COVID–19 Data Set Modeling and Analytics | Starschema

COVID–19 Data Set Modeling and Analytics

Most successful companies are very good at monitoring the factors that influence their business and responding to changes with fast and effective decisions and actions. In normal times, this is sufficient to ensure the company runs efficiently, effectively, and delivers on financial expectations. These are not normal times.

The COVID–19 pandemic has introduced new factors that affect nearly every business. There is no precedent, no case studies and no best practices to guide the way. Instead, companies must look at the available data — both internal and external— and try to understand how that data can be used to determine how the business is currently being impacted, how it is likely to be affected in the future, what are most likely scenarios that will play out, what can be done to counter those scenarios and take advantage of hidden opportunities in this rapidly changing environment.

Data modeling

New relevant and reliable data sources will be added to this data set as they come available and it will be constantly updated and revised. The pandemic is a moving target and will remain so for the foreseeable future. A good model can help identify trends, alert us when things are changing, show us how fast they are changing, and do so at various levels of detail.

These models — and the visualizations and dashboards they power — can be particularly helpful in evaluating

  • supply chain dynamics
  • demand planning
  • HR and location vulnerabilities
  • financial impacts

By integrating the Starschema COVID–19 Data Set with other related data — both internal and external — executives and managers can better understand the impacts at a deeper level and make business-critical data-driven decisions based on answers to newly relevant questions:

  • What geographic areas are affected, how badly, when will they begin to normalize, and how quickly?
  • What areas are at risk?
  • What areas are threatened by a possible recurrence?
  • How are government policies affecting each area and what effect will potential future policy changes have on the business?
  • Who in your organization is at risk and how does this risk affect the capabilities of the organization?
  • Who can be reassigned to ensure the most important functions and projects aren’t impacted?
  • How is working from home impacting projects — good and bad?
  • Which projects are at risk now and which are likely to be in the future?
  • How does working from home impact operational costs?
  • What supply chains, distribution centers, and customer channels are at risk now, and which are likely to become at risk in the future?

The Starschema COVID–19 Data Set Modeling and Analytics Solution

Through the work of collating, curating, and unifying the data we developed a nuanced understanding of the data, its biases, and how to best work with it to gain meaningful insights. Our solution teams are led by a senior data scientist with long-standing expertise in clinical epidemiology and the analysis of viral outbreaks.

Key Benefits

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Greater visibility of the factors affecting your business

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Accelerated decision-making process

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Ability to react rapidly to changing events

Key features

Snowflake access with 300 credits

The Snowflake Data Marketplace, a secure, fully-governed platform for sharing and exchanging data, allows Starschema to easily and seamlessly share data on COVID–19 in near real-time. Public and private sector organizations can connect to the Data Marketplace from within their Snowflake account for seamless integration of the COVID–19 incidence data set and fast query processing.

Access to Starschema COVID–19 Data Set via S3

For use cases that do not require a data warehouse, the data sets are available as flat CSV files via Amazon’s S3 storage service at fixed endpoints. This allows bulk downloads and easy utilization in the customer’s tool of choice.

Data integrations with internal data sources

Integration with your key source system data with the COVID-19 data set, provide context about the data set through a consultation.

Data modeling

Leveraging your key source system data, Starschema’s data science team can build models to answer the questions needed to make crucial decisions

Data visualization and dashboard creation

Real-time interactive visualizations and dashboards built on Tableau, Mapbox, Plotly, PowerBI and other tools reveal key data as it changes to facilitate quick, data-driven decision-making.

The Starschema difference

Experience in large environments

Fortune 100 companies trust Starschema to keep their data pipelines robust, resilient, and reliable. Our experts have been trusted by Fortune 500 companies, governmental organizations and NGOs to visualize operations-critical data in a clear and accessible manner.

Complete data lifecycle management

From ingestion to consumption, our teams of database administrators, data engineers, ETL developers, application developers, and data visualization experts provide a seamless solution for your complete data pipeline.

Flexible service models

Starschema offers platform design and management and DataOps for entire, multi-vendor data pipelines or specific components.

Proven onboarding methodology

With standard processes for deployment, knowledge transfer, and integration with ticketing systems, Starschema ensures faster time to value.

Tools-based approach

Starschema deploys open source and proprietary frameworks, methodologies and tools to provide effective, accurate, and repeatable solutions and services.

Ask the Expert

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Kristof Csefalvay

Kristof Csefalvay is Starschema's VP for Special Projects, having previously served as Principal Data Scientist at Starschema. As a data scientist with over 10 years' experience, he has pioneered AI approaches in epidemiology, earth observation, and digital signal processing. Educated at Oxford and Cardiff, he has worked in data science roles for companies across Europe and the Americas and holds a number of patents in the field of machine learning, AI, and DSP.

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