Category: microstrategy

MicroStrategy – Creating Filters ”; Previous Next Filtering data is a very important part of data analysis and visualization. MicroStrategy Desktop provides a variety of options to filter data in a report. It has simple filters, which get the data based on the values selected by the user. It also has features to create complex features, which will filter out data based on the calculations. In this chapter, we will learn the basic steps to create a filter on a column with non-numeric values. Example In this example, we aim to create a filter on the field subcategory in a grid report made up of the fields category, subcategory, and sales. Step 1 Create a new visualization by choosing the fields category, subcategory as the rows and sales as the metric. The visualization is shown in the following screenshot. Step 2 Go to the Filter tab next to the Editor tab. Drag the field subcategory to this tab. It will automatically create a filter of type Dropdown as shown in the following screenshot. Also note that the number of values for this are shown in parentheses (25). Step 3 Now check mark the specific values on which we want to filter out the results in the report. On checking these values, only the respective results are visible in the report. Print Page Previous Next Advertisements ”;

MicroStrategy – Advanced Filters ”; Previous Next The advanced filter feature is useful in applying filter conditions, which will otherwise involve complicated steps. In MicroStrategy desktop, we access these features after the filter is created and applied to the report. We have the following additional options besides the check box option. Slider Search Box Radio Button Drop down In this chapter, we will be looking at the search box option in detail. Using Search Box The search box option is available by choosing the already existing check box filter. Rightclick it to get the display type option as shown in the following screenshot. Step 1 Start writing the initial letters of the subcategory we want to filter. It automatically populates the different values from the data set. We choose some specific values by selecting them with clicks. Step 2 On finishing the selection, we get the result in the report as shown in the following screenshot. Print Page Previous Next Advertisements ”;

MicroStrategy – Creating Derived Metrics ”; Previous Next Many times we need calculated metrics which are not already available in the data source. If such situations, metric values can be calculated from the existing metrics, using the create metric option. Thus, creating a derived metric is an approach to create values which we will need frequently in the report but which do not exist in the data source. Example In this example, we are going to calculate the total of shipping cost and unit price for a product in the superstore sales data. Following are the steps to calculate it. Step 1 Let’s create a grip report using superstore sales. The report contains product-sub category as attribute and unit price as well as shipping cost as the metrics. Step 2 Next, right-click near any of the metrics and choose the create metric option. It gives us a window to write the formula for the new metric. Here, write the formula we use in the existing metrics. The formula is as shown in the following screenshot. Step 3 The new metric appears under the list of metric of the data source. We drag it to the existing grid report. Print Page Previous Next Advertisements ”;

MicroStrategy – Importing Data ”; Previous Next MicroStrategy connects to nearly every kind of data source available. It has native connectors, which establish connection with these data sources and also has a connect live feature, which fetches data as and when required. Interestingly, it also shows the icons of data sources for quicker identification of data source you are looking for. Add Data The simplest way to search and select the required data set is by using the Add Data option available with a + icon under the main menu. The following diagram shows the steps to add data. Data Sources On clicking the Add Data option, we see the icons of various data sources. These help in quickly identifying the data source. Search Data Source With this vast number of connection types available, sometimes we need to type in the data source name or filter it from a small group of data set names. MicroStrategy has the feature of advanced search, which makes it possible. Adding Data from Files In this section, we will see how to add an excel file as a data source and create a simple visualization. Select the Excel File Click the option Add Data and choose Excel available under the alphabetically arranged headers showing E. The window shows a Choose File option and clicking it we can browse the local system to select the required excel file. In the following example, we have a sample file containing the employee data of an organization. Prepare the Excel File Before accepting the content of the Excel file, we can preview and also edit the data present in it. Once the file is selected, we can see the button Prepare Data next to the Finish button. Clicking it produces a preview of the data present in the file. Prepare Visualization On clicking Finish, after the data is previewed, we are presented with the MicroStrategy window showing the data objects chosen. Next, we can create a simple visualization from this data source by dragging the columns in the data source into rows and columns boxes. A metric can also be added. The following diagram shows the final visualization. Print Page Previous Next Advertisements ”;

MicroStrategy – Quick Guide ”; Previous Next MicroStrategy – Overview As a Business Intelligence tool with wide range of capabilities, MicroStrategy has powerful features that helps to find answers and insights in business data analysis. Following are some of the important features. Data Discovery This feature enables MicroStrategy to connect to any data source and blend the data from various sources. It can connect to relational sources, flat files, big data sources, social media platforms, and cloud systems to name a few. Data Wrangling This feature helps in data transformation and modification with an extensive set of builtin data wrangling and parsing capabilities. Business users benefit from automatic recommendations while data scientists can leverage the full breadth of wrangling capabilities. There are history scripts that remember data transformations and can be reapplied to any analysis. Data Mining and Predictive Analysis MicroStrategy has a wide range of native analytical capabilities, with the option to easily incorporate third-party data mining and modeling tools. The Data Mining Services can be used by business users, report designers and analysts to view and build predictive reports and distribute these reports to users on any device. Library of Analytics Functions It has an extensive library of over 300 OLAP, mathematical, financial, and data mining functions, which can be used to better understand the relationships between data, create business metrics and top-level KPIs, or build advanced statistical analyses. Extensible Visualization Library It has out-of-the-box grids, graphs, and in-built data visualizations tools. It also allows addition of hundreds of open-source visualizations available from D3 or other providers with built-in tools that help with the integration process. It also has a visualization builder and SK to code a new visualization from scratch. Real-time Dashboards You can build dashboards that can source live data to provide real-time monitoring of the most current information. With scheduled updates that have controllable intervals, users can be guaranteed of the latest data. Embedded BI MicroStrategy comes with several out-of-the-box development-ready portlets that require no additional coding. These portlets allow organizations to seamlessly embed MicroStrategy functionality with IBM WebSphere, Oracle WebLogic, Microsoft SharePoint, and SAP NetWeaver, among others. A portal integration kit includes sample code and documentation for integrating MicroStrategy Web with other enterprise portals. Mobile Platform The existing visualizations, reports, and dashboards are instantly available in mobile platforms, once they are created. MicroStrategy – Environment Setup Download MicroStrategy Desktop The Free Personal Edition of MicroStrategy Desktop can be downloaded from the Microstrategy Desktop. To download, you need to register with your details. After downloading, the installation is a very straightforward process in which you need to accept the license agreement and provide the target folder for storing the desktop version. Desktop version is available for both Windows and Mac OS. In this tutorial, we will consider only the Windows version. The following screenshots describe the setup steps. Start the Installation Wizard Double-click the MicroStrategy Desktop-64bit.exe and it will present a screen to allow the installation program to run. Click Next. Required Components Depending on the Windows environment, you may need additional Windows platform software for MicroStrategy to run. .Net Framework is a common requirement. The installation process takes care of it on its own. On successful completion of the above steps, MicroStrategy Desktop is available on your system. Verify the Installation To verify that MicroStrategy Desktop has been successfully installed, open the start menu in Windows and click the icon for MicroStrategy. The following window opens confirming the installation of MicroStrategy Desktop. MicroStrategy – Desktop The MicroStrategy Desktop environment is very intuitive. It has a simple menu to import data for analysis and export the result of analysis. The menu also provides features to connect to a server if required, view the data sets available, the visualization gallery, and data filtering options, etc. Desktop Windows Following screenshot shows the image of MicroStrategy desktop windows. Following is a brief description of each of these windows. Dataset Panel − This is used to add the required data sets to be analyzed. The data sets can come from any of the compatible sources. This section also gives an option to connect to the data sets available in MicroStrategy server. Editor Panel − This is used to bring in the required rows and columns from the data set for analysis. Also the different matrices or mathematical expressions can be applied to the data analysis available here. Properties Panel − This panel is used to set the display formats of the data such as font size, color alignment. etc. Filter Panel − This panel is used to apply various filters on the data sets being analyzed. Visualizations − It is the panel which shows data analysis. You can drag the data objects to this panel and apply a method of visualization to see the results. Visualization Gallery − This panel displays the inbuilt-visualizations available, which can be applied directly on the data set. The various visualizations available are – Heat maps, bar charts, bubble charts, network diagrams, etc. It also allows to create custom visualizations. MicroStrategy – Architecture MicroStrategy has a metadata-driven architecture. The metadata is a central repository, which stores all the objects used by it. Also the metadata can be used by any of the MicroStrategy products, which has ensured uniformity in the values of the objects. The objects stored in the metadata are reusable. Object Layers The following diagram represents the different layer of objects created and stored in MicroStrategy metadata. Administration Objects − This Objects layer establishes the security, user grouping, and performance parameters that govern the MicroStrategy applications. Report Objects − This objects layer assembles the building blocks from the Schema and Analysis Object Layers to provide insightful textual and visual analysis. Analysis Objects − This objects layer provides the building blocks for sophisticated analysis. The analysis objects are built on the objects developed in the schema layer. Schema Objects − This objects layer provides a logical abstraction of the database schema that is tailored for the business model. ROLAP

MicroStrategy – Useful Resources ”; Previous Next The following resources contain additional information on MicroStrategy. Please use them to get more in-depth knowledge on this topic. MicroStrategy Desktop Course 48 Lectures 2.5 hours Pavan Lalwani More Detail MicroStrategy Desktop 2020 47 Lectures 3 hours Packt Publishing More Detail MicroStrategy Data Analytics & Business Intelligence Course Featured 75 Lectures 17 hours Amit Kumar More Detail Print Page Previous Next Advertisements ”;

MicroStrategy – Predictive Models ”; Previous Next Predictive Modeling is a mathematical approach to build models based on the existing data, which helps in finding the future value or trend of a variable. It involves very heavy mathematical and statistical analysis to create such models. Following are some examples, where predictive modeling is used. Weather forecasting. A university tries to predicts whether a student will choose to enroll by applying predictive models to applicant data and admissions history. In a retail shop to find out which two items are most likely to sell well together. In airline industry to estimate the number of passengers who won’t show up for a flight. MicroStrategy can help in carrying out predictive modeling as its data mining services is fully integrated to its BI platform. Predictive Analysis Using MicroStrategy MicroStrategy has data mining services, which allows the users to import PMML (Predictive Model Markup Language) from third party data mining tools, which can then be used to create predictive reports. PMML is an XML standard that represents data mining models developed and trained by data mining tool. PMML supports a number of different data mining algorithms, including Regression, Neural Networks, Clustering, Decision Trees and Association. It incorporates data transformation and descriptive statistics. The following diagram describes the process of creating predictive data model reports in MicroStrategy. Once imported into MicroStrategy, we can enhance the model by using the following features. Features for Predictive Modeling Following are the list of features which highlight the strength of MicroStrategy to be used as a predictive modeling tool. Built-in Data Mining Functions − There are 250 basic, OLAP, mathematical, financial, and statistical functions that can be used to create key performance indicators. Data Mining Integration Using PMML − It allows the users to import PMML from third party data mining tools, which can then be used to create predictive reports. User Scalability − Hundreds of thousands of users, internal and external to the enterprise, can access this feature. Data Scalability − MicroStrategy’s relational OLAP (ROLAP) architecture combined with its Intelligent Cube technology can handle any size of database while delivering high performance. Print Page Previous Next Advertisements ”;

MicroStrategy – Conditional Formatting ”; Previous Next Conditional formatting in MicroStrategy involves highlighting parts of the visualization, which meets some pre-defined criteria in their values. Usually in case of metrics, we want to highlight the values which are greater than a certain percentage. There can also be examples of highlighting some category of product names, etc. In MicroStrategy desktop, we can achieve this using the threshold feature. In this example, we will define the color to be used for highlighting certain values when a certain threshold is satisfied. Following are the steps. Step 1 Create a grid report with the all_sales.xlsx as an example data set. Put the attributes Business line, Category in the grid along with the metric sales. Right-click the metric sales, and we get the option to choose the threshold as shown in the following screenshot. Step 2 The following screenshot shows options to choose different colors based on the percentage value of sales. Step 3 Finally, the result of applying the threshold is displayed in the following screenshot. In the metric Sales, the values are highlighted in different colors based on the percentage value of the sales as compared to the total sales. Print Page Previous Next Advertisements ”;

MicroStrategy – Report Cache Flow ”; Previous Next A report cache is a data store which holds the information that was recently requested from the data source to be used in a report. Whenever a report is executed for the first time, a cache is created. The report’s cache contains the results that were fetched from the database, files, or web sources. Advantages of Report Cache Following are some of the advantages we get by using MicroStrategy caching feature. A cached report returns the results faster as the data is already available inside MicroStrategy software. The execution time involving any calculations and derived metrics is quicker as the cached reports do not need to run against the data source. In a cache, results from the data source are stored and can be used by new job requests that require the same data. Types of Cache There are three types of cache used in MicroStrategy. Report Caches − These are the results which are pre-calculated and pre-processed. They are stored in the memory on the Intelligence Server machine or on the disk. They can be retrieved more quickly than repeatedly re-executing the request against the data warehouse. Element Caches − These are frequently used table elements, which are stored in the memory on the Intelligence Server machine. They can be retrieved quickly as the users browse through displays of attribute elements. Object Caches − These are metadata objects stored in the memory on the Intelligence Server, so that they can be retrieved quickly on subsequent requests. Enabling the Cach Cache can be enabled, both at the report level and at the project level. This is done using the project configuration editor. Enabling at the Project Level If the cache is enabled at the project level then, all the reports within the project will use the caching feature. Enabling at the Report Level On enabling at the report level, only specific reports will use the cache. Even if the reporting is disabled at the project level, it will function at the report level, when enabled at the report level. Cache Disadvantage The cached data is not always the most up-to-date, as it has not been run through the data source since the cache was created. This can be avoided by deleting the report’s cache before executing the report. This forces the report to be executed through the data source again, thus returning the most recent data from the data source. However, it needs administrative privileges to delete a report cache. Print Page Previous Next Advertisements ”;

Visualization with Multiple Datasets ”; Previous Next So far we saw reporting with one source of data as the source. But we can also add more than one data source to the same report. In such case, we can use the attributes and metrics from both the sources in creating the visualization. The result appears as if we are dealing with one source of data. This happens because MicroStrategy combines both these sources and internally treats them as one. Following are the steps to combine two source data sets and create a visualization. Step 1 Create a report with one source of data. We will use All_sales.xlsx in the example. Next, click the New Data menu as shown in the following screenshot. Step 2 Now you can see both the data sources available under the Dashboard. The attributes and metrics of both of these sources are available under their respective names. Step 3 Next, drag the attribute “Business Line” from All_sales.xlsx to the rows box. Drag the attributes “customer segment” and “Product Category” from the second data set to the rows box. The grid visualization appears showing data from both the data sets. Print Page Previous Next Advertisements ”;