The Finance dataset allows you to analyze your library's revenues and expenditures over time. This includes a visual breakdown of expenditure and revenue categories, with year-over-year differences and annual trends. You can even analyze individual line items to see changes over time.
In this Springboard, you'll learn how to create and configure a Finance dataset, as well as record and analyze data.
Finance 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 revenues and expenditures are you going to be tracking? In Finance datasets, your revenues and expenditures are recorded by category, so knowing what you exactly you want to track is essential. For example, you could track expenditures for personnel costs, monographs, serials, etc. For revenues, you could track things like overdue fines, photocopier charges, grants, etc.
- 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 extend 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.
- Create a Finance dataset
Learn how to create a Finance dataset; define the dataset's permissions; and set up your dataset's categories.
- Managing categories in a Finance dataset
Learn how to add, edit, and delete categories in an existing Finance dataset.
- Editing the info and recording mode for an existing Finance dataset
Learn how to customize an existing dataset's info, description and (if the dataset is empty) recording mode. You will also learn how to add optional custom JS/CSS code and a custom page footer.
- Editing an existing dataset's user permissions
Learn how to add, edit, or remove permissions for Regular users in an existing dataset.
There are two primary ways you can add data to your finance dataset:
- Manual entry: users who have permission to record data can enter it manually via the Record Data page in LibInsight. Users will permission to record data will be able to manually enter values by date in all of the expenditure and revenue categories in the dataset.
- Upload in bulk: in addition to manually entering data to categories individually, you can upload data in bulk via a CSV or Excel file. LibInsight will provide you with the list of category names your file must include in order to be uploaded successfully.
- In general, the column headings in your spreadsheet must match the category 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 you select the date format that matches the format that was selected for the dataset.
- Recording or uploading data to a Finance dataset
Learn how to manually enter or upload data to your dataset.
- Managing uploaded files
Learn how to view, download, and delete files that were uploaded to your dataset.
- Managing uploaded files
When analyzing a Finance dataset, you'll find the following reports:
- Overview: provides a breakdown of each category's totals for the selected date range, both in a data table and in a pie chart. In addition to the total amount for each category, you will also be provided with a year-over-year increase, as well. The sum total of all expenditures and revenues are included, as well.
- Note: When the dataset's Recording Mode is set to Monthly, an additional Monthly Details tab with month-by-month data tables will also be available.
- Trends: allows you to compare the current year to previous years so you can analyze trends in your data. This will not only help you visualize these trends, but you will also be able to see details such as year-over-year changes and a comparison of the current year to the first year included in your report.
- Line Items: allows you to analyze the totals of one or more categories over time. This will allow you to track the growth of specific expenditures and/or revenues over time, with statistics providing both the percentage of growth and of a percentage of your grand total of revenues and expenditures for the period.
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 a Finance dataset
Learn how to generate a report for a specific date range. 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.