Augment your Data Science and Data Analytics Initiatives with right framework and teams
Tridiagonal Solutions Process Analytics Group, supports Data Science and Manufacturing Data Analytics initiatives of the organizations through its Guided Analytics Services & Solutions Framework. This framework enables organization to devise KPI-based analytics strategy and selection of right approach / methods / solutions for successful implementation at an enterprise level. We fill the gap in terms of skillsets, knowhow and best practices in the data analytics space and help companies to get started in its data analytics journey. Our multi-skill teams consist of Domain experts in Chemical / Mechanical engineering with a strong industry exposure in Oil & Energy, Chemicals, Pharmaceuticals, Metals & Mining, Cement sectors. The essential combination of data engineers, data scientists, and application engineers is instrumental in implementing data analytics solution at our customers end. We have the suite of solutions (Data analytics platform), which we implement as a part of our services.
Core Data Science Group - ML Modeling Center (MMC)
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Analytics implementation Strategy – Roll-out plan with Returns on Analytics (ROA)
Building Analytics & Data-driven models for various applications (processes) – Model construction, application / validation and implementation – Lab/ R&D, Process Dev., Manufacturing, Supply chain, etc.
Department-level Value creation (Lab, Process R&D/ Dev., Quality, Operations)
Augmented modeling for complex processes (Mechanistic + Data-driven), working with SMEs for advanced analytics (level 4, 5)
Custom Application for specific purpose – Templatizing Analytics
Model Management & Tuning – Enhancing the value of models
Knowledge-creation and building Analytics Culture / Champions – Analytics Transformation
Center of Analytics (COA) – Management of Data Insights
Extended team for Data Mining and Analytics – Managing multiple plants/ assets
Dynamic reports and KPI/dashboards for global department heads (Asset-level/ Process level) – R&D, Quality, Operations, maintenance, CXOs
Working with Plant / Operations head on Operational effectiveness and productivity analytics
Working with MSAT team on Process & Optimization Projects using Data Modeling & Analytics
Back-end ‘Analytics Production Team’ to the Data Science/ Digitalization leaders
Establishment of Best Practices for Data Analytics
Knowledge-building Workshops / Programs
Hands on training on Data Analytics – Data Preparation & Pre-processing – Data Cleansing, Conditioning, descriptive statistics