PRESTO-Credit Nirvana, assist you quickly, easily and cost effectively deploy and scale cloud-based and on-premise Big data analytic solutions for real-time decision management. It enhances organizations ability to infuse precision and speed into your decision making processes, operational excellence and customer satisfaction. The product leverages and extends STATS’s industry-leading decision management tools for embedding business rules, analytics, optimization and adaptive control to automate and improve strategies. It encompasses the latest innovations in open source and cloud-based technologies to allow businesses of any size to apply customer-centric and operational solutions easily and cost-effectively.
PRESTO is a unique product providing an integrated product of big data extraction, predictive analytics using PMML complaint scoring engine and data visualization. The product leverages and extends STATS’s industry-leading decision management tools for embedding business rules, analytics, optimization and adaptive control to automate and improve strategies. It encompasses the latest innovations in open source and cloud-based technologies to allow businesses of any size to apply customer-centric and operational solutions easily and cost-effectively.
It is a first of kind of product which has integrated Big Data management + Predictive Analytics and Scoring Engine + Data Visualization.
This layer includes integration of multiple big data sources, data extraction& transformation and loading of the data on to Hadoop distributed file system as explained below. The built-in APIs support the processing of any data type like flat data, NoSql data, relational data, object-oriented data & hierarchical data. Integration of Multiple Big Data Sources: PRESTO's data integration layer APIs helps in easy integration with multiple data sources (customizable to vendor specific data storage systems). The integration can be executed without impacting and changing the client production data systems. In general, goal of the integration layer is to extract and convert the data into a single format appropriate for analytics.
Data Extraction & Transformation: This built-in ETL process involves extracting the data from the multiple source systems. The data extraction APIs helps in streaming of the data from the integrated data sources to the destination Hadoop file system and applying any data validation logic on-the-fly depending on the requirements of the organization.
The transform stage applies a series of rules or functions to the extracted data from the multiple sources to derive the accurate for loading into the target file system loading on Hadoop Distributed File System (HDFS): The load phase loads the extracted data on to Hadoop distributed file system in real time for parallel processing. Depending on the requirements of the organization, this process can be easily customized in data integration layer using its APIs.
A predictive analytics execution engine based on the PMML (Predictive Model Mark-up Language), an open standard developed using Modeling tools like SAS, SPSS & R etc. With this, any predictive models can be deployed to score the new data in real-time using Web-Services. The Scoring Engine delivers intelligent, real-time scores or recommendations to visualization layer during user interactions to support timely decision making. It also allows for ease of use in both applying models in real-time and updating models as new information develops.
PRESTO’s web based visualization layer can be configured & customized to any verticals depending on the organization requirements. It provides instant and interactive analytics for an actionable decision support. The High flexibility of PRESTO's visualization layer helps in preparing standardized reports and reducing report creation times. StatLabs has horizontal zed the PRESTO's visualization or reporting layer for marketing, sales & operations and financial & risk management for needs of its various clients.
To request information, contact us and enter your information and we will respond directly to you.