Questionnaire to understand Power BI requirment

Lets go through the questionnaire and understanding the reasoning behind each question can better help in tailoring solutions for the customer. Let's break it down:

General Information:

1. Objective: Understanding the main goal can guide dashboard design & usage of Power BI
• Example: If a company wants to monitor sales, a time series chart might be central.
• Impact: Aims dictate which data is prioritized and how it's visualized.
2. Stakeholders: Knowing the audience assists in creating user-friendly visuals.
• Example: A technical team might appreciate detailed stats, while executives prefer summaries.
• Impact: Tailors the complexity and depth of the reports.
3. Timelines: Ensures project stays on track.
• Example: A product launch might require analytics in place beforehand.
• Impact: Alters project pacing and resources allocated.

Data Sources:

4. List of Data Sources: Defines connectors or integrations needed.
• Example: Data in Google Sheets would require a different connector than SQL Server.
• Impact: Affects setup time, possible costs, and data refresh mechanisms.
5. Data Update Frequency: Informs data refresh settings.
• Example: Stock prices need real-time updates, monthly sales data doesn't.
• Impact: Real-time requirements might necessitate Power BI Premium.
6. Sensitive Data: Informs security and compliance needs.
• Example: Medical records have stringent security requirements.
• Impact: May need additional layers of encryption or compliance checks.

Dashboard & Reporting:

8. Number of Dashboards: Affects scope and complexity.
• Example: Multiple departments may need separate dashboards.
• Impact: Alters design time and potential license costs.
9. Specific Visualizations: Guides the design process.
• Example: A preference for pie charts over bar graphs.
• Impact: Tailors the visual aesthetics and tools used.
10. Drill Down: Adds interactive depth to reports.

• Example: Clicking on a region to see individual sales data.
• Impact: Requires more detailed data models and interactivity setup.

Data Queries & Transformations:

13. Business Rules: Essential for accurate data representation.

• Example: A sale isn't "complete" until shipment.
• Impact: Affects data transformation logic and resulting visuals.

14. Merge Data: Increases complexity.

• Example: Combining sales data with inventory data.
• Impact: Requires careful data modeling and validation.

Pricing & Licensing:

16. Users: Determines license type and number.

• Example: Designers need a more advanced license than viewers.
• Impact: Affects total cost and type of Power BI subscription.

Deployment & Access:

20. Device Access: Affects design layout.

• Example: Mobile users require a responsive design.
• Impact: Guides dashboard layout and interactivity.

21. Embedding: Integrates Power BI with other tools.

• Example: Embedding a report in a SharePoint site.
• Impact: Might require Power BI Embedded, affecting costs and setup.

Training & Documentation:

23. Training Needs: Assists in user adoption.

• Example: First-time users may need basics, while advanced users might want custom design tips.
• Impact: Dictates the type and depth of training materials.

Maintenance & Support:

25. Support Needs: Guides post-deployment commitments.

• Example: A company without an in-house BI team might need monthly support.
• Impact: Affects ongoing costs and resource allocation.

Other Questions:

27. Security & Compliance: Essential for certain sectors.

• Example: Financial data might need GDPR compliance.
• Impact: Informs data storage, processing, and report sharing methods.

28. Branding: For consistent company aesthetics.

• Example: Using company colors and logos on the dashboard.
• Impact: Customizes the visual design elements.

Each question and its corresponding impact is designed to gather as much relevant information as possible, ensuring that the Power BI solution meets the customer's needs in the most effective and efficient manner.

Now lets check when to use Power BI as along with Visualization we can also do some transformation with this tool. So when to choose BI , Synapse, Data bricks or Hadoop etc.

Power BI is primarily a data visualization and business intelligence tool, while Azure Synapse, Databricks, and Hadoop are designed for data engineering, big data processing, and analytics. However, the decision on when to use Power BI over these other tools depends on the specific needs of the project or business use case.

Here's a breakdown to help guide your decision:

Power BI is primarily a data visualization and business intelligence tool, while Azure Synapse, Databricks, and Hadoop are designed for data engineering, big data processing, and analytics. However, the decision on when to use Power BI over these other tools depends on the specific needs of the project or business use case.

Here's a breakdown to help guide your decision:

1. Nature of Task:
• Power BI: Suited for creating interactive reports, dashboards, and visualizations from various data sources. Ideal for business users and analysts who need to gain insights from data quickly.
• Azure Synapse (formerly Azure SQL Data Warehouse): An analytics service that brings together big data and data warehousing. Suitable for large scale data integration, data preparation, and analytics.
• Databricks: A unified data analytics platform designed for big data and AI. It's built on top of Apache Spark, making it powerful for distributed data processing tasks.
• Hadoop: A big data framework for distributed storage and processing of large datasets. It's typically used for very large-scale data processing tasks.
2. Data Volume:
• Power BI: Handles data that fits within its dataset size limits (1GB for Pro, up to 400GB for Premium per dataset as of last update in 2021).
• Azure Synapse/Databricks/Hadoop: Suited for very large datasets, often in the order of petabytes.
3. User Base:
• Power BI: Targeted at business users, analysts, and data professionals who want to visualize and gain insights from data.
• Azure Synapse/Databricks/Hadoop: More for data engineers, data scientists, and IT professionals working on data integration, transformation, and advanced analytics tasks.
4. Real-time Needs:
• Power BI: Can provide near real-time updates with DirectQuery and streaming datasets.
• Azure Synapse/Databricks/Hadoop: More suited for batch processing, though they can support real-time processing with the right configurations and tools.
5. Integration:
• Power BI: Integrates well with other Microsoft products and a wide range of data sources.
• Azure Synapse/Databricks: Offer integrations with numerous data sources, storage options, and other Azure services.
6. Complexity of Data Transformation:
• Power BI: Good for basic to intermediate data transformations using Power Query.
• Azure Synapse/Databricks/Hadoop: Suitable for complex data transformations, especially at scale.
7. Cost and Licensing:
• Power BI: Costs associated with licensing (Pro, Premium, etc.).
• Azure Synapse/Databricks/Hadoop: Often have usage-based costs which can become significant at scale.

In summary, while there's some overlap in capabilities, the primary decision point is the nature of the task at hand. If you're focused on visualization and business insights, Power BI is a natural choice. If you're dealing with large-scale data processing, transformation, and advanced analytics, then tools like Azure Synapse, Databricks, and Hadoop are more appropriate. Often, in enterprise scenarios, these tools are used in conjunction with each other, where large-scale data processing is handled by tools like Databricks, and the processed data is visualized in Power BI.

Power BI Pricing:

1. Power BI Desktop: This is a free version, allowing data preparation, data discovery, and creating reports. However, to share reports or dashboards with others, you'll need a paid version.
2. Power BI Pro: Priced per user/month. This allows report authors and business users to share content with other Pro users within the organization.
3. Power BI Premium: This is intended for larger enterprises and offers dedicated cloud resources. It's priced per capacity/month. It also has enhanced refresh rates, more storage, and additional features. With Premium, you also get Power BI Report Server to manage on-premises reports.
4. Power BI Embedded: For developers and ISVs to embed Power BI visuals in applications. This is priced per capacity.

In Power BI, the term "per capacity" refers to the dedicated resources provided to customers who opt for the Power BI Premium licensing model. When you purchase Power BI Premium, instead of licensing per individual user (like Power BI Pro), you're buying dedicated resources (or capacity) in the Power BI service.

Let's break this down:

Power BI Premium: Per Capacity

1. Dedicated Resources: With Premium, you're provided with dedicated hardware resources, meaning your data models, data refreshes, and queries are isolated from others, ensuring more consistent and faster performance. This is particularly important for organizations with large datasets or many users accessing reports simultaneously.
2. Larger Datasets: Premium offers support for datasets that are larger than what's available in the Pro version. Datasets in Premium can be up to 400 GB, compared to 1 GB for Pro.
3. Higher Refresh Rates: With Premium, you can refresh your datasets more frequently than with Pro. This is crucial for businesses that require near real-time analytics.
4. Cost Efficiency for Large Teams: One of the significant advantages of Premium's per capacity pricing is that it can become more cost-effective as your organization grows. Instead of paying for each individual viewer (as in Pro), you pay for the dedicated resources. Thus, if you have a large number of report viewers, the per-user cost could be lower with Premium than with Pro.
5. On-premises Reporting: Premium includes Power BI Report Server, allowing you to manage and host your Power BI reports and traditional paginated reports on your organization's infrastructure.
6. Viewing Reports with Free License: An essential feature of Premium is that users with the Power BI Free license can view reports and dashboards shared from a Premium workspace, something they can't do with content from Pro workspaces.

How is Capacity Measured?

The dedicated resources in Power BI Premium are organized into "capacity nodes." Each node has a certain amount of CPU, Memory, and other resources. Depending on your organization's needs, you can purchase more nodes to handle more considerable workloads.

In summary, "per capacity" in Power BI Premium means you're buying dedicated resources (or capacity) for your Power BI tasks, rather than licenses per individual user. This model can offer better performance, flexibility, and cost efficiency, especially for larger organizations or those with substantial data needs.