![]() ![]() Here is how to switch to the pivot charts mode in one click:Īnd here you go! You can now share your results – export a report to PDF, Excel, HTML, or whatever format suits you best. You can also look at your OLAP data from another angle by visualizing it with pivot charts that are drillable and interactive. To find patterns in your data, just connect to the cube from the pivot table and use the Field List as a pivot table designer: drag and drop hierarchies to rows, columns, and measures. How to build OLAP-based pivot table reports Your end-users can work with data from tabular or multidimensional data cubes – OLAP data analysis will be rich and interactive in each case. ![]() That’s why Flexmonster Pivot Table & Charts supports both models. Our development team believes that both tabular and multidimensional solutions can successfully meet diverse business and user requirements. Having all this in mind, we designed Flexmonster Pivot to be a front-end component for OLAP visualization.Īnd knowing how large your data cubes can be, we optimized the tool to handle any size datasets, making visualization and reporting fast and reliable. OLAP reporting should be not only insightful but also swift to respond to emerging data analysis goals. support of slicing, pivoting, rolling up, and drilling down – essential operations for data cube analysisĮnd-users should also be able to explore their data interactively without generating complex queries.Īnother critical aspect is performance.the flexibility of integration with modern web and desktop technologies.When choosing a suitable data visualization tool, we recommend paying attention to these criteria: Combined, they can make up powerful data dashboards or be a part of OLAP business intelligence. Pivot charts complement and enhance this visualization type, making information easier to grasp. One way to bring your OLAP data to life is via reports with pivot tables and pivot charts.Īs a form of data visualization, tables are beneficial for comparative data analysis. Such tools help you spot trends in your tabular or multidimensional data and communicate them at maximal efficiency. This is where data visualization tools come to the rescue. Now it’s essential to find a way to extract meaningful information from OLAP data. Say you’ve chosen the model that works best for your project. some features, such as aggregations or actions, are supported in the multidimensional model only.performs better in terms of scalability.If your database requires more than five terabytes, multidimensional is the only option. works better with a large amount of data – when we are talking about terabytes, it’s better to go with the multidimensional database.more efficient data compression about one-tenth of the size, whereas compressed multidimensional data takes up a third of the size of the original database.However, tabular is a memory dependent solution, and more memory will ensure better performance hardware, such as disks, is not essential.works quicker than multidimensional cubes for queries based on columns.easier for understanding and creating the model.But we’ll guide you with core points to consider before giving preference to a specific solution. Similar to cubes, the model supports measures and key performance indicators (KPIs).Īs far as choosing the model goes, it’s better to conduct a detailed study based on project requirements. Similar to databases, the tabular model supports tables with relations. The tabular model is something in between relational databases and multidimensional cubes. That was why Microsoft introduced the SQL Server Analysis Services (SSAS) tabular model in 2012. However, many users claimed that multidimensional cubes were hard to understand, especially when designing the model. One common motivation to use Microsoft SQL Server Analysis Services is the analysis of massive datasets. OLAP cubes allow coping with much more significant data volumes than relational databases. #Ssas tabular model updatePLEASE NOTE: Since we update Flexmonster Pivot with new features biweekly, the information might become outdated. ![]()
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