Counts/Aggregate datasets: everything you need to know
The Counts/Aggregate dataset is the best way to record and analyze data in a tabular format. This type of dataset is ideal when you want to gather and record daily, monthly, or yearly totals for something. Unlike a Custom dataset, where records are analyzed based upon each record's timestamp, records in the Counts/Aggregate dataset area analyzed by the day, month, or year you provide.
In other words, if you have a spreadsheet where you are tracking totals by day (such as library head counts), month (such as ILL or reference transactions), or year (such as acquisitions or expenditures), the Counts/Aggregate dataset will be a good fit.
With these datasets, you can analyze your data with the following reports:
- Overview: datatable containing the daily/monthly/yearly totals
- Field Aggregates: provides the count, sum, average, median, minimum, and maximum of your data
- Charts: analyze one or more fields in a bar, stacked, or line chart
- Distributions: provides a breakdown of your data by year, month, day of the week, and weekdays vs. weekends
- Trends: allows you to compare data for the same time period over a number of years (e.g. compare fall semester totals for the current year against the previous 5 years)
In this Springboard, you'll learn how to create and configure a custom dataset, as well as record, upload, and analyze data.
Counts/Aggregate datasets are only available to LibInsight Full customers. If you're interested in upgrading to the Full version of LibInsight, contact our Springy Sales team.
To create a new dataset, Admin users can go to Admin > Manage Datasets and click the Add New Dataset button.
Before you begin, you may find it helpful to do a little planning. This can make the process of creating your dataset go more quickly.
- What recording mode is appropriate for your data? You can enter aggregate totals by day, month, or year. Each option has implications for how you can analyze your data.
- Daily: enter aggregate totals for each day of the year. This will allow you to analyze your data by day, month, or year.
- Monthly: enter aggregate totals for each month of the year. This will allow you to analyze your data by month or year, but not by day.
- Yearly: enter aggregate totals for each calendar year. This will allow you to analyze your data by year, but not by month or day.
- What data do you want to collect? It can help to sketch out a list of all of the data you want to collect and analyze.
- Once you have a list, consider what type of field is best suited for that data. See the Available field types panel below to learn more about each type.
- In addition to the required timestamp, all submissions will include an optional Entered By field (who "owns" the record), as well as an optional Internal Notes field where you can leave a comment about the data.
- Who should have access to the dataset? By default, only Admin users are allowed to manage, record data to, and analyze a dataset. However, you can choose to extended each of those permissions to selected Regular users, or all Regular users in your system. For example, if you only want a few people to add data to your dataset, you would extend them Record permissions. But, if you want everyone in your library to be able to view and analyze (but not edit) the data, you could choose to give Analyze permissions to all Regular users.
|Field type||Ideal use||Options||Analysis features|
|Numeric||Choose Numeric Fields to capture numerical info (integers only), ex: # of attendees, # of items, # of minutes spent preparing, etc. Use the Instructions field to instruct users on how to enter data, ex: "Record time in minutes".||None||When analyzing data, you can run statistical analysis on the numeric field to capture things like average values, totals, maximum/minimum/median values, etc.|
|Monetary||Use this field when entering amount values like money or cost. It accepts whole amounts and up to 2 decimal points. Amounts will be displayed using the Currency Symbol from your System Settings.||None||When analyzing data, you can run statistical analysis on the monetary field to capture things like average values, totals, maximum/minimum/median values, etc.|
|Calculated||Use this field when calculating the sum, difference, product and quotient of 2 or more Numeric or Monetary Fields. Because this field types uses information in other fields, its contents cannot be edited except on this screen.||
Replace field_* with your Numeric or Monetary field ID found in the Fields drop-down.
|When analyzing data, you can run statistical analysis on the calculated field to capture things like average values, totals, maximum/minimum/median values, etc.|
- Create or copy a Counts / Aggregate dataset
Learn how to create a new dataset, copy fields from an existing dataset, assign permissions, and set up fields.
- Editing the info, styles, and recording mode of a Counts / Aggregate dataset
Learn how to edit an existing style's name, description, and (if empty) recording mode. You'll also learn how to add custom JS/CSS code and/or a custom HTML footer to the dataset's Record Data page.
- Editing fields in a Counts / Aggregate dataset
Learn how to add, edit, or remove fields from an existing dataset.
There are two primary ways you can add data to your custom dataset:
- Manual entry: users who have permission to record data can enter it manually via the Record Data page in LibInsight. Users can add data for multiple days/months/years at once using a convenient table layout.
- If your dataset contains Calculated field types, the calculations will update automatically as data is entered into the appropriate fields.
- Upload in bulk: in addition to manually adding individual records, you can upload data in bulk via a CSV or Excel file. LibInsight will provide you with the list of field names your file must include in order to be uploaded successfully.
- In general, the column headings in your spreadsheet must match the field names in your dataset. All required fields (such as the Start Date) must be present, but optional fields (such as Internal Notes) may be omitted.
- When uploading a file, make sure that the date format in your spreadsheet adheres to one of the accepted date formats. You will find a list of these under the File Upload tab when uploading your data.
Users who have permission to add data to a Counts/Aggregate dataset can also edit any existing entry.
- Recording or uploading data to a Counts / Aggregate dataset
Learn how to manually enter or bulk upload data to a Counts/Aggregates dataset.
When analyzing a Counts/Aggregate dataset, you'll find the following reports:
- Overview: provides a summary table of your data within the selected date range. For example, if you are recording data by month, this will provide the total for each field by month, ending with a grand total for the entire period.
- Field Aggregates: provides a statistical summary of your data, including the Count, Sum, Average, Median, Minimum, and Maximum values for each field.
- Charts: allows you to visualize your data for one or all fields, using a bar, stacked, or line chart. You can even select individual fields to compare, as well.
- Distributions: breaks down the data from one or more fields over time. This includes totals by year, month, day of the week, and weekday vs. weekend.
- Trends: allows to see how the totals of your numeric data has changed over time (i.e. the past 2 years, 3 years, 5 years, or even 10 years). In addition, you'll see year-over-year changes and the percentage change against the first year of the report.
In addition, LibInsight includes other tools to help you analyze, visualize, and share your data with others:
- Dashboards: dashboards allow you to display charts of key data points from one or more datasets on a single page. Dashboard pages can be public or private, allowing you to create and share dashboards internally with staff or with the public.
- Cross-Dataset Analysis: allows you to compare up to 4 variables from across one or more datasets. This can provide some really useful insight for seeing trends across services or resources over time.
- Analyzing and exporting a Counts/Aggregate dataset
Learn how to generate a report for a specific date range and export your data. This includes an overview and example of each available report option.
- Comparing multiple datasets using the Cross Dataset Analysis tool
Learn how to generate a cross-dataset analysis report to compare multiple datasets at once.
- Creating a dashboard
Learn how to create a dashboard to visualize and share key data points from your datasets.