The Nine Principles of Agile Business Intelligence

whitePaper | October 17, 2022

Today, massive amounts of data are collected, processed, and stored for a range of analytical purposes around the world. Every customer, device, transaction, email, and image leaves a data trail. At present, this data is growing too big, changing too fast, and becoming hyper distributed. The traditional ways of doing integration and analytics are no longer viable or scalable. It is not feasible to create millions of data pipelines and to continue moving large amounts of raw data to a data lake or a centralized data warehouse.

whitePaper | April 7, 2022

This white paper was created to outline best-practices for measuring, reporting, and building a constant stream of key performance indicators related to your physician network.

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 | October 27, 2022

Data governance is on everyone’s mind as we move from a static model of data to a dynamic, living, breathing data architecture. As many brilliant people have already said, data — and knowledge in general — is full of “ghosts,” or implicit knowledge existing within any organization that never makes it to documentation. Ghosts affect companies in both data and people spheres, making it challenging to modernize legacy architectures or bring new talent on board. Even more, it makes using data a challenge.

whitePaper | August 1, 2022

The Graph database is fundamental to driving a much-needed breakthrough in the world of Master Data Management (MDM). Until now, traditional MDM systems have imposed strict rules and structures on how these projects are managed. This has cost enterprises dearly in terms of wasted time and resources and has been a major contributory factor to the failure of many MDM initiatives. Graph has changed all of that, allowing modern MDM platforms to completely redefine how master data is prepared for insight and used to deliver tangible business outcomes.

whitePaper | December 22, 2022

The key objective of setting up data mesh or data fabric architecture is to enable the availability of quality data in a timely fashion to the right people in the right format. A data fabric is an architecture framework and a set of data services that provide frictionless data capabilities across a choice of endpoint applications or services spanning hybrid or multi-cloud and on-premises, by using rich metadata foundation and artificial intelligence/machine learning (AI/ML) automation.