Hybrid Cloud and Data Analytics for Financial Services: Maturing the Model

whitePaper | April 1, 2021

Metadata is more important now than ever. New technologies have enabled businesspeople who have traditionally not been analysts to work with data. The consumerization of IT means people expect systems to be intuitive and require little training. With so many people using data to support so many kinds of decisions, it’s critical that your data is described, defined, and understood.

whitePaper | January 20, 2023

Organizations increasingly recognize that accountability through the implementation of a data privacy management program (DPMP) is essential to operate effectively in the modern digital economy. For many years, the focus of organizations in implementing a DPMP has been mainly to achieve compliance with data protection requirements. Today, many organizations have undergone a shift in understanding and realize that a DPMP is as critical for risk management and compliance as it is for enabling data strategy, building customer trust, winning business, and attracting company investment.

whitePaper | September 26, 2022

Communications service provider (SP) traffic volumes are progressively increasing as networks evolve, user devices gain greater capacity, and applications engaging with advanced network data such as that from the 5G standalone (5G SA) network exposure function (NEF) start to deliver on customer expectations. Cloudification of network functions — virtualized network functions (VNFs) and cloud-native network functions (CNFs) — is placing new burdens on old systems and processes not designed to manage intent-based network architecture. Silos of data locked within many installed systems keep transformation efforts from reaching anticipated objectives.

whitePaper | July 25, 2022

Experts estimate that the average person generates more than 1.7 MB of digital data per second, amounting to over 2.5 quintillion bytes per day. However, as the world becomes increasingly digitized and networked, experts predict that, on average, people will produce 463 exabytes of data per day by 2025.

whitePaper | May 27, 2021

In many organizations, we need more collaboration between businesses, analytic teams, application developers and IT operations. These teams often work with data in silos and end up duplicating efforts, failing to integrate, or missing opportunities to deliver value from data. In addition to siloed efforts, data scientists are also faced with ever-increasing volumes and speeds of data. And the reality is they’re expected to answer questions just as fast as - or faster than - before. It’s important that we’re using the right data and the right techniques to ensure optimal outcomes. Download this guide to learn more about SAS and open source.

whitePaper | March 12, 2020

Operational Acceptance Testing (OAT) is the penultimate phase of Acceptance Testing in a Software Testing Life cycle and is the last defence line between a software development project and deployment of software on production. FFor decedes, Operational Acceptance has been undermined and misunderstood. Where User Acceptance has been written about and hailed as a final phase in testing before production. User Acceptance is but one side of the coin, Operational Acceptance is the other.