The Azure Data Clinic focuses on data, processes and strategic alignment in order to identify new use cases for monetizing your data and devise an implementation roadmap.
Our experience in Big Data technology, AI, and data product development on Azure results in a unique approach for obtaining value through tangible deliverables. We want to get value from our data assets and achieve a high degree of data monetization through simple group dynamics in which all relevant organizational units and data stakeholders participate. After these dynamics, and a thorough analysis of your strategic goals, data ecosystem, roadmap, and data governance initiatives we will outline a Data Strategy Plan, as the map that guides your company's Data Journey to the right destination.
Our method is divided into three stages:
Immersion and Data Maturity Assessment: In first place, we need to understand the company context and corporate strategy, and the current data ecosystem, including the map of information systems, available data assets, data analytics practices and the underlying data architecture and technological infrastructure.
Ideation and definition: At this stage we will focus on identifying new use cases that support your corporate strategy. For that, we will conduct brainstorming sessions in which to introduce the capabilities of Big Data and AI, and identify new use cases in a collaborative way. We will define with you your key data architecture principles, anticipate the technological enablers (data analytics, data warehousing, AI, IoT, etc.) for the new use cases and design a data architecture based on Azure Data Services (such as Azure Synapse, Databricks, Data Factory, Data Lake Storage, ML Power BI, etc.), industrialize your data products with DataOps practices that leverage Azure DevOps, and define your Azure migration strategy, as well as a data governance framework that takes advantage of Azure Purview for a unified data governance.
Planning: We will devise a detailed roadmap and a high-level effort estimate for iterative and incremental implementation of all the data initiatives on an Azure data ecosystem.