Fast Data Streaming

Student: Kita Abuodha, 2021-2022

Sponsor: Avanade, Seattle, Washington

In today’s data-driven economy, businesses seek to harness this data to improve decision-making, revamp and refine operation and create new streams of revenue. However, the data journey is often predicated on data moving slowly and the acceptance that query responses reports may not be real time.The challenge emerges in use cases where real time analysis and recommended action is necessary. For example, emergency situations, fraud detection, machinery maintenance, and methane detection to name a few. The problem this project is trying to solve involves identifying market opportunities for fast data by evaluating decision latency, determining criteria for fast data usage by assessing profile use cases and defining successful outcomes so that the proportion of fast data implemented in a clients operations optimizes economic value for clients.