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Machine Learning Discovery Study: 4-wk Assessment

The Data Analysis Bureau

In four short weeks, T-DAB will deliver an Machine Learning Discovery Study to accelerate your data science & machine learning projects using Azure services.

The Data Analysis Bureau (T-DAB) is a data science and engineering innovation agency specialising in the development and delivery of bespoke, high-end machine learning solutions.

T-DAB will guide you on your data & analytics journey through our Discovery Study; bringing industry and domain best practice and insight to your business. By applying our Machine Learning Transformation Framework, we’ll help you demonstrate the potential of data in your business.

T-DAB will help you to: * identify opportunities for analytical investigation through a Discovery Workshop, * assess the suitability of your data and architecture through a Data & Architecture Review, and, * aim to validate the feasibility of your selected analytical concept through an Exploratory Data Analysis.

T-DAB will also review your current architecture and recommend services you can utilise to effectively and quickly return value for your project. If you are not currently using Azure services, this will include an Azure architecture roadmap for your future concepts.

The Discovery Study consists of 3 components: * Specification workshop: identify key insights, specify requirements objectives, action plan and solution priorities * Data & Architecture review: assessing data structure and format, data quality and suitability for purpose, current and target architecture * Exploratory Data Analysis: minor data cleaning, wrangling & munging, analytical exploration; data mining with unsupervised ML/basic statistical modelling

To conclude the study, we will devise an action plan to include recommendations and an initial data roadmap to help you take your next steps with iterative sprints to build and pilot your initial data concepts in Azure.

The workshop cost can vary depending on the scope/scale of the workshop and number of use cases selected to investigate.

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