In the digital era, data is generated on an exponential scale in different modalities. Traditionally, decision making is centric on tacit knowledge and common sense to anticipate risks and consequences of critical business choices. The availability of big data and computational resources has opened up new opportunities for businesses to generate actionable intelligence.
As companies start to leverage the massive data volume collected by legacy systems, current data systems, and future Internet of Things devices, it is critical that proper data governance and information management policies are put in place. Actionable insights are only gleaned when data is fused across multiple sources, thus bringing value to the organisation and not just the data silos.
To ensure that critical and sensitive information is not haphazardly shared across the organisation in the name of Data Science and Analytics, we provide the expertise to develop and deliver a data governance and information management platform to modernise the management of data. By implementing searchable data catalogues, governed by data quality and data control rules, an organisation would worry less on the data compliance and data stewardship, and be able to focus more on actively mining their data for new insights.
Our suite of AI, Data Analytics and Machine Learning Operations (MLOps) solutions is designed to support end-to-end model development lifecycle, incorporate explainability in AI and operationalise AI modes at scale to production environments.
This solution is an open-source, purpose built analytics platform product that is built upon an open architecture that is modular and scalable to support large scale customer demands in domains such as Smart Cities, Public Safety and Defence. It can be hosted on premise or support hybrid and multi-cloud environments leveraging common analytical toolsets and orchestration layers.
The Smart Enterprise Platform supports: