization in the commodity world is reshaping how commodities are procured with optimal use of present-day technologies, thus increasing productivity.

Testing of ETL Projects – Why is it crucial than ever?

Testing of business-critical applications that are data and process-intensive is a laborious process owing to varied factors. Processing of huge amount of data from multiple sources involves complex calculations, transformations that necessitate frequent and elaborate data loading and reloading activities.