How Analytics & Data Science Teams can leverage the Semantic Layer

whitePaper | October 1, 2021

centering your database and data analytics workload development and deployment on a Kubernetes-based container, you can create a more efficient and speedy data life cycle. Access this white paper to learn how to improve key capabilities for database and data analytics workloads across hybrid cloud environments.

whitePaper | December 1, 2022

IT and business leaders are increasingly seeking to harness the valuable data they collect every day to transform their business operations. Yet, these data assets are only as valuable as their organization’s ability to securely access and convert siloed information into scalable enterprise-wide insights. Even though every modern enterprise generates a goldmine of data, many lack the necessary infrastructure to mitigate data privacy and security concerns enough to fully leverage that data for informed decision-making and maximum impact.

whitePaper | August 25, 2022

Most organizations realize data governance is necessary - if not indispensable - for mitigating data risk while sustaining its longterm value. However, there’s still a fair amount of ambiguity around what exactly data governance is and how to best implement it. By definition, data governance is an enterprise-wide initiative for formalizing the processes, people, and protocols for using data. It reduces risk while increasing data’s ultimate value: consistent reusability for achieving mission critical objectives. Data governance is a strategic approach for creating unassailable trust in data throughout the enterprise.

whitePaper | December 9, 2022

In Data Governance Methodology, we described why a modern active data governance methodology is superior to a traditional top-down methodology and how active data governance is supported by continuous improvement. We also discussed how a data governance process based on continuous improvement is a key component of a DataOps process.

whitePaper | November 30, 2022

Modern cloud analytics can help financial services organisations to gain greater insight into their ever-increasing volumes of data, enabling them to improve customer experience, boost productivity and generate new revenue streams.

whitePaper | March 12, 2020

This point of view is an exploration of the possibilities engendered by rethinking the role of data scientists in the wake of industrial revolution. It might be claimed that current trends in industrial revolution reflect a paradigm shift towards data centric processing with data science playing an increasingly critical role. This point of view also explicitly highlights the potential role of Data scientists as an emerging phenomenon, and then to show some of the benefits that this role can bring as we move towards industrial disruption