Your Data and Analytics Strategy should include the Common Data Model for 3 very good reasons: Agility, Resilience and Value. In this post, we will discuss the reasons why you should, and also what you should consider. But first, what is the big deal and why does Power BI Data Flows and the Common Data Model revolutionise your Agility, Resilience and Value when it comes to producing diamonds from your data.

1. Agility

In traditional reporting design, we drew a dotted line down the middle of any report development initiative. To create a report we divided the left side of the dotted line off to the Data Provisioning team who brought the data into the warehouse and to the right we assigned that work to the reporting team to develop the report against the provisioned warehouse data. This divide or handing off creates an agility issue, an assumption that the warehouse team will be able to execute quickly and a get it right once mentality that meant there was no room for shifting specification if a column was forgotten. Power BI dataflows does away with a dotted line, increasing agility and giving the analytics team the power to create their managed integrations. These integrations, called Power BI Data Flows, increase agility by enabling analysts to create powerful transformations from source to common data model in a low code environment. The engine behind these transformations is actually Power Query, the same engine that sits in the back of Power BI desktop, Excel and a growing number of other platforms. If you forget a column, this isn’t a big issue as the Power Query steps can be traced back to refactor. If load times are an issue, your Power BI Premium workspace supports incremental data loads. Power BI Dataflows also increases agility allowing data provisioning to be accomplished by a wider pool of people than just those trained in the art of integration with traditional platforms. The inclusion of unstructured data also opens up a new world of possibilities and agility.

2. Resilience

Traditional Data Warehouses require the schema of the data to be declared before the data is written to the database. This single constraint creates a significant breaking point for any change that occurs in your Integration system. A Common Data Model uses Azure Data Lake Gen 2 under the covers, removing this breaking point, and is known as Schema on Read. Data is written to the Lake as data and the schema doesn’t have to be declared until you read it with Power BI. The Common Data Model significantly increases the resilience of your warehouse by removing the long-standing breaking point in traditional warehouse architecture.

3. Increase Value

Power BI is part of a bigger ecosystem of the Power Platform which includes Power Automate, PowerApps, and Power Virtual Agents and is tightly integrated into other Office 365 Features like Microsoft Information Protection. Aligning with the Common Data Model adds value by opening up your data seamlessly to the entire Power Platform. Power Automate cuts down on mundane manual business processes involved in preparing, approving and actioning data. PowerApps gives the business agility to close gaps in the current application portfolio with business-friendly apps that empower and engage employees. Power Virtual Agents adds value to frequently asked use cases within the business streamlining processes like onboarding, creating an innovative and engaging place to work. AI Builder for the Power Platform brings Artificial Intelligence to reality allowing you to truly do more with less. Finally, as Data is your number 1 asset, the Common Data Model does an outstanding job of promoting your data as an asset, an integral part of any data or ICT strategy.

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What you should carefully consider :

  1. You don’t have Power BI Premium. Power BI Data Flows requires workspaces to be changed to Power BI Premium capacity mode which means any user who publishes or reads from this workspace is going to need Power BI Premium Per User License, or the organisation needs a Power BI Premium Capacity license P1 or above. This isn’t so much as reason not to embrace the Common Data Model, but a plan around how many workspaces and people actually need Premium will give you an understanding of the cost to move to the Common Data Model.
  2. Training – Power BI Data Flows is a newer feature, is powered by the Power Query Engine and uses Azure Data Lake Gen 2 under the covers. Ensuring your staff are well trained in Power BI Data flows, Power Query and Data Lake is essential to empower your agility, resilience and realise the value out of the Common Data Model. Though Power BI Data Flows is a codeless environment, this does not mean you are exempt from some baseline best practices and ensuring your follow a design pattern.
  3. Data Lake – Power BI Data flows uses Azure Data Lake Gen 2 under the covers and gives you a total of 100Tb to work with. That said you should enable your self hosted Data Lake in the Power BI Tenant Settings. This gives you more flexibility to read and write to the lake as your Azure Data Lake Gen 2 resource is visible and manageable in your Azure Subscription, not just confined to Power BI under the covers. Your Power BI Data Flows will benefit from scaleup techniques into other big data services that also sit over the Azure Data Lake Gen 2.
  4. Your existing Warehouse Investment Power BI Data Flows wasn’t around not so long ago, so a traditional warehouse was the way you achieved trust and single source for your reporting needs. Should you move your existing warehouse to Power BI Data Flows entirely or just move parts. As traditional Data Warehouses get more and more complex over time, weigh up the agility, resilience and value of Power BI Data Flows moving forward compared to maintaining what you’ve built to date. Azure Data Lake Gen 2 supports structured and unstructured data sources where your traditional warehouse caters well for structured only. Consider a pilot to prove the concept on a value initiative in the business. Today is a pivotal point to consider freshening your Data Strategy to include Power BI Data Flows and the Common Data Model.
  5. Where to Start – If you are not sure where to start, consider Customer. As customers pay the bills, any insights derived from knowing your customers is bound to pay wins, like handling customer feedback, recognising upsell opportunity or reduce churn risk. Customer isn’t going to be as sensitive as say employee or payroll data so there will be less roadblocks. There is a reliable off the shelf Customer entity or you can create you can customise this entity. Customer is Queen and is bound to resonate with any executive.