• 🎊 New features
• 1. Main new features
• a. Charts: “Compare to” feature
• b. Sheets: Powerful date picker
• c. Data model
• Manage data source model
• Manage sheet model
• Column sharing
• d. Big Query connector
• 2. Other new features
• a. URL formatting
• b. Charts: improvement of zoom feature
• c. Python library extended
• d. Formula editor functions extended

🎊 New features

This release brings a lot of bug fixes and UI improvements.

1. Main new features

a. Charts: “Compare to” feature

This feature makes it easy to visualize and compare your data against specific benchmarks or targets, whether you're using bar charts, line charts, or indicator charts.

• For bar and line charts, you can add constant goal lines or aggregated lines (SUM, AVG, MIN, MAX) to your chart.
• For indicator charts, you can add constant goals or aggregated goals (SUM, AVG, MIN, MAX), and see how the last value compares to the goal value, including the percentage difference. You can also compare the last value with the previous one, to see the change over time.

💡 Note:

• the comparison feature is only available for bar charts, line charts, and indicator charts,
• It requires at least one series and one grouping to make it work.
• The aggregated comparisons rely on the chart view configuration (series, groups, filters).

Example:

• For example, let's say you're tracking your company's monthly revenue, and you want to set a target of $100,000. With "Comparison lines," you can easily add a constant goal line to your chart to see how your actual revenue compares to your target. Or, if you're looking at data over time, you can add an aggregated line (such as an average or minimum value) to quickly see trends and identify outliers.

Example of how to do it in KAWA:

b. Sheets: Powerful date picker

In KAWA, it’s now possible to filter views based on important dates with ease using our new date picker!

• Grid and pivot view: the date picker will automatically appear when there is a date or datetime column in the primary keys of the underlying data source.
• Chart view: the date picker will appear when the first group level of the chart is a date or datetime column.

Our date picker offers a variety of powerful filtering options:

• Predefined useful presets
• Absolute date ranges
• Relative date ranges.

This means you can quickly filter your data to see only what you need to, when you need to.

c. Data model

This feature is designed to align with the existing data preparation and governance concepts in the market, and will allow users with the right permissions to decide which columns appear in all sheets, set default aggregations, formatting, and more. Users without permission can still play around with grids in their own sandbox without sharing them.

Manage data source model

To manage the data source model, users need to have the "Manage data source" permission.

With this permission, users can share data sources and define their model. Defining the model allows users to

• specify the scope of the data by applying filters upstream and
• customize each indicator by
• renaming it,
• defining a default aggregation,
• setting an attribute,
• formatting the data
• defining it as a default filter or as default field in all newly created views.

This configuration happens in the “Model” tab of the datasource:

Manage sheet model

Similarly, to manage the sheet model, users need the "Sheet modeler" permission.

This permission allows users to define the model of the sheet by

• specify the scope of the sheet’s data by applying filters. These filters will be applied to all the views of the sheet.
• configuring computed columns:
• renaming them,
• defining default aggregations,
• setting attributes,
• formatting data,
• defining them as default filters or as default fields in all newly created views
• moving them to trash

💡 Note:

Indicator columns inherit configurations from the data source model and cannot be modified in the sheet model.

Column sharing

In sheets, all newly created columns are not automatically shared across views. Instead, it requires an explicit action in the sheet model tab to make the column visible for everyone.

To share columns across sheets, users need the "Column sharing" permission. Only users with this permission are allowed to share columns across views.

d. Big Query connector

KAWA now supports connecting to Big Query data sources! With this new feature, users can easily create a connection to their Big Query data and create a data source that is connected to it.

Steps:

1. Create a new data source by connecting to an external system.
2. Click on the “+” icon next to the data provider dropdown menu.
3. Select "Big Query" and enter your Json configuration details.
4. Test the connection to ensure that it is successful.
5. Create your new Big Query connection.

Once you have created your Big Query connection, you can select any database and table to create a new data source that is connected to it.

2. Other new features

a. URL formatting

Users can now format text columns as URL links, allowing to redirect to associated pages by clicking on the link. Additionally, users can use another column's values for the URL's labels by selecting the column in the dropdown below.

To do so, use the format data feature on the concerned text column and check the “Format as link” option. By default, the link labels is based on the values in the current column. However, if you prefer to use a different label for your links, you can easily select another text column from the drop-down menu.

b. Charts: improvement of zoom feature

• Zoom capabilities are enhanced in our bar and line charts. With this update, users can now use the zoom feature for all types of groupings, regardless of whether they are date or datetime columns. Previously, this feature was only available for datetime column groupings.
• When the first group level is a date or datetime column, the zoom feature is automatically linked to the date picker. This enables users to easily zoom in on specific date ranges and analyze their data with greater precision.

c. Python library extended

The latest release of our Python library includes several new functions to enhance your user management experience. Here are the details of the new functions:

1. create_users(user_id_list): This function allows you to create new users by specifying their user IDs in a list. With this function, you can quickly and easily add multiple users to your system at once. The users will be created with password, they can use the reset password feature to set one. This won’t be needed when KAWA is connected to SSO (for instance Kerberos etc).
2. toggle_users_status(user_id_list, active=False): This function allows you to toggle users by specifying their user IDs in a list. When a user is disabled, they will no longer be able to log in to your system and their session will be immediately closed.
3. add_users_to_workspace(user_id_list, workspace_id, permissions=None): This function allows you to add users to a specific workspace by specifying their user IDs in a list, along with the ID of the workspace. Additionally, you can also specify the permissions for each user by providing a list of permissions. The permissions parameter is optional.
4. remove_users_from_workspace(user_id_list, workspace_id): This function allows you to remove users from a workspace by specifying their user IDs in a list, along with the ID of the workspace.

d. Formula editor functions extended

Several new functions have been added to the formula editor. Here are the details of the new functions:

1. IF: The IF function has been extended to take an unlimited amount of then arguments. With this update, you can now create more complex conditions and outcomes.
2. IF_ELSE_NULL: This function is the same as IF, but without the else argument. If all the conditions are false, it will return NULL.
3. IN_LIST: This function will check if a value is the same as one of the items in a list. For example, IN_LIST(auto, pharma, indus) will return false, while IN_LIST(auto, pharma, auto) will return true.
4. NOT_IN_LIST: This function is a shortcut for NOT(IN_LIST).
5. WTD, STD, QTD, MTD, YTD: These functions all take three arguments (the third is optional). The first argument is the date to check, the second argument is the offset of the reference date, and the third is the optional reference date. By default, we use today as the reference date. The offset is in units (week for WTD, etc.).
6. STD_YoY, QTD_YoY, MTD_YoY, WTD_YoY: These functions all take three arguments (the third is optional). The first argument is the date to check, the second argument is the offset of the reference date in years, and the third is the optional reference date (by default, today).