Articles
Data owners bring credibility to the data value chain, removing uncertainties around data interpretations and applicable business rules.
A paradigm shift introduces product thinking to data, resulting in domain-specific data products that evolve with changing business needs.
The lack of co-ordinated collaboration between source system owners and data teams may impact optimal functioning of the business.
Before deploying AI models to solve business problems, it’s vital to take a step back and assess the quality of available data.
Edge computing complements cloud infrastructure to provide resilient and reliable service and improve customer experience.
There are often reservations within a business when it comes to making changes to data tech systems, so it’s good to be aware of the challenges upfront.
The goal is to have a modernised, intelligent data platform that supports prompt delivery of high-quality data to data consumers.
Implementing data automation can help organisations efficiently and accurately process huge volumes of data with minimal resources.
An organisation must have a clearly-defined use case the cloud will satisfy, and a plan detailing the migration method and process that will be followed.
The goal is to undertake the cloud migration with minimal disruption to operations, at the lowest cost and in the shortest timeframe possible.
Data self-service is undoubtedly key to business agility, but the process must start with building a solid data culture in the organisation.
In this fast-paced world, any organisation wanting to survive, thrive and remain relevant simply cannot ignore the urgent need to digitally transform.