Why Consider a Hadoop to Databricks Lakehouse Migration?
Hadoop offers the option to maintain huge on-prem workloads but enterprises need to migrate this data into cloud-based managed services...
Point72 Asset Management is a global firm that invests in multiple asset classes and strategies worldwide. They operate across a few different business lines and handle multiple portfolio funds. The company prides itself on proprietary, state-of-the-art investing methods. Their quantitative investing solution designs and implements computer-driven trading strategies that are based on both publicly and privately available data.
Point72 Asset Management needed a data processing pipeline to deal with the complex accounting and reporting aspects related to managing investor capital. The varying characteristics of the different portfolio funds (such as fee structures, tax implications, and trading life-cycles) resulted in an urgent need to address the deficient operational performance and limitations of the data processing architecture. Of utmost importance were the reliability and security of the system throughout the evaluation and necessary updates without interrupting any existing business workflows.
The main operational problems originated from the inefficient design of the data processing architecture, for this Blue Orange Digital proposed a two-step assessment strategy. In the first phase, the core components at fault were identified and alternative technologies were investigated for their suitability. Critical components of the system that were negatively affecting reliability and performance were rewritten and stabilized by effectively employing the strengths of Scala & Akka technologies. In a second phase, a more efficient data architecture was designed, together with a proposal for a gradual transitional migration plan.
The new technology proved to be a successful decision resulting in a more performant data architecture. Especially in the computationally demanding environments brought by hedge funds, critical attention is needed for specific client requirements, data formats, and overall restrictions of the system. By providing the client with an accurate evaluation of more efficient tools (such as Scala and Akka), we were able to solve their immediate issues while helping to ensure that their system is adaptive for their future technology choices.
It takes into account the main features that are important for the customer, namely, it offers stability and performance for existing workflows, provides ease-of-maintenance, and extensibility capabilities for future needs.
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Josh Miramant is the CEO and founder of Blue Orange Digital, a data science and machine learning agency with offices in New York City and Washington DC.
Miramant is a popular speaker, futurist, and a strategic business & technology advisor to enterprise companies and startups. As an example of thought leadership, Miramant has been featured in IBM ThinkLeaders, Dell Technologies, Global Banking & Finance Review, the IoT Council of Europe, among others. He can be reached at firstname.lastname@example.org.
Blue Orange Digital is recognized as a “Top 10 AI Development and Consultant Agency,” by Clutch and YahooFinance, for innovations in predictive analytics, automation, and optimization with machine learning in NYC.
They help organizations optimize and automate their businesses, implement data-driven analytic techniques, and understand the implications of new technologies such as artificial intelligence, big data, and the Internet of Things.
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