Our Power BI Tenant Provisioning workshops are designed to help provision your Power BI tenant as per Microsoft best practices and aligned with your organization’s usage scenario. Each workshop covers one primary subject area (see the course outline for details). Intended Audience BI Teams, Enterprise Architects (Data, Application, and Security), Lines of Business (LoB)
Evaluation
First Consult
Goals Identify the high-level value chain of your organization Understand where you are in your Digital Transformation Journey Understand the business problem's that the customer is looking to solve Outcomes High-level value chain map of your organization An articulation of the high-level business problem and a solution approach
Post Deployment
Azure DevOps
Plan smarter, collaborate better, and ship faster with a set of modern dev services. Agenda: Understand how Azure DevOps Services can help your teams to share code, track work, and ship software Azure Pipelines. Understand how Azure DevOps can continuously build, test, and deploy to any platform and cloud Azure Boards Plan, track, and
Evaluation
Combining SQL and ML
Ever wondered if SQL and ML can be leveraged together? SQL ML Services is the best solution to combine both these technologies. Machine Learning Services as a feature in SQL Server gives the ability to run Python and R scripts with relational data. Agenda: A brief overview of the components of SQL ML Services
Evaluation
Understanding Cognitive Services
Explore a wide variety of cognitive options in Text, Speech, Image, Web Search for building your solutions. Cognitive Services is a purpose-built collection of AI algorithms and application programming interfaces ( APIs) to help developers add AI capabilities to websites, apps, and AI agents. Cognitive Services allow enterprises to support AI research staff, infrastructure,
Evaluation
Evaluating Azure Databricks
Azure Databricks is the jointly developed data and AI service from Databricks and Microsoft for data engineering, data science, analytics, and machine learning. Agenda: Understand how Azure Databricks are tightly integrated with Azure Data Lake Storage, Azure Data Factory, Azure Machine Learning, Azure Synapse Analytics, Power BI, and other Azure services to store all
Evaluation
AutoML Overview
A deeper dive into the AutoML to build a high-quality model by automating algorithm selection and hyperparameter selection. Automated machine learning (AutoML) for dataflows enables business analysts to train, validate, and invoke Machine Learning (ML) models directly in Power BI. It includes a simple experience for creating a new ML model where analysts can use their
Evaluation
Azure ML Service Overview
A deeper dive into the Azure Machine learning Service to build integrated, end-to-end Azure data science and advanced analytics solutions that enable data scientists to prepare data, develop experiments, and deploy models at a cloud-scale. Agenda: Gain a deeper understanding of Microsoft Azure ML service functionality and limitations. Understand how the different components of
Adoption
Choosing the right ML framework & tool
Choosing the right framework and right tools for your business problem is the first and foremost step of AI adoption. This can be overwhelming at times because of the plethora of options out there. We at DSI can guide you in this decision-making process understanding your requirements and pinpointing them in the right directions.
Post Deployment
The Post Deployment AI Journey
Implement an early end-to-end integration to iterate faster by using small and valuable increments. Create an entire deployment process, continuous monitoring, and management strategy. Agenda: Evaluate the best approach to train and serve models to production – batch / real-time. Adopt ML System Architecture and Writing Production-Ready Codes. Model Deployment, Monitoring, Maintenance Measures –