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Microstrategy reporting tool basics of investing

Опубликовано в Forex deposit without investments | Октябрь 2nd, 2012

microstrategy reporting tool basics of investing

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You can view a MicroStrategy report from different perspectives, depending on the type of work you wish to perform. Grids - A grid report is the most commonly used type of report. Grid View displays grid reports using a formatted, cross-tabular display of the report data. Most business intelligence analysis is performed using this view.

The following figure displays the Grid View of a report. Graphs - A graph report is a representation of data in a visual format that can help you see overall trends easily, identify medians and exceptions, and so on. You display report data as a graph using Graph View. There are many different graph styles you can choose from to display your report data most effectively.

The following figure displays the Graph View of a report in the bar graph style. Inclined to build a profession as MicroStrategy Developer? Then here is the blog post on, explore MicroStrategy Training. The following figure displays the Grid Graph View of a report. This view provides a good way to troubleshoot and fine-tune the selection of data that is retrieved from your data source and displayed in reports. SQL View also includes various execution statistics for a report, such as the number of rows, number of columns, the time it took to execute, and so on.

The following figure displays the SQL View of a report. Documents are a display of data from multiple reports with special formatting added, as shown below:. Report Services documents can be viewed, analyzed, and created in both MicroStrategy Desktop and Web. A document can contain data from one or more MicroStrategy reports. Documents can appear in almost as many ways as you can imagine and are generally formatted to suit your business needs, in a single display of presentation quality.

Documents allow you to display your business data in a user-friendly way that is suitable for presentation to management for boardroom-quality material. MicroStrategy Interview Questions. A view filter is different from a report filter, which restricts how much data is retrieved from the data warehouse. A view filter dynamically restricts the data being displayed on the report without re-executing the report against the warehouse.

This capability provides improved response time and decreased database load. It is important to note that you can use a report filter and view filter on the same report. The report filter returns a set of data for the report, which the view filter then further restricts. Derived metrics perform calculations on-the-fly with the data available in a report.

They are an easy way to present data already available on the report in different ways, providing further analysis of data. You can use derived metrics to quickly perform on-the-fly analyses such as margins, contributions, and differences between metrics included in the report. These metrics are created based on existing metrics in the report.

Since derived metrics are evaluated in memory, their computation does not require any SQL execution in the database. Since derived metrics are created within a report, they can only be used for the report in which they are created.

Derived metrics cannot be saved as individual objects in the project, and therefore cannot be applied to other reports in the project. A derived element is a grouping of attribute elements on a report. These groups provide a new view of report data for analysis and formatting purposes. For example, you can group data for the months of December, January, and February into a single element that combines and displays the data for the entire winter season.

Rather than having to define consolidations or custom groups, you can use derived elements to create these groups on-the-fly while viewing a report. Derived elements are evaluated on the report dataset without regenerating or re-executing SQL. Derived elements are defined by using a list, filter, or calculation to combine attribute element data.

Dynamic aggregation allows you to change the level of report aggregation on-the-fly, while you are reviewing the report results. This feature allows metric values to be aggregated at different levels depending on the attributes included in the report without having to re-execute the report against the data warehouse. Dynamic aggregation occurs when the attributes included in the report layout changes.

The attributes included on the report layout changes when you move an attribute or attribute form off of the report layout to the Report Objects pane, or when you move an attribute or attribute form from the Report Objects pane back onto the report layout. As included in the report layout changes, metric values are dynamically aggregated to the new level of the report. Formatting a report involves highlighting certain data to enhance analysis, as well as changing the overall display or look and feel of a report.

You can:. Using the banding option, you can group rows or columns of report data using colors to enhance readability and make it easier to identify business concepts on which you would like to focus. Thresholds are cells of data that are formatted differently from the rest of the data on a report; the formatting is applied dynamically, whenever the report is re-executed.

Thresholds highlight particular data in a report by displaying special cell formats, symbols, images, or replacement text. Threshold images cannot be viewed in Desktop, although all other threshold formattings, such as symbols and replacement text, can be viewed in Desktop. To see threshold images you have added to a report, view the report in MicroStrategy Web.

Click Field first, to select the business attribute or metric calculation that is part of your condition. Click Value to specify the elements from the available list. This formats the values that meet your threshold condition. This replaces the value that meets your threshold condition with text. Type the text in the text text field. The text should be limited to characters. Choose the symbol from the selection in the box to the right. If you selected any option except Image above, click Edit the threshold formatting on the toolbar to apply formatting to the metric values, replacement text, or symbol.

Select whether to apply the threshold formatting to subtotals. Click one of the following icons on the toolbar:. If you chose Quick Symbol earlier in this procedure, select the Allow users to display and hide the thresholds checkbox if you want to allow other analysts to change between the metric value and the symbol that you have specified for the threshold value. Users can switch between the symbol and value using the F12 function key or by selecting the Hide Threshold or Show Threshold from the Data menu.

By creating an alias for an object on a report, the object can be displayed on that report with a different name, without changing its name in the MicroStrategy project. If you have the MicroStrategy OLAP Services product, you can hide any metric column by simply dragging it off the grid report into the Report Objects pane to the left of your report.

Banding is a method of organizing or grouping data values in a grid report according to certain criteria. You can band rows or columns in several ways. You can band based on the number of rows or columns for example, alternating color every 5 rows. You can also band based on the row and column headers for example, sorting the Units Sold column in order, then applying alternating colors to sets of values.

MicroStrategy comes with several presentation styles for displaying reports. These are called auto styles. Each auto-style automatically applies a set of formatting that includes color scheme, font style, and font type to a report. When reports return large amounts of data, it can be difficult to easily understand what the data is telling you. Several MicroStrategy tools can help you analyze large amounts of data more quickly.

Sorting lets you move data so you can analyze that data more effectively. You can sort on any column or row that is on a grid report. When you sort, you determine the sorting order, either ascending or descending:. Ascending sort order arranges the data alphabetically, from A to Z, or lowest to highest, such as from 1 to Descending sort order arranges the data in reverse alphabetic order, from Z to.

Sorting is processed by the MicroStrategy Analytical Engine, which means you can sort and organize the data on a report without taking up the time and resources to re-execute the report against your data source. Whenever you want to quickly locate a specific data value in a grid report, or you want to jump to a section of a large report, use the Find feature. You can create an indented grouping of related data on a grid report by organizing the data into a standard outline style.

Using an outline style, you can collapse and expand sections of related data. Outlining is particularly useful when information displayed would otherwise involve repetitive entries. For example, you want to display sales for three years, , , and You also want data listed by month within each of the years.

Rather than having all data visible for every month of every year, you can use an outline to expand and view just that data you want to see immediately and keep other data collapsed, to be expanded later for quick comparisons. Multiple-page reports work in the same way. For example, if you are on page 4 of a multiple-page report and you want to collapse the data to the second level, then you will only be collapsing data that is displayed on the fourth page of the report.

When you have a very large set of data on a report, it can be easier to handle that data by grouping the report data into logical subsets and viewing only one of the subsets at a time. To group data into subsets, you can use the page-by feature. To retain page-by display, when saving the report, follow the below procedure.

Data pivoting enables you to rearrange the columns and rows in a report so you can view data from different perspectives. With data pivoting, you can do the following: Move an object a business attribute or a metric calculation and its related data from a row to a column. Move an object a business attribute or a metric calculation and its related data from a column to a row.

Change the order of objects in the rows. Change the order of objects in the columns. You can limit the data displayed in a report by specifying maximum and minimum values for a given metric. These maximums and minimums determine which rows of a result set are displayed in the report, and are called report limits. For example, the image below shows you a report that ranks all employee sales. You want to see only the results of the top ten employees. If you apply a report limit to restrict the data displayed to the top ten employees, the data used to calculate the sales rank is not affected.

Only the employees displayed changes, as shown in the image below. If the report has a filter, the filter is applied to the report data first, then the reporting limit is applied to further restrict the data returned in the report. Metric join types : These determine how tables of metric data usually numerical data, such as sales, costs, or profits are joined to each other. The image below shows the metric join typesetting in the Report Data Options dialog box.

Default : This option sets the metric to use the join typeset for that individual metric when that metric was created with the Metric Editor. If no join type was determined this way for the metric, this option sets the metric to use the join typeset at the project level. Inner : This option displays only the data common to all data source tables from which data is being gathered for this metric. Outer : This option displays all of the data from all data source tables from which data is being gathered for this metric.

Attribute join types : These determine how tables of attribute data business concepts, such as year, store, or item are joined together. Evaluation order : This determines in what order the various objects on a report are calculated. Objects that can affect the calculation of data to be displayed on a report include such things as metrics, report limits, and subtotals. Subtotals : These allow you to total metric data using a selected mathematical function. A report filter sifts the data in your data source to bring back the information that answers exactly what you require.

The report filter will be displayed in the Report Details Tab as shown below. You can configure the report details for a specific report, with the Report Details Formatting option in the Report Editor, or for the entire project, with the Project Configuration Editor.

Settings configured at the report level override settings configured at the project level. A hierarchy is made up of a group of related business attributes that are conceptually related to each other. Drilling allows you to view report data at levels other than that displayed in the report. You can investigate the data in your report quickly and easily with the help of drilling. Drilling automatically executes another report based on the original report to get more detailed or supplemental information.

You can set various options that determine how drilling works on a given report. These allow you to control how other users drill on the report when they execute it, or to preserve your own most useful drilling paths and drilling behavior for later reuse on a given report.

Examples are provided above. Drill down only: Users can only view data associated with objects lower in the hierarchy than the attribute on which they are drilling. When you drill on a report, you can have the page-by fields of the original report appear in exactly the same state in the drilled-to report, with all the same paging choices available. There are several ways that data shown on a report can be refreshed so that the report reflects the latest values in the data source. A cache is the stored results of a report query that has already been executed.

When the report is executed again, the system can quickly access the cache to display report data, rather than putting a load on the system to re-run the request to the data source. The following methods can be implemented to ensure that refreshed data is accessible when a report is re-executed:. If the stored cache is deleted, the system is forced to submit the request through the data source again, thus gathering the most recent data. Disable caching for a report : A system administrator can disable caching for a specific report so that a cache of results is never created in the system when that report is executed.

In this way, every time the report is re-executed, the query goes through your data source and thus returns the most recent data. You can see whether the results on a report have come from a MicroStrategy cache in two ways:. When a new MicroStrategy project is created, users with access to that project can create objects and store them only in their personal folders under that project. However, it is desirable sometimes to make many MicroStrategy objects available to other users.

For such a scenario, a user of the administrative group can create and place various MicroStrategy Objects under the public folder. Non-administrative users can only view and use the objects from the public folder, but they cannot delete or create new objects under the public folder.

To access the public folder, login to MicroStrategy developer as administrator and go to option Public Objects. On expanding the button, the following screen opens showing different public objects available in MicroStrategy. Schema Objects are the MicroStrategy Objects which are logical representation of the structures of a data warehouse.

These are the objects which are decided during the creation of a MicroStrategy project. Login to MicroStrategy developer as administrator. The following screen opens up showing the various schema objects. They are generally the descriptive data from the business. They help in carrying out drill-up and drill-down analysis on the data. Each report in MicroStrategy is built using some underlying objects which represent the business scenario. These objects together represent the set of data requested by the report user and also the relationship between the various data elements.

To get the report objects of a report, open the report and click the report object icon as shown in the following screenshot. Report Objects are very important from report design perspective as they decide which fields from the data source goes into the report and also the calculations applied on those fields. The reports created in MicroStrategy can be seen from a different prospective.

Some can be seen as only numbers and text, while some other only as graphs. We can also combine the textual and graphical visualizations together. Some can be seen as only numbers and text. While some other only as graphs. Consider the report created from the employee data earlier.

As we display only the textual information showing the employee ID and salary for each of the departments, it is an example of a grid report. We can choose an appropriate graphical visualization of the data from the gallery of visualizations available in MicroStrategy. In the following screenshot, we see the bar chart graph created for the above data set by simply clicking the bar chart visualization available in the right pane.

We can combine both the grid and graph charts by adding both the types of visualizations on one screen. The Slicing operation of a data set involves creating a smaller data set by filtering one dimension. It helps in analyzing the relationship between a given dimension and all the remaining variables of the data set. This will produce the following screenshot with the diagram showing the sales data for each category.

The Dicing operation of a data set involves creating a smaller data set by fetching multiple values of one dimension with respect to one value from another dimension. For example, we get the values of sales for different subcategory of products with respect to one single category. Here, there is a hierarchical relationship between the category and sub-category of products.

Following screenshots show the steps to dice the data with respect to the dimensions customer segment and product sub-category. We can also add the metric Profit. Next, let's create a filter using the dimension customer segment.

For this filter, we choose the value 'Customer segment'. However, we get the value of profit for all the values of sub-categories under this customer segment. Here, the data is diced across the subcategories for a given customer segment. Pivoting of data in tables is done when we want to swap the position of columns and rows. It is also called rotating data. The change in such structure produces different kinds of summaries of data. In the following screenshots, each row represents a Business Line and Sales value for each product line in different columns.

However, if we want to see the result as Product Line in each row and Business Line in each column, then we have to apply pivoting. Following are the steps to apply the pivot. Create the Table with the required dimensions and measures as shown in the following screenshot.

Here, sales is summarized and shown for each business line in each row. Using the visualization editor, swap the dimensions in the rows and columns. Use the swap button as shown in the following screenshot. Drilldown is the process of going down in a hierarchy of dimensions to get more granular values of the measures. In a data set with more than one dimension, which is linked to each other in an hierarchical fashion, we start with a dimension at the top and then gradually add more dimensions to get new granular values.

Create a visualization with dimension - product line and measure sales as shown in the following screenshot. Add the dimension category to the visualization below Product Line. As you can see the value of the sales column changes, reflecting the values for each category under the product line. Rollup is the process of moving up in the hierarchy of dimensions in a given data set. As we move up, the values of the measure become less granular and more summarized.

It is the opposite of drilldown. This process is called Rollup. Create a visualization with all the three dimensions mentioned above and sales as the measure value. Now, the result shows the summary at the Category level. To remove, right-click and choose remove from the options.

Metrics in MicroStrategy are the calculations performed on data. They are the derived columns which show results such as sum or average of some numeric values of a column in source data. They are useful in creating custom calculations required by business. Creation of a metric involves using the in-built functions already available in MicroStrategy.

The formula editor is used to create the formula for a metric. In this example, we aim to find the average sales for each sub-category under every category from the sales data. This can be done by creating a metric which uses the Avg Function to find the average sales. The steps to create and use this metric is as follows. Create a report with Category and sub-category as its two columns. Next, right click anywhere under the data source tab and near any of the measure fields.

A pop-up appears which shows the create metric option. In the Metric editor, write the formula for the average sales. Now, the metric AvgSales appears under the Dashboard Data as a measure. It can be dragged to the metric filed and then appears in the report. Nested Metric in MicroStrategy are the calculations in which one aggregation function is enclosed inside another. They are useful when in the data warehouse design, we do not have data stored at the required level of granularity.

In such case, we create an inner formula and an outer formula. Combining them creates the nested metric. In this example, we aim to find the average sales for each sub-category as compared to the total sales under each category. Next, right-click anywhere under the data source tab and near any of the measure fields. In it, we write the inner formula for the sum of sales for each category and the outer formula giving average sales for each category, corresponding to the sub-category.

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. 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.

The report contains product-sub category as attribute and unit price as well as shipping cost as the metrics. 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. The new metric appears under the list of metric of the data source. We drag it to the existing grid report. Metrics are the numerical values on which we can apply mathematical calculations and also compare them numerically.

MicroStrategy desktop provides some functionality to compare the values of two metrics using the filtering functions. If required, we can also create a derived metric to make complex comparisons based on some specific calculation. Create a visualization with the grid report using the superstore. Next, drag the two metrics - Unit price and Shipping cost - under the filter tab as shown in the following screenshot.

Enter some specific values in the filter condition of both the metrics, so that we can compare their values within a range. The following screenshot shows the result after entering the values. 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. 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.

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. 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 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. 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. 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. 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. On finishing the selection, we get the result in the report as shown in the following screenshot.

In MicroStrategy, we can create shortcuts to filters. For this, we have to use the results of an existing report as a filter for another report. The first report itself becomes a filter inside a new report. This type of filter is called a shortcut-to-a-report filter.

This is a part of MicroStrategy server edition and we will take some examples from builtin data sets in MicroStrategy server. Following are the steps to create a shortcut-to-afilter. Open the filter editor. Choose the filter definition area and double-click it. On the next screen, a filter dialog box pops up.

Enter the name of the filter, which we want to use or click browse and select the filter to use. Finally, the following screenshot opens which has the filter name and filter definition which is now a shortcut-to-a-filter. The reports created in MicroStrategy Servers are accessed by the users repeatedly to find the new results from the additional data gathered in the report source.

Hence, the data in the report needs to be refreshed both periodically as well as on demand by the user. The reports in MicroStrategy desktop version can be refreshed by simply reporting the data again. This is done by using the refresh button available in the menu. Currently, the report shows the data as shown in the following screenshot.

We add the category aquatic animals. On clicking the refresh button, we get the new result as shown in the following screenshot. When we run the reports created in MicroStrategy, they fetch the data from the warehouse to apply the calculations and generate a report. When multiple users request for the same report but with different range of values or different filter conditions, then the warehouse has to repeat similar calculations for each of the report and this hits the performance.

To avoid this, MicroStrategy uses intelligent cubes, which is an object sitting in the middle layer between reports and the warehouse. The Intelligent Cube is shared as a single in-memory copy, among the different reports created by many users. A set of data is returned from the data warehouse and saved directly to the Intelligence Server memory.

Multiple reports are built that gather data from the Intelligent Cube instead of querying the data warehouse. A dashboard is made up of multiple visualizations. It shows many attributes grouped into separate visualizations. When we place some common attribute or metric in multiple visualization, it is easy to study the variations among them. In the following example, we will create a dashboard showing some common attributes among the visualizations.

Create a grid visualization using superstore. We drag the attributes product - Subcategory and Shipping cost - to the rows box. Then we insert the second visualization into the report as shown in the following screenshot. Add all the above attributes as well as an additional attribute named unit price to the newly inserted visualization as shown in the following screenshot. Finally, apply different visualization types to these grids. We apply pie-chart to the top visualization and heat-map chart to the bottom visualization as shown in the following screenshot.

The result shows a dashboard with some common attributes used in the two visualizations. Different parts of the dashboard can be formatted for a better look using the formatting dashboard option available. In the following example, we are going format a dashboard using additional colors and highlighted areas. Consider the dashboard visualization we created in the last chapter.

Choose the Dashboard formatting option as shown in the following screenshot. Next, in the screen that pops up with formatting options such as selecting the font, fill color and border style, etc. Finally, the formatting is applied to the dashboard. The formatting reflects in both the visualizations present in the dashboard. MicroStrategy Desktop provides 10 standard graphs which are readily available to be plotted with a data source.

Each of them gives a different view of the data depending on the number of attribute or metrics we are going to use. The coloring features in each of them will make it easy to understand the different chunks of data present in a single data visualization. In the right most window of MicroStrategy Desktop, there is a visualization gallery, which shows options for 10 different graph types. Grid Visualization is the simplest form of visualization in MicroStrategy, yet a very powerful analysis method.

Here, data is presented as a grid with rows and columns as well as headers of the columns. It provides features such as sorting and drilling the data. After loading the required data set into the MicroStrategy Environment, we pull the required fields to the editor panel. This automatically creates the Grid visualization.

In the following example as shown, we pull the relevant fields from the data set and create a grid. Grid visualization provides a facility to sort on multiple columns simultaneously. Right-click on a column name and choose the option advanced sort. This brings us to a screen where we can select all the columns and their order to do the sorting. We can swap the columns and rows in the grid visualization to make a pivot report.

Just drag and drop the columns into rows as shown in the following screenshot. We can drill on an attribute on the grid visualization to get down to the values of the next attribute in the hierarchy. Right-click the column name and choose the drill option as shown in the following screenshot. A Heat Map visualization shows adjacent colored rectangles, each representing an attribute from the data set. It allows you to quickly grasp the state and impact of a large number of variables at one time.

For example, heat maps are often used in the financial services industry to review the status of a portfolio. The rectangles show a wide variety and many shades of colors, which emphasize the weight of the various components. The color of each rectangle represents its relative value.

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