Three ways data analytics boosts lender margins

whitePaper | November 23, 2022

Artificial intelligence (AI) and machine learning (ML), along with data analytics, are widely seen as a way to tackle everything from daily inefficiencies and low productivity, to advancing healthcare and climate change mitigation. As more organisations look to leverage their data more effectively, demand for people with data capabilities is only going to grow

whitePaper | September 6, 2022

Data is the heartbeat of the modern enterprise. Technology has progressed to the point that data-driven decision making is the norm and data literacy is often prized above all other skills.

whitePaper | November 15, 2019

The potential of artificial intelligence to transform business performance is only now starting to be more widely understood in Financial Services. This is nowhere clearer than in the security domain, where the fusion of big data, advanced analytics and machine learning holds out the promise of startling improvements in cyber defenses through the introduction of Prescriptive Security.

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.

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 | May 5, 2021

Over the last decade, interest in the field of data science has not only increased enormously, but has also changed and developed considerably. In view of the new technological advances and the constant growth of data, we expect Data Science to continue to develop strongly in 2021. We have identified 7 trends that will be relevant for the coming year.