+
+We can see our new database and two schema in Snowflake:
+
+
+
+### Add Snowflake connection in Sigma
+In Sigma, navigate to `Connections` and click `Create Connection` (Administrative rights in Sigma is required):
+
+
+
+Select `Snowflake` and give it a name.
+
+Configure the account details for your instance and also the `Write Access` section:
+
+
+
+Click `Browse Connection` and verify the sample data is available and the `SIGMA_QUICKSTARTS` database is also present:
+
+
+
+The won't be any data in the `SIGMA_QUICKSTARTS` database yet. We will be using the `SNOWFLAKE_SAMPLE_DATA` > `TPCH_SF1` > `PARTSUPP` table. The column we are interested in for our stock level use case is called `PsAvailqty`:
+
+
+
+
+
+
+
+## Demonstration Use Case
+Duration: 5
+
+For demonstration we will use an `Inventory Actuals` use case to build a data application that empowers teams to track and update inventory data.
+
+Using Snowflake sample data, users can view the current in-stock quantities for items, make adjustments to reflect actual counts, and preserve the updated records for future analysis.
+
+The workflow includes:
+
+
+
+
+
+
+
+### Add PARTSUPP table
+From the `Add element bar`, drag a table element onto the page and click `Select source`:
+
+
+
+Start typing `PARTSUPP` into the search bar and select the `PARTSUPP` table as shown. Be sure to choose this specific one, as there are several with different sizes.
+
+
+
+Lets enrich the data for the user by joining the `PART` table to this, including all columns:
+
+
+
+Sigma will configure the join for us. Review it for accuracy and click `Preview output`:
+
+
+
+We are presented with a graphical lineage and can make last minute changes. Click `Done`:
+
+
+
+After hiding some columns and grouping on three others, our table looks like this (renamed to `Reported Inventory`):
+
+
+
+Click `Publish`.
+
+### Add Filter Control
+Add a `List value` control to the page and configure it to use the `P Name` column as it's source. Be sure to enable the `Allow multiple selections` option:
+
+
+
+Rename the control to `Select Product Name`.
+
+Verify the new control filters the `Reported Inventory` table.
+
+Make note of the fact that some products come from different suppliers and carry different costs too.
+
+For example, the product named `aquamarine frosted tomato medium navy` is available from four different suppliers, each with a different brand and each having different costs and retail prices:
+
+
+
+
+
+
+## Configuring Actions
+Duration: 5
+
+Here is where we start to go beyond the typical capabilites of a anaytics product to add rich interactivity.
+
+### Add select column
+We want the users to be able to select one row of data from the table to edit.
+
+Add a new column, rename it to `Select` and set it's formula to `"EDIT"`.
+
+We can make the column standout a bit more using a conditional formula:
+
+
+
+### Adding actions
+With the table selected, click `Actions` in the `Editor panel` and configure the first action as shown:
+
+
+
+Click the `+` next to `Action sequence` to add another action. Select `Open modal` and `New modal`:
+
+
+
+This will create a new `Page` with the corresponding label. Since this is the first modal we have created this way, the page is named `Modal `:
+
+
+
+
+
+When we click on `Edit` in a single row, we can see the new modal (which is still empty) and also note that the underlying page control has been set to the customer name of the row selected.
+
+
+
+## Modal configuration
+Duration: 5
+
+While it may not be immediately obvious, we’ve already made a few design and workflow decisions. This is a common part of building any application (not just data apps). Often, it’s only after you start designing that the implications of small decisions become clear.
+
+It’s always crucial to ensure the workflow and functionality of an application are intuitive for the end user. The goal is to help them understand the interface and complete their work as efficiently as possible.
+
+
+
+In our use case, we aim to enable users to report an accurate inventory count as soon as they have that information.
+
+Once the values are updated in the input table, we will take a snapshot of its content, freezing the data into another Snowflake table for future analysis. This approach preserves the integrity of the original inventory data while providing flexibility for managers to make adjustments.
+
+Before we proceed with snapshotting, let’s set up the input table in Sigma to ensure it’s ready for use.
+
+Click the `Edit modal` button. We are taken to the `Modal 1` page, where we can work with all the functionality Sigma has to offer.
+
+Two buttons are provided for us in the modals "footer". The buttons have preset actions available (but not configured to do anything yet) so that you can configure them to do whatever is needed. These can also be hidden if they are not required (in the `format` options section).
+
+There is also an action to control when the modal is closed (using the `X` button on the modal). This can be used in many ways. For example, we may want to take the user to another workbook page upon close of the modal:
+
+
+
+Rename the modal's title to `Stock Adjustments`:
+
+Feel free to adjust the modals' styling using the `Format` option in the `Editor panel`.
+
+Using the `Element bar`, drag a `Linked Input Table` to the modal cavas.
+
+Click the `Select source` button. The source we choose will act as the "starting point" for the stock adjustments.
+
+Sigma will suggest we use `Reported Inventory`; select that.
+
+
+
+Since the same part can come from different suppliers, we need to make sure we present all those items so that the correct inventory quality can be adjusted.
+
+To do this, we simply add multiple columns to be user as unique identifiers.
+
+
+
+Also add the column `Ps AvailQty` from the `2. Add more column(s) to your linked input table (optional).` section. We want to display the current inventory count for the select item(s) to the editor.
+
+Click `Create input table`.
+
+
+
+To keep this demonstration "Quick", we will add one column called "Adjusted_Qty". This will be the only place a manager can make edits, but will demonstrate the workflow simply.
+
+Add an additional column and rename it to `Adjusted_Qty`. Be sure to change it's "type" to `number`:
+
+
+
+
+
+Rename the input table to `Please provide adjusted stock quantities`.
+
+Before we can do a quick test, we need to set the input table to allow others to edit it:
+
+
+
+Click `Publish`.
+
+Set the workbook into published version:
+
+
+
+Searching again for the product `aquamarine frosted tomato medium navy`, we can click the `EDIT` link in the first row.
+
+Our modal now looks like this, and we can update the row(s) we are interested in by clicking the `Edit Data` button:
+
+
+
+As a validation test, update one row's `Adjusted_Qty` value, hit `enter` and click `Save`:
+
+
+
+`Close` the modal.
+
+### Add tracking columns
+Input tables come with two column that indicate who and when the last edit was made, each time a row is edited. Lets add them.
+
+
+
+Lets also set an action `ON CLOSE` so that when the modal is closed, the control filter is reset on `Inventory Master`. Little touches like this mean alot to users and save click-time too:
+
+
+
+Next we will setup snapshotting, but first lets check in Snowflake to see where the input table stored this data.
+
+
+
+
+## Warehouse view
+Duration: 5
+
+By design, input table data is not made directly available in Sigma via the warehouse connection. This is by design. This allows Sigma to apply sophisticated operations when working with input table data that has significant benefits to the user. Performance, multi-user access and reliability when editing data are just a few of the things driving this design decision. It would not be unreasonable to characterize an input table as a `Data API` than a conventional table.
+
+That said, we still need an easy way to leverage input table data for use as a "typical" table would be in the warehouse and in Sigma's UI.
+
+To simplify this Sigma provides support for [Warehouse Views](https://help.sigmacomputing.com/docs/create-and-manage-workbook-warehouse-views).
+
+
+
+We can now use the results returned from the warehouse view when we create snapshots to capture "point-in-time" changes to stock levels, perform additional calculations and enrich the data with other information too.
+
+Sigma has made creating a warehouse view simple; no SQL skills are required. It is done directly in Sigma's UI.
+
+We will need to be in `edit` mode in Sigma and return to the modal page. The `Inventory Master` tables should not be filtered as we want all the rows included in our view.
+
+Using the input table's menu, click to create the warehouse view:
+
+
+
+Make the name `SNAPSHOT_AND_INVENTORY_ADJUSTMENTS_VIEW` anc click `Create`:
+
+
+
+Sigma will start the process, and when finished we will see this information here:
+
+
+
+We can copy the path of the view for later use. Our path is:
+```code
+SIGMA_QUICKSTARTS.SNAPSHOT_AND_INVENTORY_ADJUSTMENTS_SNAPSHOTS.SNAPSHOT_AND_INVENTORY_ADJUSTMENTS_VIEW
+```
+
+There is also a page in Sigma to show the status of all warehouse views:
+
+
+
+### Use case design decision time
+It took a long minute to realize that several users might be using the input table to adjust inventory levels and we need to account for that. They ***might*** be doing it in real-time and collide but they input table itself can help with that.
+
+The more likely senario is that they entering data whenever and we want to snapshot those changes by user and date/time on demand.
+
+
+
+To account for that, we **DO NOT** want to try to update any data in the input table in Snowflake directly. This is always a bad idea and may have unexpected results. Instead we will create a metadata table that will store information on who made what changes, and when, plus some other related details. This removes the need to try and interact with the input table data directly in Snowflake.
+
+
+
+
+## Metadata table
+Duration: 5
+
+The Metadata Table acts as an index for managing and tracking the snapshots created by the Snapshot Procedure. It provides a centralized summary of all snapshots, ensuring clear visibility and efficient historical tracking of inventory adjustments.
+
+- Records metadata for each snapshot to enable version control and quick identification of snapshots.
+- Facilitates incremental snapshots by maintaining a reference to previously captured rows, ensuring no duplicates are included in subsequent snapshots.
+
+### How It Works
+
+**1: Snapshot Registration:**| SNAPSHOT_METADATA Table Schema | +||
|---|---|---|
| Column Name | +Type | +Description | +
| SNAPSHOT_ID | +VARCHAR | +Unique identifier for each snapshot. | +
| SNAPSHOT_TIME | +TIMESTAMP | +Timestamp indicating when the snapshot was created. | +
| SNAPSHOT_NAME | +VARCHAR | +Name of the snapshot table (includes a timestamp). | +
| SUPPLIER_KEY | +VARCHAR | +Supplier identifier associated with the row. | +
| PART_NAME | +VARCHAR | +Name of the part being adjusted. | +
| BRAND | +VARCHAR | +Brand of the inventory item. | +
| MANUFACTURER | +VARCHAR | +Manufacturer of the inventory item. | +
| Snapshot Table Schema | +||
|---|---|---|
| Column Name | +Type | +Description | +
| MANUFACTURER | +VARCHAR | +Manufacturer of the inventory item. | +
| BRAND | +VARCHAR | +Brand of the inventory item. | +
| SUPPLIER_KEY | +NUMBER | +Supplier identifier associated with the row. | +
| PART_NAME | +VARCHAR | +Name of the part being adjusted. | +
| ORIGINAL_QTY | +NUMBER | +Original quantity before adjustment. | +
| ADJUSTED_QTY | +NUMBER | +Adjusted quantity entered by the user. | +
| DIFFERENCE | +NUMBER | +Difference between the adjusted and original quantity. | +
| PERCENT_CHANGE | +NUMBER | +Percentage change between the adjusted and original quantity. | +
| LAST_UPDATED_AT | +TIMESTAMP | +Timestamp indicating when the adjustment was made. | +
| LAST_UPDATED_BY | +VARCHAR | +User who made the adjustment. | +
+
+In the snapshot table we can see our one row that was edited:
+
+
+
+
+
+
+## Snapshotting
+Duration: 5
+
+There are many ways to design an interface for snapshotting; lets explore just one. We will make some assumptions but when we are done, the basics will be clear and you can alter the design any way that suits your requirements.
+
+### How to call it with Sigma
+Sigma supports stored procedures thru actions, and we will use an action to call our snapshot script that is stored in Snowflake.
+
+For those may not already know, A stored procedure is a reusable block of SQL code stored in the database that performs specific tasks. It simplifies workflows by allowing complex operations, such as data manipulations and calculations, to be executed as a single command.
+
+
+
+Our stored procedure will create a snapshot of inventory adjustments by leveraging the Warehouse View (WV) to ensure consistent and user-friendly column names. It ensures that only the relevant rows (matching current edits in the input table) are included in the snapshot.
+
+We already created our stored procedure in the last section.
+
+The stored procedure is located here:
+
+
+
+### Update Modal in Sigma
+After our manual test, we know that the snapshotting works. Return to Sigma and update the actions on `Modal 1` to allow users to trigger it.
+
+First, open `Mondal 1's` format panel and uncheck the option for `Show close icon`. This removes the `X` icon from the upper right corner of the modal.
+
+Next we want to change configure our footer buttons for text and action.
+
+#### Primary button
+Set the text for the `Primary button` to `Take a Snapshot`.
+
+Change the `Secondary button` to `Return to Inventory Master` while we are on this screen anyway:
+
+
+
+Next, configure an action to trigger our stored procedure in Snowflake:
+
+
+
+#### Secondary button
+Configure an action for the button to return the user to `Inventor Master` and clear the control so that the table is not filtered when the user is landed there:
+
+
+
+`Publish` the workbook and return to the `published version`.
+
+
+
+
+## Validation testing
+Duration: 5
+
+
+
+Lets perform to editing "runs" in Sigma, each time saving the edits and taking a snapshot. The expected outcome will be two additional snapshot tables.
+
+### Reset the text environment
+While not required, it may be helpful to know how to quickly reset the data so that the test results are more easily seen. Here is how to do that:
+
+**1:** Clear the one cell that was edited (to have the "1000" value). Do this directly in the Sigma UI. Just click on the cell that has the value, press the delete key and then enter. Save the input table data. It will not matter that Sigma will record this action in Snowflake, we are only concerned with rows that have values for `Ajusted_Qty`, so this edit will be ignored when we snapshot.
+
+**2:** Truncate the metadata table to remove all rows.
+```code
+TRUNCATE TABLE SIGMA_QUICKSTARTS.SNAPSHOT_AND_INVENTORY_ADJUSTMENTS_METADATA.SNAPSHOT_METADATA;
+```
+
+**3:** Drop all previous snapshots.
+We like to list them out before just deleting table. Run this script to do that:
+```code
+-- List out the snapshot tables. Copy paste and run the output
+SELECT 'DROP TABLE SNAPSHOT_AND_INVENTORY_ADJUSTMENTS_SNAPSHOTS."' || TABLE_NAME || '";'
+FROM INFORMATION_SCHEMA.TABLES
+WHERE TABLE_SCHEMA = 'SNAPSHOT_AND_INVENTORY_ADJUSTMENTS_SNAPSHOTS';
+```
+
+Right-click the box shown below and select `Copy`:
+
+
+
+Paste in the script and run the row(s) to delete the snapshots:
+
+
+
+### Testing
+
+In Sigma, select a product to edit, change a few values, `save` the changes (pause for a few second to make sure the data landed) and then click `Take a Snapshot`:
+
+
+
+After the `Take a Snapshot` button returns to active, click `Return to Inventory Master`.
+
+Repeat the editing, selecting a different product to edit:
+
+
+
+
+
+Return to Snowflake and check that there are two snapshots and they have only the rows from run one and two:
+
+**Run one snapshot table:**
+
+
+
+**Run two snapshot table:**
+
+
+
+Now that we have verified that the data app is working, we can do something with all this new data.
+
+
+
+
+
+## Viewing Snapshots
+Duration: 5
+
+Over time we will collect many snapshots and we may want to look at then individually or in one table so that we can explore the data futher.
+
+Lets just assume that we want to look at all of them as one big table and leave the analytics part to the assumption that is understood.
+
+We will not immediately know that all the table names, and using the connection browser to join them would required on-going maintence too.
+
+Instead, lets follow a the path we have already taken in this QuickStart and leverage Snowflake stored procedures and a view to create single table that unions (combines) every available snapshot. Users will be able to click a button to refresh the union to account for newly created snapshots.
+
+### How it will work
+
+**1 Use a Snowflake view:**
+
+Click the new button to run the stored procedure.
+
+Next, add a new `Data` > `Table` element to the page, selecting the `Data Apps for QuickStarts` connection and `SQL` as the source.
+
+Paste this SQL query into the editor:
+```code
+SELECT *
+FROM SIGMA_QUICKSTARTS.SNAPSHOT_AND_INVENTORY_ADJUSTMENTS_SNAPSHOTS.ALL_SNAPSHOTS_VIEW
+```
+
+Click `Run`.
+
+We can now see all the snapshots unioned together into one table.
+
+Also notice that we can see two columns that were created programmatically by our snapshotting stored procedure earlier.
+
+
+
+
+
+As a last step (and we leave the details up to you to configure as "extra credit"), create another table that uses the `Custom SQL` table as its source. Then we can join the `PARTSUPP` table to it so we can bring in the `Ps Supplycost` column and use that to calcuate the `Dollars Lost` amount, The percent change and dollars lost numbers are crazy large; we did not worry about using reasonable values when we were editing inventory numbers earlier:
+
+
+
+We could do so much more to visualize the new data but the point is proven; data apps in Sigma are powerful. For example:
+
+
](https://twitter.com/sigmacomputing)
+[
](https://www.linkedin.com/company/sigmacomputing)
+[
](https://www.facebook.com/sigmacomputing)
+
+
+
+