Harnessing and making sense of actionable intelligence hidden within the copious amount of available corporate data is a momentous yet necessary task. With the growing use and increased influence of web-based activity and mobile devices, any strategy that doesn’t comprise of external and internal assessments only delivers partial insight. kasTech Network’s Big Data and Information Management solutions, with their anytime, anywhere and on any device capability, transform corporate and social intelligence into trustworthy and actionable insight by providing the whole picture and by allowing a wide range of opportunities to be explored.

kasTech Network can help empower companies with the ability to maximize insight to transform organizational procedures, such as management processes, operational functions and the creation of new business models. Yet the ability to also yoke key indicators within external data reserves and analyze them independently and in conjunction with internal corporate intelligence can optimize performance by quickly reacting to opportunities as they emerge or before they become problems.

Working with kasTech Network, organizations can greatly improve their understanding as to their strengths and gaps in Big Data readiness. How best to implement Big Data within existing infrastructure, which business initiatives would benefit the most from Big Data, where can the fastest returns be realized and how best to handle any potential barrier all become apparent through kasTech Network’s rigorous evaluations. The end result: A step-by-step framework that accelerates Big Data from being just an aspiration to a fully realized data-driven initiative.

For Big Data or Information Management to provide timely, trustworthy and responsive business intelligence, a strong architectural foundation is pivotal in terms of storing and supplying the information that is the backbone of any Big Data analysis. kasTech Network’s holistic approach takes into consideration structured and un-structured data types, resource pools, business requirements and workload processes. By applying what-if scenarios, co-existence between central repositories of integrated data and standalone databases are bridged and multi-tenancy architecture developed to increase the robustness of functionality.