Data Science Solutions
Assess → Recommend → Partner → Build
The five-step engagement.
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The value of data to effectively deliver your business value proposition is greater than ever. Just as businesses that fail to adopt efficiency-driving software are driven out of the market, deploying data science solutions in the face of sophisticated, disruptive, scalable competition is critical. Whether you are a startup or an established industry presence, decision-making that is fast and reliable only happens when you get your data right.
Phase 1 of a partnership with Echelon DS consists of a five-step engagement to evaluate your team’s current systems architecture and recommend the data science service that would cost-effectively provide the most benefits. Assessments deliver a holistic review of data infrastructure, technical systems, security practices, and current data science applications, comparing each to up-to-date industry best practices.
1: Architecture & Systems Review
The Architecture & Systems Review is a comprehensive evaluation of the current state of your company’s infrastructure and application layers based on factors critical for an organization to implement data science and machine learning systems successfully.
The Architecture & Systems Review is broken into two high-level categories: (1) Data Architecture and (2) Technical Systems.
2: Data Science Review
The Data Science Review is a nuanced evaluation of existing data science applications and high potential future implementations. The Data Science Review process evaluates existing practices toward Data Processing, Data Exploration, Predictive Data Models, Real-Time (online) Predictive Modeling, Real-time (online) optimization.
3: Data Science Recommendation
The Data Science Recommendation discusses the high-level areas where Data Science, Machine Learning, and AI are most valuable to your organization. It describes how machine learning can be used to specifically drive improved business decisions, and expected development timelines, costs, and expected impacts. This sections also includes a discussion of how for your organization can bring the Machine Learning discipline into the business.
4: Machine Learning Resources
Regardless of the organizational approach, your team will benefit from existing employees gaining additional working knowledge of machine learning. This will both allow them to develop tools, as well as provide valuable context when integrating developments from other data science sources. We culminate the report providing recommendations to machine learning resources based on wide usage within the data science community.
5: Next Steps
In this final section of the review, we provide next steps for your organization to continue upon your data science development path. Echelon DS provides custom solutions as an external AI collaboration partner, consulting services to help develop and train your internal team, and consulting to help hire technical team members. Read more about how we’ve partnered with organizations to create data-driven success here.
Case Studies
We aren’t here to tell you how to run your business. We’re here to support you in building data intelligence that helps you make better decisions.
See what our customers are saying.
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