Do No Harm Guide Centering Accessibility in Data Visualization

whitePaper | March 29, 2023

Migrating to a new analytics environment can be a complex, timeconsuming and resource-intensive undertaking. Significant investments have been sunk into existing analytic environments, and migrating to a new platform can involve months of effort. When organizations go to this level of effort and expense, ideally, they should achieve more than simply migrating the existing environment. A migration provides an excellent opportunity to look to the future, rethink the environment, and deliver new capabilities to the business that can improve efficiency and serve as a source of competitive advantage.

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 | September 23, 2022

For Intel’s complex factory environments, quickly identifying tools that are operating below their optimal capacity and finding the root cause is crucial for maximizing production output. With thousands of tools involved in production and each manufacturing tool running from one to 50 operations, there are tens of thousands of tools and operations to monitor, analyze and adjust. Knowing where to focus engineering efforts is a monumental challenge.

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.”

whitePaper | August 25, 2022

As they seek an edge in their trading and investment activities, hedge funds and other sophisticated trading firms are looking to harness new sources of insight that can allow them to identify and exploit emerging market and industry opportunities. But many organizations are saddled with a disconnected sprawl of legacy systems that are unable to handle the demands of today’s fast and often volatile markets.

whitePaper | April 27, 2023

Data analytics are used to test controls and validate that business risks are managed. This would generally occur at a point-in-time when an assurance activity is scheduled. Rather than test a number of transactions, the entire population of transactions can be reviewed for greater coverage. Data analytics includes automated tools such as generalised audit software, test data generators, computerised audit programs, specialised audit utilities and computer-assisted audit techniques (CAATs).