This QuickStart presents common challenges when working with dates. Sigma can be used to manipulate dates to get the desired results, quickly and easily.

There are many ways to solution with dates in Sigma. Not every solution is covered and you may even found a better method. Suggestions and feedback is always appreciated.

This QuickStart assumes you have a working instance of Sigma and the connection called Sigma Sample Database.

We will use the Sigma provided RETAIL.PLUGS_ELECTRONICS.PLUGS_ELECTRONICS_HANDS_ON_LAB_DATA table so that you can recreate each QuickStart Step in your own Sigma environment.

Target Audience

Anyone who is looking for solutions to date challenges or just want to learn new date methods.

Prerequisites

1: A computer with a current browser. It does not matter which browser you want to use.
2: A Sigma account.

What You'll Learn

How to apply Sigma functions to date challenges.

What You'll Build

We will cover a large number of methods for working with dates in Sigma. Date logic can be confusing so we will start with the basics to show how Sigma makes the simple stuff easy and then get more complex to show how Sigma makes the hard stuff possible all through an easy to used interface.

Let's start simply by presenting the standard ways to alter/adjust a date column.

Create a new Workbook and place the PLUGS_ELECTRONICS_HANDS_ON_LAB_DATA table on the page. You can just take all the columns. We are mostly interested in the Date column right now but will use the others as we add logic later.

Click on the Date columns down arrow and select Truncate date. This is one way to adjust how the Date column will be modified.

If you select the Day option, notice that the column name is changed to Day of Date

Reset the Date column back the the default (use "Remove date truncate" or the back icon if you are in edit mode).

Click on the Date columns down arrow and select Format date. This is another way to adjust how the Date column will be modified:

Feel free to experiment with the available options, resetting to the original when done.

Sigma supports applying custom formats to date columns. You can do this by selecting the Date columns menu and then Format and Custom:

Setting the Format string to the code below will cause the popup to show you a sample of the output. This is quite useful to know your string is correct before applying it.

%a %B %d %Y

A full list of custom format strings is available here.

Feel free to experiment and then reset the Date column back to the default when done.

Another way to use custom date formatting is to apply a Function in the formula bar using one of the many DateFormat functions.

For example, you may want to get the full month-name from a date column.

Create a new column and rename it Month of Date.

Place this code in the formula bar and click the checkmark (or press Enter):

DateFormat(Date([Original Date]), "%B")

Here are some others we built using the same method and there are many more possible:

It can be useful to get the current or previous weekday when presenting data to users. For example, in the table below we have one row of data with today's date in the Today column.

We use this column in a Function to determine If the input date is a Monday, we show the day in the Day Name of Today and then the function returns the calculated Current Weekday.

The Function is:

DateFormat(DateAdd("day", (If(Weekday([Today]) = 7, -1, Weekday([Today]) = 1, -2, 0)), [Today]), "%A")

If the input date is a Saturday, the function returns the date of the Friday immediately previous.

A breakdown of this Function's parts is available here.

It is often useful to know the elapsed time between two dates (and times). Some examples are:

Call Center Support: Call duration
Customer Service: Order fulfillment time
Healthcare: Time since last blood test

Let's take a look at the Customer Service use case.

Marketing is interested in targeting customers who purchase frequently but only has a table with all orders to start with.

They want to know a few things:

• When was a customer's first order?
• When was their second order?
• Number of days between the first and second order?
• How long since they last placed an order?
• Marketing will use this in campaigns targeting active and inactive customers.

Create another Workbook Page.

The data we will use is still the PLUGS_ELECTRONICS_HANDS_ON_LAB_DATA table. You can create a child of the table we used earlier of just add a new table to the Page based on it as source. We only need the columns Customer Name and Date.

Group the table by Customer Name.

Truncate the Date column to day:

Group by the Day of Date:

Lets filter the data (to keep things simple to see as we work) for Customer Name = Leah Douglas:

The table should now look like this:

Add a new column by clicking the Customer Name menu arrow and rename it to First Order:

For First Order set the formula to:

Min([Day of Date])

Now we will add four more columns, rename them as shown below and apply the Functions in the formula bar for each:

Column:                         Formula:
Second Order                    Nth([Day of Date], 2)
Last Order                      Max([Day of Date])
Days 1st to 2nd Order           DateDiff("day", [First Order], [Second Order])
Days 1st to Last                DateDiff("day", [First Order], [Last Order])

The table should now look like this (after collapsing it):

Go ahead and turn off the filter:

Now Marketing has the data they are requesting:

Sales Operations wants to know see how weekly sales numbers look compared to the previous week.

Let's use this example to investigate using the Lead and Lag function in Sigma. These functions make this use case surprisingly simple to execute.

In this example, we will go about getting data a different way (extra credit!). Create another Workbook Page and rename it Week Over Week.

Add a table to the Page but this time select the F_Sales from the Sample Database, selecting these columns:

This gives us all the sales transactions. Now we want to join a table to this for the point of sale data.

Click the menu in the F_Sales table and select Element Source and then Join:

Select the table F_Point_of_Sale, selecting only the Sales Amount column.

Now we have to decide what type of join we want and on which columns (Join Keys).

Based on our joining the two tables against Order Number we have 100% match. Change the join to inner join and see the results. Still 100%, so in this case, either join will work.

Preview the data and click Done. We now have a table on our Page we can rename to Week over Week Sales.

Drag the Date column to Groupings and Truncate it to Week:

Hide the Order Number, Date and Sales Amount columns.

Drag the Sales Amount column to Calculations, rename it to Weekly Sales and set the format to currency:

Add two calculated columns (in CALCULATIONS). Rename each and set the functions as:

Column:                         Formula:
Sales Lag 1 Week      [Weekly Sales] / Lag([Weekly Sales], 1)
Sales Lead 1 Week     [Weekly Sales] / Lead([Weekly Sales], 1)

Set the Lead/Lag columns to percentage:

Read more about Lead and Lag funtions.

Viewing data organized Year over year by month gives users insight on how a business is doing in use cases like seasonality. Observing year over year performance gauges if performance is improving, static, or worsening.

We are going to move a little faster now that we learned how to work with the Sigma UI.

Create a new Workbook Page and add the PLUGS_ELECTRONICS_HANDS_ON_LAB_DATA table to it.

Hide all columns to start. Use Shift and Click to select the first and last in the list and then click Hide column.

Add a new group (click the + to the right of GROUPINGS and select Date)

Set the formula for the Day of Date column to:

DateFormat(Date([Date]), "%m")

Rename this column Month Number and set it's sort order to Ascending.

Add a new column:

Set it's formula to

DateTrunc("year", [Date])

Add this new column to a new group (click the + to the right of GROUPINGS and select Year of Date)

Click the - in the Month Number column to collapse the table. We now have 12 months of data:

Add a new column (to the right of Year to Date) and rename it Monthly Sales. Set it's formula to:

Sum([Quantity] * [Price])

The table should now look similar to this (after collapsing/expanding and formatting):

Add a new CALCULATION (click the + to the right of CALCULATIONS in the Year of Date grouping and select New column)

Configure the new column as shown below:

Column:             Formula:
Previous Month      Lead([Monthly Sales], -1)

Add another new CALCULATION (click the + to the right of CALCULATIONS in the Year of Date grouping and select New column)

Column:            Formula:
Year over Year     ([Monthly Sales] - [Previous Month]) / [Previous Month]

Set the Year over Year columns format to Percentage.

Now we can start to see trends in the data.

The InDateRange function provides a succinct way to write calculations such as Year to Date and Last 3 Month. It also simplifies more complex calculations, making them shorter and easier to read.

The InDateRange function will return True or False based on its configuration. The table can then be filtered based on a InDateRange column being true or false.

For example, we may want to see how sales this year compare with last year, side by side.

Create a new Workbook and rename it to InDate Range.

Add the PLUGS_ELECTRONICS_HANDS_ON_LAB_DATA table.

Truncate the Date column to Day.

Add a new column as:

DatePart("week", [Day of Date])

Rename the new column to Week.

Add a new column called Sales Amount.

Set it's formula to

[Price] * [Quantity]

Hide this column.

We will use the InDate Range function in several new columns.

For each of the following new columns you add, configure them using the following:

COLUMN NAME          FORMULA TO APPLY TO COLUMN
                    
Week #               DatePart("week", [Day of Date])
isCurrent Year       InDateRange([Day of Date], "current", "year")
isLast Year          InDateRange([Day of Date], "last", "year")
isCurrent Quarter    InDateRange([Day of Date], "to_date", "quarter")
isCurrent Month      InDateRange([Day of Date], "to_date", "month")
isCurrent Week       InDateRange([Day of Date], "to_date", "week")
isIN Last 2 Weeks    InDateRange([Day of Date], "last", "week", 2)
TY Sales Amount      SumIf([Sales Amount], [isCurrent Year])
LY Sales Amount      SumIf([Sales Amount], [isLast Year])

The table should now look like this:

Next add a child PivotTable.

Configure the Pivot Table as shown:

Now that we have all these columns as part of our data there are many ways you may want to leverage them in Sigma to create interesting Period over Period style visualizations.

In this example we will demonstrate using data from one table in another.

Let's assume that there are two tables that have columns that do not exist in a third. We can use a Lookup to bring those columns over to the third table.

The tables will be are joined by a pair of columns — one from each — that share common values. We call these joining columns join keys.

Columns created from a lookup can be added using the Lookup function. However, you can also add a new lookup column without explicitly writing a formula.

Click here for more information on using Lookups

Create a new Workbook Page and add the PLUGS_ELECTRONICS_HANDS_ON_LAB_DATA table to it.

Rename the Page tab to Lookups - Year over year.

Rename this table Regional Sales Performance - This vs. Last Year.

Duplicate the table using the table menu.

Rename this table Sales This Year

On the second table, hide all the columns leaving only Store Name, Store Region, Store Key, and Date.

Add a new column, rename it Total Sale and set its formula to:

[Price] * [Quantity]

The formula on the Date column to:

DateTrunc("day", [PLUGS_ELECTRONICS_HANDS_ON_LAB_DATA/Date])

Rename the column back to Date

Your page should now look link this:

Let's filter this table to display orders from this year only (click on the Date column's drop arrow and select Filter):

Back on the Regional Sales Performance - This vs. Last Year, we want to group on the Store Region column.

Now add a new column / Column via lookup:

You will be prompted to set how the two tables will be joined. Use this configuration:

Now drag the new Lookup column to the Calculations sectrion of the Store Region grouping:

Now lets get last years sales. Duplicate the table Sales This Year.

Rename the table to Sales Last Year.

Change the filter to use last year as the range.

The page should look like this now (after moving thing around to suit):

Now add another new column via Lookup (into the Regional Sales Performance - This vs. Last Year table) as before using the new Sales Last Year table.

The only configuration difference is the source table as shown:

Drag this new column to Calculations and you are done. We now have last year and this year (by Store Region) with all the detail as well.

The InPriorDateRange function is used for calculations that look at a date range in a prior period, such as This Week Last Year.

The results will appear as Boolean (true or false), and we can use that to filter rows to suit.

To make this go faster, open the Workbook Lookups - Year over Year and use Save As to make a copy as InPrior Date Range.

Please the new Workbook in Edit mode.

Rename the Sales This Year table to Sales In Current Quarter. Do the same for the Sales Last Year table, to Sales Last Year - Same Quarter.

In the Sales In Current Quarter table, we want to filter the data to show only the rows from last quarter. We can do that by simply using the filters control:

In the Sales Last Year - Same Quarter, add a new column called InPriorQuarter and set is formula to:

InPriorDateRange([Date], "quarter", "year")

This will evaluate the Date column and return true or false if the date is in the quarter, one year prior.

Now alter the table's filter, adding a new filter on our new column, InPriorQuarter and only select to see the rows where the value is True. Delete the filter for Date.

Since the Regional Sales Performance - This vs. Last Year table uses Lookups to get the Total Sale column from each of the other two columns already, we don't have to do anything; the sales are summed and grouped already.

We are done:

Sigma provides tools to help you understand warehouse costs, built right into the Sigma platform.

For more information about that, click here. and here.

Companies often use table-based calendars in analytics to help address data consistency, seasonality, and planning.

In this QuickStart Step we will build a pivot table that leverages the NRF Retail 4-5-4 Calendar combined with our Plugs Electronics sample data to look at same store sales the way most retailers prefer. The same general methods apply to using any table-based calendar you may have.

The NRF Retail 4-5-4 Calendar is a standardized retail calendar developed by the National Retail Federation (NRF) to help retailers track and analyze their sales performance. It is widely used by retailers in the United States, and it is particularly useful for businesses that operate on a fiscal year that does not align with the traditional calendar year. The calendar helps retailers plan their inventory, staffing, and marketing strategies based on historical sales data and seasonal trends.

Create a new Workbook and rename it to Same Store Sales.

In this exercise we will use some Sigma functionality not yet covered to enhance your learning by creating a joined table for Plugs sales and the 4-5-4 table to that for analysis.

Add a new Table to the Workbook.

Navigate to the Sigma Sample Database / Retail / Plugs_Electronics / Plugs_Electronics_Hands_On_Lab_Data table:

Rename the table to Plugs Same Store Sales.

We will need to calculate the value of each row (Order Value) since the data only has quantity and price.

Add a new column, rename it to Order Value and use this formula:

[Quantity] * [Price]

Click the Tables menu and select Element Source then Join:

Navigate to the 4_5_4_CALENDAR and select it:

We are now presented with a screen that allows us to adjust how the two tables are joined. We will need to adjust how the 4-5-4 table is joined as we want to join on the Date column. For this to work, we need to ensure the datatype is the same. To do that, click the 4-5-4 table (on the left) and change the Join Keys for both tables to use a custom formula. That formula is:

DateTrunc("day", [DATE])

After making the changes, you should have many matches. It won't be 100% match as there are some values in the Plugs table that are not in the 4-5-4 table. Click Preview Output.

We are presented with the data and a graphical representation of the data flow (lineage):

We can now create a Child from this table and use a Pivot Table:

Now we can create our pivot by dragging column name (in the Element Panel to the respective groupings, not the table) as shown below:

Rename the pivot table to Plugs Same Store Sales - 454 Calendar.

Notice that #4 shows no data for the Fiscal Year= 2019. Filter that out:

Let's say we want to see the Sale Store Sales for Thanksgiving. Since 2022 is the most recent year we had a Thanksgiving, the Fiscal Day of the Year value according to the 4-5-4 Calendar is 299*.

*The NRF Retail Calendars are located here.

Now we can see the year-over-year side by side with just a few clicks to expand as show:

Of course we could make this more user-friendly by adding a Page Control to allow filtering that shows major holidays and other improvements but that is outside the scope of this QuickStart.

Link to the NRF Calendar Page

In this QuickStart we covered many of the commonly used date functions and use cases where they are applied. This was not comprehensive and there are many more ways to leverage dates in Sigma.

To get more information on date functions in Sigma, click here.

Additional Resource Links

Be sure to check out all the latest developments at Sigma's First Friday Feature page!

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