Given the increasing magnitude of distributive frameworks for data processing, organizations encounter colossal amounts of data spread across contrasting and unconnected systems. Moreover, since the endorsement of Software-as-a-Service (SaaS) applications and cloud services, with larger data and varied access patterns, business operations and IT are facing an ongoing discord over the need to share data. Data silos are the result of the increasing challenges of unifying data.

As businesses become AI-ready, efficient data management has acquired an unprecedented role in ensuring their success. Bottlenecks in the data pipeline can cause massive revenue loss while having a negative impact on reputation and brand value. Consequently, there’s a growing need for agility and resilience in data preparation, analysis, and implementation.

Data is the fundamental building block of any organisation. Any transactional data helps analyse how well your organisation is performing as well as optimize your operations for better results. With digitisation making its mark everywhere, it is not an easy task to keep track of the data pouring in from all directions. Organisations have to deal with transactional logs, social data, structured, unstructured, and semi-structured data, which are all going to be captured in a digital format. The traditional methods of simply storing data in a common database go for a toss with such large volumes of data.

It’s a bird! It’s a plane! It’s an unmanned aerial aircraft system recording data in real-time and supporting artificial intelligence to speed up insurance claims, reduce risk to field workers, and save carriers gobs of cash!