Disclaimer: The views expressed in this article are those of the author and do not necessarily reflect the views of the Economic Times – ET Edge Insights, its management, or its members

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Data modernization is one of the most talked about trends in the data management community. In essence, AI is only a part of a much larger data modernization ecosystem, contrary to what many data professionals believe. It entails a plethora of cloud solutions that leverage data as one of the most lucrative assets owned by the business. These solutions include scalable infrastructures that can handle varying workloads, data storage mechanisms combined with analytical engines, functional ML models, and much more.

Niveus has been driving data modernization for transforming business trajectories with sharpened data machines. Our work includes building customer data platforms, connected telematics platforms, other cloud to GCP Migration, Machine Learning Development and Ops (MLOps), AI-based search for documents, images, and videos. From some of the top conglomerates in India to up-coming tech startups, our data modernization solutions have been bringing a digital edge to business operations, replacing legacy and traditional methods of boosting business growth, for accelerated identification of new business avenues. The cloud has opened up an entirely different scope for expansion and growth within the digital pane for businesses. From building automated CI/CD pipelines, curating the best practices in building data lakes, fortifying cloud assets with best-in-class security programs, and much more, Niveus has created solutions for businesses to boost their cloud operations.

A prime area of opportunity for innovation in the industry is to leverage IoT. One of our primary IoT use cases was within the field of telematics solutions to leverage continuous data insights from a connected vehicle platform for automotive manufacturers. The solution improved fleet uptime, repair efficiency, and customer service.

Upon evaluating numerous customer interactions, we realized one of the most pressing requirements that businesses need is to be able to predict customer demand in order to deliver a more profound user experience round the clock. By leveraging the unique capabilities and benefits that come with automation, artificial intelligence and machine learning, we have elevated our solutions and platforms to streamline processes and facilitate innovation. We built a comprehensive solution to map a customer 360° view to cater to the ever increasing customer expectations and improve the overall user experience. The solution brings benefits including real-time dashboards to locate and visualize data for data-driven decision-making. It aggregates all data under one platform for analytics and prediction for proactive decision-making.

The media and entertainment industries is a fields where data is wealth. We realized the potential for machine learning in creating solutions specifically for the media industry. Our custom translation model allows for automated translations of videos from English to selective regional languages – with the ability to assess the context and translate with dialectical intelligence. Our intuitive translation application accepts user inputs, in form of txt files or plain text and facilitates the download of translated files on the fly. With this solution, businesses can promote their media content beyond geographical and linguistic boundaries, reaching new and wider audiences.

Data modernization is all about utilizing cutting-edge, creative technologies to turn your data into a useful asset for your business. Harnessing Big Data allows businesses to employ the wealth of information within their operations for advancing business goals. Partners such as Niveus, bring leading technological advancements into your data modernization strategy, letting you stay ahead of the curve.

Authored by

Aditya Thorat,  Cloud Leader – Customer Engineering, Niveus Solutions

Disclaimer: The views expressed in this article are those of the author and do not necessarily reflect the views of the Economic Times – ET Edge Insights, its management, or its members