Before you tackle any data project, it is essential to deeply understand and define the business need, your available data and the best methodologies to maximise your investment in Azure and Power BI
A Data Discovery process also enables you to gain an assessment of the best Azure technologies you require for data integration and modelling, and data visualisation tools (PowerBI) to select and configure to drive the analytics outcomes you're after. Importantly, you will gain the right insights into your available data and what is possible within the Azure ecosystem and associated tools as applications before committing to an approach that may not meet your business needs.
The first step in undertaking a data analytics or advanced data science project requires a detailed discovery process to understand: 1) the problem you are trying to solve, 2) the availability of the right data, 3) the use cases or user stories, and 4) the gathering of requirements.
Over a 3 week timeframe, Empirics will work with you via a structured workshop series, uncovering and documenting the necessary Azure infrastructure, research, requirements gathering and scope to develop your desired data project. The phases for a Data Discovery Process include:
• Research & Preparation - Empirics Data Intelligence team undertakes research and presentation preparation
• Project Kick off – start of formal client engagement
• Client Survey – Design a questionnaire to identify current data usage and opportunities from a wide range of business users • Client Stakeholder Interviews - Structured in-depth interviews with selected key stakeholders to identify business challenges and document specific use cases • MVP Development – Development of use cases and quick wins, building a picture of suitable investment in Azure and PowerBI • MVP Workshop – Working with business and data stakeholders to frame business problems and data solutions and assessment of business value • Scope Sign off – Formal acceptance of the Discovery Process
Key Benefits • Truly define the project and best outcomes from stakeholders to get the most value from your data project • Establish the best methodologies and approach surrounding data modelling options and techniques to solve your business challenges and to maximise your return on investment