Six challenges for Artificial Intelligence’s sustainability and what we should do about it

whitePaper | July 8, 2022

This series of white papers lays out the essential steps you need to take to ensure your business stays at the forefront of an increasingly data-driven and automated world. We cover everything you need to know about growing a data science team, the current trends in machine learning, data visualisation, essential data science tools and technologies, automation, deployment, how to prove value with data science and also give our thoughts on the next ‘big ideas’ that are set to take the world of AI in business by storm.

whitePaper | December 19, 2022

When an Azure region is not available due to issues at the Datacenter level, this should not affect the availability of data. Hence, database replication is required to avoid data loss at any given point in time. Some Microsoft Azure regions do not support Azure database replication in different regions. (Refer to the image given below) To overcome this, manual replication of MySQL database using MySQL workbench is the only feasible option.

whitePaper | November 15, 2019

We are living in an era of digital disruption. Multiple industries are being disrupted, or fear being disrupted in the near future. Business models are evolving to cater to the dynamic markets and digital transformation that seems to be the answer to changing business models. Digital transformation is rapidly becoming a key priority in most industries, as organizations adapt to changing markets by leveraging technologies to build IT-centric business models. In general, organizations are using digital transformation to reach their goals of achieving greater agility, improving operational efficiency, improving customer experiences, and developing new revenue streams.

whitePaper | September 2, 2022

This year, unlike previous years, we asked professionals the most difficult elements of a successful data strategy instead of the most important.

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 | June 24, 2022

The reactive approach to discovering, analyzing, and correcting data quality issues in business applications has been marginally effective throughout the era of data consolidation for analytics (data warehousing, etc.) and the subsequent onset of “big data.”