Microsoft Azure is cloud-native and runs across multiple regions, making tracking its metadata complex and challenging. The current dashboard involves ad-hoc SQL data queries which is inefficient and inaccessible to non-technical users. Additionally, the dashboard doesn’t provide useful visualizations for analysis. To address these issues, we developed the Software Deployment Tracker which is designed for all team members, from project managers to engineers. Our solution empowers the Microsoft Azure team to effectively monitor global deployments by querying and visualizing deployment data instantly without writing any code.

Arrived Homes is a real estate investment start-up that allows anyone with $100 to invest in property. Arrived Homes had a manual sorting process for their acquisition process where their buyers sifted through thousands of MLS listings to find eligible properties, costing them time and missed opportunities. We developed a tool to automate Arrived's acquisition process with an intuitive interface displaying data aggregated from sources such as Zillow, Redfin, and Century 21, along with an algorithm to suggest properties with the highest expected return. This allows Arrived to increase the acquisition process and scalability to enter new markets moving forward.

To help the Xbox team determine which technology performs better at detecting unsafe images, our project builds a comparison system that evaluates the performance of two image detection algorithms. The key results include: 1) a system that takes user images and generates similarity scores automatically; 2) an analysis pipeline that analyzes the data in Python and is live-connected with Power BI to show the key metrics. With our pipelines, the Xbox team can easily plug in images and see the comparison results on the dashboards. It eventually improves user experience by helping moderators remove the bad content effectively.

CuriosityBased fosters curiosity within the workplace to help teams and companies build trust, collaboration, and communication. One of their tools is an assessment based on their 7 Forms of Respect™ framework. This framework helps individuals identify how individuals and teams demonstrate respect in the workplace. Their previous system for calculating and visualizing assessment answers was manual and extremely tedious. Our team was asked to automate this process and redesign the results delivery. The resulting product will save time for the CuriosityBased team and allow them to put more effort into services and consulting.

Data-Driven Waste Management Solutions with trashcan pick-up frequencies are determined primarily by empirical observation. Seattle Public Utilities (SPU) sought a data-driven solution to better estimate waste levels and thus optimize waste bin placement and service scheduling. Our team detailed shortcomings of organization data collection and infrastructure, collaborated with stakeholders to create an appropriate data collection system, and created an optimization model to minimize costs associated with each collection route. Our efforts intend to reduce SPU’s expenses, support a cleaner city, and bolster SPU’s future information management practices to allow further opportunity. 

The Microsoft Mixed Reality team currently lacks a centralized tool to manage policy documents. Our team focuses on recommending the best document management system to our sponsor that has functionalities including automated tagging, access control, version control, and notification. We have taken into consideration factors such as financial cost, usability, scalability, and user experience. Our project provides our sponsor with essential research findings on different DMS tools and valuable insights into improving their document management process, indirectly contributing to improving the efficiency of the overall policy document management workflow.

Anecdata is a citizen science platform that allows users to upload, download, and browse content pertaining to their surroundings and environment. We worked on improving the user experience and information architecture of the platform. We achieved this by working on requirement gathering (surveys),  conducting usability analysis, creating user personas, and creating a system map. We further recommended a few features to improve the taxonomy and user flow of the platform. We believe that our work has positively impacted the lives of people who take a deep interest in the environment and use a platform like Anecdata to connect with like-minded people.

Microsoft’s Azure Machine Learning platform is currently experiencing a growth in its number of users, creating an area of opportunity to sustain these incoming users month over month. We explored this opportunity by using a hypothesis validation framework to examine what efforts can be made to improve customer retention, focusing on customers who are still in the early stages of their development. Through this framework, we were able to identify key user behaviors and pain points that led to churn. These findings have been used to suggest changes to the platform to improve product experiences and usability for customers.

Financial institutions have long been looking for quantitative methods to analyze tens of thousands of jargon-filled documents generated in the highly dynamic market. Thus, MarketOwl is the solution that can collect and assimilate these text data into measurable indicators. Through analyzing SEC filings and earnings call transcripts with its NLP engine, MarketOwl provides insights such as sentiment and credibility trends and transforms them into curated dashboards. MarketOwl empowers portfolio managers to make faster and better decisions with integrated and trustworthy company information and make more profits for their company and clients.

Our team worked with the Microsoft Azure Machine Learning product team to improve the retention of deeply engaged customers on the AML platform. The project involved both qualitative and quantitative analysis of customer usage patterns, including customer interviews, telemetry data analysis, hypothesis building and testing. The result of our analysis serves as a good foundation to understand the needs and pain points of the customers and to come up with strategic ways of moving forward. It has the potential to help improve the user experience of the AML platform and allow AML to gain more competitive advantages in the market.