Big data evolution: Forging new corporate capabilities for the long term

whitePaper | September 1, 2022

Organizations often adopt a hybrid cloud strategy when deploying their first analytical solution to the cloud. The cloud combines sheer infinite scalability with consumption-based pricing. These are desirable attributes for analytical environments that require scalability and can be very expensive when scaled for maximum capacity over an extended period.

whitePaper | August 23, 2022

Digital transformation has moved businesses from a mode of retrieving and organizing critical information in conventional data stores to a new goal: capturing and storing every bit that passes through the business. The number and diversity of data sources are constantly expanding. New horizons are recognized in data as a raw resource with potential for value creation, even if specific points of value cannot yet be discerned.

whitePaper | February 7, 2020

Multiple studies have proven that, while the business demand for databases grows, operational teams are constrained by traditional, reactive processes. Combined with budgetary pressures, this causes them to fall short in meeting the demand in a timely fashion. In addition, as companies adopt cloud paradigms, operational teams must manage across on-premises and cloud environments with the same resources. To be effective, companies need to shift from a reactive posture to one of standardization and proactive analysis and planning by leveraging intuitive tooling to automate manually intensive and non-value adding activities and to deliver real-time insights.

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 | 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 | December 29, 2022

Every day we are inundated with tables, graphs, charts, and maps explaining everything, including the unemployment rate, COVID-19 vaccination rates, baseball home run launch velocities, and our investment portfolios. When made well, data visualizations can help readers and users find insights and make discoveries. When made poorly, they obfuscate, mislead, or make it difficult for people to use them effectively.