DMI Big Data Platform

Turning data into actionable insights

Our comprehensive operational analytics platform is designed to meet your big data needs, taking into account your business processes, technology landscape and specific data challenges around volume, variety and velocity. The Big Data Platform uses the COTS (commercial off-the-shelf) or open source tools best suited to the solution.

What can our Big Data Platform do for business?

The Scenario

A business line manager and his team have been reengineering business processes to become more customer-centric. As business processes become automated and advertising for his products has gone digital, he is capturing all sorts of customer data. The data comes from both structured and unstructured sources, including web traffic logs, transactional data and even social media logs. In fact, the manager now has more customer data than he knows what to do with, and this has resulted in a new set of challenges. His team needs a solution that can not only store large amounts of data, but also process this data.

Organizing the data

So how can the business line manager process all that data and transform it into something meaningful? Our Big Data Platform sorts and tags unruly data, helping him to identify which pieces of data he can actually use to his advantage. Using a hybrid system, data from external sources (such as traditional RDBMS or third party APIs) and information stored in big data storage is accessed through a DMI Analytics Engine layer. This layer can combine, transform and aggregate data. Aggregated data can be loaded back into the big data storage or loaded into high performance databases for integration with analytical tools, and then delivered to users through a business intelligence reporting and visualization platform.


From this point, the business can now begin to use traditional BI tools to analyze the data, just as they have with more traditional enterprise data warehouses. In addition, the business line manager can now explore other options such as predictive analytics, analytical modeling or real-time reporting engines.

Solution Components

Big Data Storage

Storage systems that offer scalability, high availability to data and redundant data storage.

Analytics Engine Layer

Applications that can combine data from different sources, such as big data storage, data warehouses and external APIs, and then process, aggregate and produce new datasets based on the results.

High Performance Database

Low latency databases that can scale to provide quick access to queries and enable connectivity to reporting and visualization platforms.

Enterprise Data Warehouse

Traditional databases that store integrated data for reporting and analyzing. These typically have some reporting features.

Business Intelligence Reporting and Visualization Platform

Tools for transforming raw, unstructured data into reports to create actionable strategies for better business decisions.

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