ALA uses Cisco UCS integrated infrastructure for Big data Analytics. Cisco have Big Data SKU bundles, Big data starter, High performance, Performance Optimised, Capaticity Optimised and Extreme Capacity options, thus providing scaleable solutions to organisations with different capacity requirements. Also the Nexus networking solutions provide industry leading connectivity to support our proposed solutions.
MapR and ALA work together to deliver world-class big data and analytics solutions to help financial markets firms quickly get started with big data projects and achieve faster time-to-value. MapR delivers on the promise of Hadoop with a proven, enterprise-grade platform that supports a broad set of mission-critical and real-time production uses. MapR brings unprecedented dependability, ease-of-use and world-record speed to Hadoop, NoSQL, database and streaming applications in one unified big data platform. MapR is used by more than 500 customers across financial services, retail, media, healthcare, manufacturing, telecommunications and government organizations as well as by leading Fortune 100 and Web 2.0 companies. Investors include Lightspeed Venture Partners, Mayfield Fund, NEA, and Redpoint Ventures.
HPE & Vertica Compliance Solutions
HP has developed award winning software specifically designed to provide the best results for combining structured and unstructured data.
HP’s HAVEN solution is a combination of 3 key elements: A Hadoop datalake (see below), Idol unstructured data processing layer and a Vertica database for blazingly fast analytical queries.
Vertica is HP’s industry-leading Big Data platform for structured and semi-structured data, regularly beating Teradata, Exadata, Netezza and Green Plum in Proof of Concept comparisons of speed and performance. It’s a next generation columnar, Massively Parallel Processing (MPP) architecture database with high availability and strong compression rates, with customers including Facebook, Twitter and several large banks.
Idol is HP’s unstructured data analytics platform which can ingest and analyse all forms of unstructured data, from voice to video and machine logs to social media. This allows for identification of people within video files, tone and sentiment in phone recordings and many other capabilities. This is an important part of analysing the emotional content in source data using our Emotional Finance algorithms and statistical models.
Hadoop is an open source system for storing and working with very large volumes of data. Its most famous component is the Hadoop Distributed File System for storage, which is extremely fault tolerant and allows for very high throughput access to these huge data sets. By processing query logic close to the data rather than moving data closer to the logic, processing times are significantly reduced. In addition, it’s extremely reliable, due to automatically maintaining multiple copies of the data and automatically redeploying processing logic in the event of hardware failure.
Hadoop’s ‘datalake’ concept has become popular in large institutions by virtue of it being an extremely effective way of consolidating and processing very large and varied data sets across the entire organisation. Within the reference architecture in this document, we would be using a Hadoop datalake as an initial step to pooling and transforming our data for analysis with Vertica and Idol.
Hadoop exists in 3 distributions, which are developed by 3 different companies (Cloudera, Hortonworks and Map-R). These are largely interchangeable, but there are specific advantages to each one for particular use cases. As a result, we will be a distribution-agnostic solutions partner and tailor our Hadoop offering to the specific needs of the customer.
Visualisation of Big Data Analysis is critical to the success of bring the data to the business use level. Data needs to be presented in an easy to digest format, with ability for the user to do some customisation of view for specific business applications.
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OptiRisk specializes in optimisation and risk analytics and is renowned for its research and development of models and software systems in these domains. In the domain of Sentiment Analysis, OptiRisk is a partner of Thomson Reuters and RavenPack. The company has researched and published the Handbook of News Analytics in Finance and has developed the Sentiment Analysis Toolkit (SAT) which consolidates market data and news (meta) data and connects sentiment analysis to financial models. The other domain of specialisation of OptiRisk is Stochastic Optimisation; the company is a certified IBM partner (Optimisation Modelling) in the UK and in India. In the domain of optimisation the company has developed a family of Algebraic Modelling Language (AML) tools which are specifically designed for modelling and solving a wide range of stochastic programming and robust optimisation problems. The company has a track record of successfully delivering tailored applications in finance, logistics and energy systems.