InstaData Systems: Harnessing the Power of Data

The big data analytics landscape has been transforming like never before. Cloud computing technologies and out-of-the-box business intelligence software are driving business operations, improving business value and profitability. However, except for the bigger corporations, often there is “a dearth of resources that smaller businesses or government institutions can deploy to translate business knowledge into business analytics tools,” says Dr. Angshuman Guin, Co-founder and Partner, InstaData Systems. This is where InstaData comes in. Bridging this gap, the company provides an environment where they employ in-house thought leaders and domain experts to communicate with a business and help them translate concepts into successful implementation. “We reduce the need to take away already scarce resources in businesses from performing their existing business functions and driving requirements gathering and software development.”

As a Big Data analytics company, “InstaData helps businesses harness the power of data to move beyond descriptive and diagnostic analytics to predictive and prescriptive analytics.” With their robust in-house domain expertise, the company brings together cloud computing experts, data scientists, big data experts, statisticians, and visualization experts to build Decision Support Systems that enable problem solving by diagnosing root causes and effects and anticipating and optimizing outcomes, behaviors, and processes.

InstaData analytics platform is built with big data architecture to work seamlessly in cloud-based environment. The architecture leverages the scalability of a cloud platform such as AWS. “For example, the same computational platform that is used for real-time processing can be scaled up on demand, with no additional development requirements, when there is a need for additional single use heavy duty processing, such as reprocessing of archival data to match an upgraded data handling algorithm,” explains Dr. Guin. This architecture allows for minimal initial investments, while allowing for incremental increases in resource deployment as necessary, with no direct end-of-life technology overhaul costs.

Dr. Guin also mentions the ability of the platform to process real-time data collected from sensors, by filtering, cleansing, and validating the data from sensors on-the-fly with advanced predictive filtering algorithms.