How do you leverage BI cloud and SaaS to create and share dashboards and reports with your stakeholders?

PowerBI and Tableau are the titans in the BI cloud and SaaS space, as confirmed by Gartner's Business Intelligence reports. While Tableau can get pricey, they offer a one-year student trial that's perfect for testing the waters. Once you grasp the core concepts of data visualization, transitioning between platforms becomes a matter of learning a new user interface. And let's be real, when you hit a snag or need to bring a creative idea to life, resources like Stack Overflow, YouTube, and even AI solutions like ChatGPT become invaluable allies. So, choose your platform wisely, but remember, the real power lies in your ability to adapt and solve problems, no matter the tool.

Almost all BI platforms offer cloud today, including OAS, Tableau, Power BI, Qlik, etc, There are lot of SaaS software like Taleo that offer a semantic layer for reporting and analytics, As an Architect do the analysis on how many in-house and cloud products you have currently today and work with your leadership and understand your strategy and also check-in to make sure you have budgets and then come up with the platform, either you choose cloud or SaaS, you'll have to follow BI best practices to be successful, I have observed that new tools like tableau and power BI work really well when you pre-aggregate the data and keep it ready for consumption and they are not good at complex logic.

For my team, the inherent integrations between all the MS ‘Power’ platforms, (query, apps, automate, BI) make PowerBI the winner. Being able to take simple user entry data from the likes of Forms, pass through Automate to enrich the data, add additional user entry through Apps, and then pull in external sources through Power Query with background refreshing set to bring it all together under the single sign on of Office365 via mobile has delivered critical insights in a fraction of the time of paying for external report building, and the only ‘cost’ is the time to build given the business subscription to O365 includes all the standard usage cases for the power platforms…i.e. why ignore this and pay extra for Tableau. Tj

Selecting a Business Intelligence (BI) cloud or SaaS platform depends on various factors such as your organization's needs, budget, and integration requirements. Consider evaluating user-friendliness, scalability, data security, and the platform's ability to handle your specific data sources. Additionally, assess customer support and the platform's track record for innovation and updates.

In the BI world, platforms like Tableau offer a plethora of options for connecting directly to various data sources. While that's convenient, I'd argue it's not the best practice for professionals. My go-to approach is to funnel all data into a centralized data warehouse like BigQuery first. Here, you can transform and manipulate the data to ensure it's in the right format. Once that's done, connect your visualization tool, like Tableau, to this 'clean' table in your data warehouse. Sure, you can use Tableau to join tables or do some quick 'noodling,' but that should be the extent of it. Use direct connections to raw sources only for quick tests or exploratory data checks, not for your main data pipeline.

Connecting a BI cloud or SaaS platform to data sources requires careful consideration of compatibility, integration capabilities, security measures, scalability, and vendor support. Prioritize ease of configuration and ensure the platform aligns with your organization's data needs and growth.

In my experience this step is #1, previously we called it requirements gathering. Data modelling and analysis is critical to any kind of usage of data

Transforming and modeling data for analysis and visualization is crucial for deriving meaningful insights. This process ensures that raw data is structured, cleaned, and organized, making it suitable for exploration. A well-executed transformation enhances data quality, enabling accurate analysis and more impactful visualizations. It's an essential step in unlocking the full potential of your data for informed decision-making.