Stories of Slalom and Google Cloud
Cloud-powered impact
Slalom is a two-time Google Cloud Breakthrough Partner of the Year, and we've never been more grateful for the partnership than in the months since the COVID-19 crisis began. Inspired by Google Cloud's mantra, "serve, don't sell," we've had incredible opportunities to help clients respond and adapt in transformational ways.
We're proud to share these stories of making a difference with Google Cloud.
social distancing
How long is long enough?
We're partnering with the Department of Technology and Governor's Office of a large US state to track how well social distancing is working to combat COVID-19. Our experts in Google Cloud, Snowflake, data science, engineering, and data visualization are contributing relevant, valuable, and timely information that enables situational awareness, informs planning efforts, and broadly improves decision making. Slalom’s data curation and dashboarding efforts have been so valuable that our reports are being shared with the Governor on an ongoing basis to support crucial policy decisions.
small business
Enabling online fulfillment
When physical storefronts shuttered across the US, small businesses have had to get creative with online sales and fulfillment. One of our clients offers a turnkey nationwide fulfillment network designed to help merchants of any size easily position products closer to end customers for a fast, inexpensive, and reliable order-to-delivery experience. Slalom is helping the company rebuild its core platform on Google Cloud with a focus on scalability, performance (including automation), and the enablement of robust features for order management and warehouse management.
media and entertainment
Data insights from a new streaming platform
With all of us spending more time indoors, it’s no surprise that streaming on media platforms has increased exponentially. For a major broadcasting company and its new streaming service, understanding how users are interacting with the platform in real-time has become mission-critical. We're collaborating to build an analytics hub in Google Cloud, then port over critical data and develop the architecture for flexible data marts on BigQuery. Our client's executive teams will be able to ask and answer questions about critical KPIs utilizing the custom Tableau dashboards built by the Slalom team.
enterprise innovation
Responding to accelerated demand
Our client is a leading software and services-led enterprise provider in the financial, retail, hospitality, telecom, and technology industries, with business in 180 countries. With the COVID-driven rise of food delivery platforms, which most analysts expect will stay elevated for the foreseeable future, our client's restaurant customers need support to quickly scale on-demand ordering. By modernizing our client's technology architecture, quality measures, and deployment processes on Google Cloud, we're not only improving the products, tools, and processes that enable them to respond quickly to their customer's ideas—we're helping them lead with innovation.
online gaming
Harnessing petabyte-scale customer insights
Online gaming is experiencing dramatic growth during lockdown efforts to combat COVID-19. We're helping a leading game company optimize and transform core components of their business in Google Cloud. Engagements include: migrating the company’s core KPIs to a modern data & analytics platform, building a scalable Kubernetes-based cloud data engineering and DevOps framework to handle petabytes of customer insights, creating new ML recommender models for in-game promotions, moving DR environment for one of the top free-to-play apps in the world from an existing data center, and developing self-service analytics solutions in Looker and Tableau.
artificial intelligence
Helping underprivileged students complete college
A not-for-profit organization focused on closing the college completion gap wanted to do more with its 12 years of data on student journeys from high school through college degrees. With Google Cloud's state-of-the-art data, analytics, and machine learning capabilities, Slalom implemented new data pipelines to ingest the organization's data into BigQuery. Then we prototyped machine learning models to classify student success and designed future-state data collection practices to enable predictive analytics. The result is an ever-improving understanding of key drivers behind student success, so the organization's network of coaches and community members can take proactive action to improve college matriculation and completion rates.
responding to disruption
Migrating a search and merchandising app
With the retail landscape shifting to e-commerce, a software client focused on helping its customers deliver personalized experiences to their customers saw the value of migrating to Google Cloud. We're helping migrate the company's primary environment and enable auto-scaling with the automation of infrastructure, deployment, and configuration. This begins with delivering a minimum viable product (MVP) Google Cloud architecture, building foundational components, establishing connectivity between Google Cloud and AWS, and demonstrating interoperability.
healthcare
Designing the caregiver model of the future
We're helping a healthcare client design the caregiver model of the future on Google Cloud. First, we're helping the organization strengthen its application development pipeline and implement cloud governance. With our expertise in infrastructure and data layers, we're also helping to modernize the architecture and transition existing applications to Google Cloud, allowing the company to develop digital-first tools for virtual care, create connections, and make data-driven decisions to determine capacity and how space is used.
life sciences
Finding breast cancer patterns with machine learning
We partnered with the American Cancer Society and Google Cloud to use machine learning to discover patterns in breast cancer tissues. Now, the American Cancer Society is set up to discover insights that could help prevent and treat breast cancer. The organization is also equipped to use machine learning to analyze other types of cancers in the future. After ACS, we wanted to do more. We recognized a model worth repeating. A model that could change the world.
