Adopting a Modern Data Infrastructure for Trading Analytics

whitePaper | October 3, 2022

C-Level executives, do you often feel that you spend a significant amount of time and resources managing costs? Or do you often wonder about the impending costs on IT assets and how to optimize them? Gartner, in a recent survey, has expected that IT services are going to raise this year, with the projected IT spending growth rate being 5.5.% for 2023. With soaring expenses, you need to find alternative tactics to reduce the burden of IT expenses.

whitePaper | August 25, 2022

Everyday user experiences are being completely reimagined. Requesting a ride through an app is better than calling a cab. Buying online is changing the way we go shopping. And gone are the days of waiting in long lines at your local bank. Data within these modern businesses is in constant motion, flowing, in real-time, across systems, environments, and applications every time a user interacts with the system.

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.

whitePaper | June 14, 2022

In a digital-first world, every organization needs a data management plan. Yet, fewer than 25% of nonprofits report having a plan in place. This means data is infrequently shared across departments and rarely used to make decisions or predict future stakeholder behaviors. A data management plan is fundamental to make an impact and an attainable goal regardless of organization sizeor technological capacity. An effective data management plan takes into account your mission, staffing, time, budget, goals, existing technology, and more.

whitePaper | September 28, 2022

Graph data science (GDS) is a scientific approach to gain knowledge from graphs, using the structures of connected data to power predictions, answer questions, and explain outcomes.

whitePaper | January 31, 2020

Many companies have invested heavily in specialized enterprise data warehouses (EDW) and Extract, Transform and Load (ETL) technologies to analyze their operational data. But these technologies were never designed to be truly real-time.They were originally built for batch, and that original design limits how real-timeEDWs and ETL can become. They were also designed to support a focused group ofanalysts, not a larger group of employees spanning operational functions, or even partner and end customers.