Data Engineering & Analytics

While a few organizations are still keen to keep their data on-premise, there is a massive shift towards adopting cloud or at least hybrid solutions. Albeit a bit tricky, this task must be carefully done with a thorough understanding of domains and technologies (AWS, GCP, Azure and others) in an agile mindset: with clear map of the risk involved, and foolproof mitigation plans in place.

The design and deployment must duly consider both business and customer requirements, along with the total cost of ownership, future advancements and the flexibility needed. Our engineers come with creative ideas that lead and support in the entire process of data migration and transformation, while making the transition to cloud easy, affordable and successful. Some of these areas include:

A new stage in the Information revolution has started: the era of the Internet of Things (IoT). The worldwide web now has physical devices which can sense and communicate data. They can interact with their external environment as well as their own internal systems. In other words, smart devices, driven through power of technology, can bring artificial intelligence.

InOpTra is eager to be a part this new phenomenon, and to partner with you to support your IoT initiatives; ranging from hardware developments to application developments, mobility to analytics and integration of them. We will be your valuable partner in developing smart, connected products and applications that harness the power of data and analytics, providing integrated services to develop and manage IoT solutions.

The Internet of Things (IoT) has the potential to completely change how businesses work and how they connect with customers. IoT isn’t just about re-launching products with IoT enabled features. While sensor technologies, wireless technologies and mobile technologies are driving the evolution of IoT, the true business value of IoT lies in leveraging the data to derive real benefits rather than just adding hardware features. Analytics on IoT data can yield useful and actionable insights about products, customers and business operations.

As IoT is an interconnection of several devices, technologies, machines and human resources to achieve a common goal, lot of objects and machines are getting connected to the internet transmitting the data. The objective is to harness this data to discover useful trends and meaningful insights that can help timely decisions or interventions.

A new industrial revolution is propelled by a system intelligently assessing the conditions that affect manufacturing processes. Humans can learn and make decisions based on such information. Companies are driving their assets to generate more revenue without further investments. With Artificial intelligence driven by Data Analytics and IoT, we can make this a reality.

Production in both discrete and process manufacturing industries rely on throughput, and is a complex system for production and sensing devices. Once the right processes and technologies have been identified for IoT enhancements, the next challenge would be to integrate these systems into existing operations, or combine them with other forms of AI seamlessly. Together, this will enable intelligent systems and processes, as information is constantly analyzed in real time to optimize the same.

One of the ways to pick up IoT, analytics or AI initiatives is to set up a Center of Excellence to drive these initiatives. Many times, it is essential to pilot and prove the concept and its usability before proceeding with large scale deployment. The best option could be to set up a COE or R&D team and pilot the concept. A further systematic ramp-up of the team, products, features can be planned.

InOpTra will shoulder the entire responsibility of developing the COE or R&D team. With access to skilled resources, flexibility, speed, and low investment costs, we can be a good partner for such innovation. Your IoT and/or Analytics initiatives will be taken up in a phased manner. The typical need for a large up front investment can be managed with phase-wise growth.