The way businesses use their data is always changing and rapidly evolving. Once, data was acquired and accumulated on internal servers. Businesses who could piece their information together, manually or in a legacy report writer, for any sort of visibility into their financial standing or operational performance, were considered advanced, even lucky.
Now, the information a business accumulates has taken on an entirely new dimension. Data is now becoming the staring role for growing organizations. To stay competitive, a company must harness their data for important insights that allow them to be more efficient, capitalize on opportunities, and make profitable decisions.
To accomplish this, visualization tools are needed to transform how your information is used. Since their introductions, Power BI and OLAP Cubes have both added that missing piece for many businesses. But how to fully utilize, and understand, these tools are often masked in some mystery and complexity.
So, how can Power BI and OLAP Cubes work together to create the best possible experience for your workplace?
Microsoft Power BI
As a visualization tool, Microsoft’s Power BI can analyze data and create visual dashboards across different programs. You can transfer information from existing sources, generating outlooks catered to specific departments and programs. With combined reports and other features, Power BI will help you gain better insight into your company.
Yet, several problems tend to exist when you approach visualizing your existing data through Power BI.
Most databases (like your core ERP system such as Microsoft Dynamics Business Central, or SAP Business One) are inherently “relational” and typically organized as a collection of tables with columns and rows. While great at intaking and storing information, relational databases are not ideal for analytics. In one way, they make housing and organizing the data exceptionally easy, even grouping and calculating pieces of data with ease. But on the flip side, these systems take an extensive amount of time probing the relevant data. The result is severe slowdowns and long delays in gathering what was often needed quickly.
Add to that, if you have multiple relational databases, or say, multiple systems the information you need put together sits on, not only do you add more processing time, you add extra complexity in pulling the data together into a single place. In some cases, combining imperative data across multiple systems is impossible without manual, error-prone efforts that often negate the gains you are to get from the report or dashboard in the first place.
Subsequently, you’ll be waiting for these items to be organized and read, rather than getting information. This will make it harder to find what you’re looking for or develop the right business strategies. In short, Power BI is brilliant at visualizing your data, but it isn’t built for data consistency, speed, or organization – so it is only as good as the data feeding that engine. The question now becomes, how do you address the multi-layer elements that make up your data clusters?
What are OLAP Cubes
Enter the creation of OLAP Cubes for your Business Intelligence needs. Short for “Online Analytical Processing,” OLAP Cubes offer the ability to have multidimensional layers to your data. Rather than one single element, multiple layers can be created to correspond to different segments of information. These ‘dimensional’ layers now allow for exceptional speed in retrieving data, seamlessly combining data across various sources, simplification of data retrieval, and governance of data for a single source of truth.
When retrieving data, you’re engaging in what is commonly referred to as business intelligence (BI). With BI, each piece provides some variable that impacts the rest of your firm. In an OLAP Cube, you’ll have access to hundreds of potential factors to break your information up by rather than a few specific variables, these conform directly to how your business is run.
Let’s get into a practical example. Say you wanted the answer to what items were trending up in sales across the Eastern US. Not just that, you wanted to understand the most profitable items trending in those sales so you could promote those first. To pull that from your standard relational database, you would need to query all sales transactions, across all regions, across all items, across millions of records, subtotal, then filter out only those in the Eastern US. On top of that, you’ll need to calculate, perhaps manually, the COG and profit against each item, then sort your data accordingly.
With an OLAP Cube, all dimensional aspects of this data, including the region, calculated measure of COGs, and margin %, is already pre-calculated, pre-combined, and organized for you to retrieve, on the fly. No processing time. Even better, if you needed to probe down to the salespeople, or the individual Eastern territories, you can do that instantaneously without needing to intimately know the underlying data structure or introducing complex configurations of piecing data together.
OLAP Cubes are sophisticated ways of organizing and optimizing data on the back-end, so it is fast and easy to retrieve it on the front-end.
Each Cube is customizable, offering a more substantial outlook over specific processes than previously before. This allows for easier pattern detection within your information, as everything becomes more noticeable. From there, you can compare data and locate the exact factors driving or preventing your company’s growth.
Power BI + OLAP Cubes
Power BI + OLAP Cubes
Here’s where it gets powerful. When combined with Microsoft Power BI, OLAP cubes create a streamlined way to analyze data and build meaningful dashboards and KPIs.
Faster Access to Critical Data
Imagine retrieving monthly sales data across multiple products over several years.
With traditional systems, this can take time to process and organize.
OLAP cubes solve this by structuring data into a multidimensional model, allowing information to be quickly accessed, filtered, and analyzed without delays.
Real-Time Insights with Power BI
At the same time, this data is seamlessly connected to Power BI. This allows users to visualize, interpret, and adjust data through interactive dashboards—without the need for heavy customization.
What once took hours to compile and analyze can now be done in seconds.
Better Decision-Making with Clear Trends
With OLAP cubes feeding structured data into Power BI, businesses gain a clearer picture of performance over time.
Trends become easier to identify, and future opportunities can be evaluated with greater confidence—giving your organization a competitive edge.
Turning Data Into Action
Every business wants a better way to understand what’s working and where improvements are needed. One of the most effective ways to do that is by leveraging the data you already have.
With the combined power of Power BI and OLAP cubes, turning data into actionable insights becomes significantly easier.
Frequently Asked Questions About Power BI and OLAP Cubes
What are OLAP cubes in business intelligence?
OLAP cubes are multidimensional data structures that allow users to analyze large datasets quickly by organizing data into dimensions such as time, geography, and product.
How does Power BI work with OLAP cubes?
Power BI connects to OLAP cubes to visualize complex data through interactive dashboards and reports, enabling faster analysis and better decision-making.
What are the benefits of using OLAP cubes with Power BI?
Using OLAP cubes with Power BI improves reporting speed, enables multidimensional analysis, and helps businesses uncover trends and insights more efficiently.
Why are OLAP cubes important for data analysis?
OLAP cubes allow users to slice, dice, and drill down into data, making it easier to analyze performance, identify patterns, and support strategic decisions.
Is Power BI suitable for large datasets?
Yes, Power BI is designed to handle large datasets, especially when combined with OLAP cubes or data models that optimize performance and querying speed.
What is the difference between OLAP and traditional databases?
Traditional databases store data in tables for transactional workloads, while OLAP cubes are optimized for analysis, enabling faster querying and multidimensional reporting.
Get More Value from Your Data with Power BI and OLAP Cubes
Turning data into meaningful insights doesn’t have to be complex. With the right tools in place, your business can move faster, uncover trends sooner, and make more confident decisions.
Power BI and OLAP cubes work together to deliver real-time reporting, multidimensional analysis, and a clearer view of performance across your organization—helping you stay competitive in a data-driven world.
If you’re ready to improve your reporting and get more value from your data, the data specialists and business application experts at Clients First are here to help.
Contact our team today to see how Power BI and OLAP cubes can transform your business insights.
