This article focuses on introducing the basics of Ad Hoc Views in Lambda Analytics.
Ad Hoc Views
Ad Hoc views are the arena for exploring data through visualizations, filters, and the selection of fields and measures. They are the key transitional stage between data sources and reports or dashboards in the Lambda Analytics Information Hierarchy.
You can use Ad Hoc views to first select which data you would like to include from a data source by selecting fields and measures, and then decide how you would like your data to be visualized and filtered.
To generate finalized reports, you would need to edit your data through an Ad Hoc view in the Ad Hoc Editor. The Ad Hoc Editor allows you to select from the following view types:
Tables: Used to view values in the database and to summarize values in the columns.
Charts: Used to compare one or more measures across multiple sets of related fields.
Crosstabs: Used to aggregate data across multiple dimensions.
Tables are the simplest view type, and primarily consist of fields. Tables can easily be sorted, grouped, summarized, and filtered. You can also conditionally format tables when you have saved your Ad Hoc view as a report.
Tables are best for reports that require finding specific values quickly, and that display both qualitative and quantitative data.
Tables consist of columns, rows, and groups:
Columns in a table correspond to the columns in the data source. They are included by adding fields or measures to the table in the Ad Hoc view.
Rows correspond to rows in the database. The information in each row depends on which columns are included in the table.
Using groups, rows can be grouped by identical values in any field with intermediate summaries for each grouped value. For example, a table view of product orders might contain columns to show the dates and amounts of each order, and its rows might be grouped by city and product.
Charts are useful when you would like to visualize your data, and can summarize your data graphically. When using charts, you will need to identify what your measure will be, like your number of users, time spent learning, or course completions.
Charts are best for reports that require the illustration of quantitative data, as they can easily visualize trends and relationships.
Types of charts include bar charts, line charts, and pie charts. With the exception of time series and scatter charts, each type of chart compares summarizes values for a group. Time series and scatter charts use time intervals to group data.
Crosstabs are a more compact representation than tables, as they only show computed values rather than individual database values. With crosstabs, you can summarize and aggregate your measures in a similar way to using charts, but you can also provide the specific details and information that you would have when using tables.
Crosstabs are best for reports that require drilling down on your data, and that summarize and aggregate your results.
Crosstabs also require both a field and a measure, and can be used to sort results in ascending or descending order. Columns and rows specify the dimensions for groups, while cells contain the summarized measurements.
Elements of an Ad Hoc View
The following Repository objects provide a prepared connection to a data connection for Ad Hoc view creation:
Topics: JRXML files created externally and uploaded to Lambda Analytics as a basis for Ad Hoc views.
Data Source: Virtual views of a data source that present the data in business terms, allowing for localization and providing data-level security.
The Ad Hoc editor contains the following panels, from left to right:
Data Source [Data Connection Name]: Contains the fields, dimensions, and measures available in the source data sources and/or topic.
Ad Hoc View: The main view design panel.
Filters: Defines a subset of data to retrieve from the data source.
You can also duplicate and edit an existing Ad Hoc view to create a new Ad Hoc view.
Using Out-of-the-Box Ad Hoc Views
Running an Ad Hoc View
Like reports, Ad Hoc views can be run by simply double-clicking the title, or by right-clicking the corresponding row and selecting Open from the context menu.
From here, you will see a variety of panels on the left-hand and right-hand sides of the page, but your data will be displayed in the centre, known as the Ad Hoc canvas.
Fields and Measures
On the left-hand side are the Fields and Measures panel. These are the values that are available to use in the Ad Hoc view.
In each of the panels, you will see that the tables have expand options, which open up to show individual fields and measures.
To add these pieces of data, simply double-click on the field or measure, and drag and drop it directly on to the canvas. You can also place them specifically in the Columns/Groups/Rows area directly above the canvas.
On the right-hand side is the Filters panel, where any existing filters for your Ad Hoc view can be seen. These may range from a variety of filters, like usernames, statuses, or course names. When working with charts, you may also notice the Data Level slider, which allows you to choose much data you can see.
Below the top menu navigation bar is the Toolbar. Here, you will see a variety of things that you can do with the Ad Hoc view, like preview, save, export, and undo/redo/reset.
You will also notice two drop-down menus, which allow you to change the Ad Hoc view type and the amount of data shown on the canvas.