Big Data

AML: Past, Present and Future – Part II

This is the second installment in a 3 part series. The first installment provides a short background on anti-money laundering. In this installment, we examine common AML problems faced by financial institutions today. The third installment introduces an approach that…
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AML: Past, Present and Future Part I

This is the first installment in a 3 part series. It provides a short background on anti-money laundering for the layperson. AML professionals may wish to skip this installment and go directly to the second and third parts. The second…
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The Value of Data for Philanthropy

The field of philanthropy is in constant search of the next big thing. And rightly so – our organizations must use limited resources as wisely as possible to try to tackle some of society’s most challenging problems. In recent years,…
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Cross-Functional Trade Surveillance

The Keystone to a Holistic Trade Surveillance Strategy Criminals don’t refer to a playbook of best practices to execute a crime. They are creative in their thinking and collaborative in their efforts (including with parties who may not know they…
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Altus SDX: Shared services for cloud-based analytics

The real power in machine learning and analytics is when multiple analytics disciplines are able to work together in concert, sharing data in service of solving more complex and more valuable questions. That’s what Cloudera SDX (Shared Data Experience) enables…
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Breaking down data silos: when SAP alone is not enough

Running a large company is impossible without having an ERP system in place, and SAP business software remains at the forefront in this category. But when companies are looking towards new technologies such as data lakes, machine learning or predictive…
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Data Engineering is Critical to Big Data Success

I mentioned in an earlier blog titled, “Staffing your big data team,” that data engineers are critical to a successful data journey. That said, most companies that are early in their journey lack a dedicated engineering group. And the longer…
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Staffing your big data team

Building the right team is as important as assembling the right IT infrastructure – and the needs differ just as dramatically. A traditional BI and analytics organization consists of three main groups:   Analysts that develop reports often using sample…
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