Cloud technology offers industries the ability to modernize, scale, and innovate. UNLSH maximizes this potential by providing a robust platform that ensures seamless digital transformation while maintaining control, flexibility, and compliance.
The ascent of cloud computing has notably redefined IT, offering unmatched scalability and flexibility, and operational efficacy. However, this narrative is not without its complexities. As organizations expand, the economic charm of a purely cloud-based strategy diminish, unveiling challenges and financial traps.
In the dynamic landscape of modern enterprises, the strategic importance of data is irrefutable. It fuels innovation, provides deep insights, and empowers decision-making. However, with the growing reliance on cloud services and proprietary solutions, the specter of "lock-in" looms large, raising concerns about data ownership, flexibility, and the ability to choose the best tools for the job.
In today's rapidly evolving industrial landscape, data management has become paramount for organizations aiming to enhance efficiency, streamline operations, and enable data-driven decision-making. One example of this shift is the concept known as the "Centralized Core Data Lake." This approach promises to revolutionize how data is collected, stored, and utilized across the range of operations domains in manufacturing.
Manufacturers embarking on a digital transformation journey and adopting Industry 4.0 technologies should carefully consider several factors when deploying a manufacturing analytics system. These considerations aim to ensure the initiative's success while minimizing project complexity and risk, enabling rapid time-to-value, and minimizing lifecycle costs.
We hear the term Digital Twin quite frequently nowadays. The term, rather the concept, was coined long back and has since evolved while staying true to its core ideology. In general terms, a Digital Twin is a cyber replica of an entity such as a machine, material, process, or person (role).
Disconnected Operations is a well-known and critical issue in the Manufacturing Industry. Over the last decade, the industry has spent to the tune of USD 200+ Billion each year on IT and OT assets. These would include Enterprise systems such as ERP and CRM at the top layer, all the way to automation systems on the shop floor generating 100,000+ time-series data streams from the sensors and actuators....
We are at the tipping point of industrial digitalization. The Industry will undergo major changes driven and initiated by technological advances, especially massive advancement in computational and connectivity related technologies. The upcoming changes in the industry are evident from the changes our personal lives have gone through over the last few years.
Maritime Industry is the backbone of most heavy industries when it comes to their supply chain. There are numerous stakeholders in the maritime industry such as ship builders, fleet owners, charterers, ship management companies (SMCs), freight forwarders, shipping liners, port operators, bunker suppliers, insurance providers, classification societies, regulatory bodies, etc.
The Oil & Gas industry is an extremely mature one with a rather complex value chain and a myriad of players playing various roles at every juncture. Every project, operation and activity require significant involvement from numerous players or entities to derive as much value as possible from every drop of oil that is available.The industry itself has implemented a lot of processes and best practices to ensure operational efficiency and continuity...
For a long time now, a lot of an organization’s records and information have been digitally maintained in various data systems such as the all too well-known IT & OT systems. Numerous heavy industries such as the Oil & Gas, Petrochemical, etc. have been dealing with large amounts of complex data for a long time. However, when it comes to digital maturity, they are not too high on the index...
This is one question that I have been faced with repeatedly while making sales pitches. What is analytics anyway? While everyone has their perspective of what analytics actually is, this is how I see things – Problem statements fall into two fundamental categories...
