Automation without intelligence doesn’t remove work. It just moves it. Many investment platforms automate surface-level workflows: file ingestion, reporting jobs, scheduled tasks while leaving the hardest problems untouched. Exceptions are still handled manually. Errors are discovered after impact. Risk is reviewed after exposure. This creates a dangerous illusion of efficiency. In a high-volume investment system we worked on, operational teams were … Continue reading Why AI-Driven Intelligent Automation Matters More Than Workflow Automation
Category: Data Analysis
Why Report-Driven Analytics Fail: The Case for Real-Time Analytics for Investment Platforms
In investment systems, delayed insight is often mistaken for acceptable latency. Reports arrive an hour later. Reconciliations happen end of day. Risk is reviewed after execution. On paper, nothing looks wrong. In reality, decisions are already behind the market. In one regulated investment environment we worked with, investment performance analytics across asset classes: shares, funds, cash deals, and loans relied on manual or … Continue reading Why Report-Driven Analytics Fail: The Case for Real-Time Analytics for Investment Platforms
A Detailed Procedure For Migrating From Hadoop To Apache Spark
A variety of data from different resources gets generated because we have a huge volume of data and this process remains in continuous flow which will create more data in future. This huge volume of data is called Big Data and storing this Big Data is a problem for us. Hadoop became one of the … Continue reading A Detailed Procedure For Migrating From Hadoop To Apache Spark
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