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Enhancing triparty repo transactions with IBM MQ for efficiency, security and scalability

IBM Big Data Hub

This reduces the risk of errors and miscommunications, which can lead to significant losses in the financial industry. This makes it easy to incorporate new features and functionalities into the triparty repo dealing system, allowing it to adapt to changing market conditions and customer needs.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

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IT leaders adjust budget priorities as economic outlook shifts

CIO Business Intelligence

Analyst firm IDC expects more of a moving target on tech budgets due to market volatility, the strength of the US dollar, inflation rates, and continued slow global growth due to economic drag by China and other key countries. Focus on risk management, he advises, and “have a little faith in your CFO and CEO.

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AML: Past, Present and Future Part I

Cloudera

Following the September 11th attacks in 2001, focus shifted towards fighting terrorism and terrorist funding. The financial system evolves as new business models emerge and new instruments are introduced into the market. History tells us that the AML landscape is constantly changing.

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Data Science, Past & Future

Domino Data Lab

Now, Google is spending what, 10 figures marketing TensorFlow? One application of this is regarding data governance. That leads to what Andrew Ng has famously called “the virtuous cycle of data.” That was the origin of big data. Data governance on big data, that was starting to happen.

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Themes and Conferences per Pacoid, Episode 12

Domino Data Lab

Consider the following timeline: 2001 – Physics grad students are getting hired in quantity by hedge funds to work on Wall St. following a breakthrough paper or two, plus changes in market microstructure). to join data science teams, e.g., to support advertising, social networks, gaming, and so on—I hired more than a few.