Guide to Data Filters in SignageTube Live’s PowerPoint Plugin

The SignageTube Live PowerPoint plugin is a powerful tool for bringing live data directly into your presentations and digital signage screens. It connects your slides to data tables, allowing you to display real-time metrics, production numbers, or sales figures automatically. One of its most flexible features is the ability to apply a custom filter to your data, letting you show exactly the information you want.

However, the term “custom filter” can sound intimidating. It often brings to mind complex code and technical jargon. While the filter syntax is based on programming logic, you don’t need to be a developer to use it. This guide is here to demystify the process. We will walk you through the basics of building filter expressions, step-by-step, with simple examples based on standard data filtering syntax. You’ll soon be able to slice and dice your data like a pro, ensuring your screens display the most relevant information for your audience.

What is a Data Filter and Why Use It?

Imagine you have a large spreadsheet (a data table) with sales information for all your company’s regions. This table includes columns like Region, Product, Salesperson, and TotalSales.

If you link this entire table to your digital signage, you’ll show everything at once, which can be overwhelming and confusing. What if you only want to display sales for the “North” region? Or maybe you want to show sales over $10,000?

That’s where a data filter comes in. It’s a simple rule you write that tells SignageTube which rows to show from your data table. It acts like a gatekeeper, only letting through the data that matches your specific criteria. Using filters allows you to create targeted, dynamic displays from a single data source without having to create multiple, separate spreadsheets.

The Building Blocks of a Filter Expression

A filter is written as an expression, which is just a statement that evaluates to either true or false for each row in your data table. If the statement is true, the row is displayed. If it’s false, the row is hidden.

These expressions are built using three main components:

1. Column Name: The name of the column you want to filter. If the name contains spaces, you must enclose it in square brackets [].
2. Operator: The type of comparison you want to make (e.g., =, >, <).
3. Value: The specific text or number you are looking for.

The basic structure looks like this: ColumnName Operator Value

Let’s explore this with some practical examples.

Filtering Text: Using the = Operator

The most common filter you’ll use is checking if a column contains a specific piece of text. For text values, the value must be wrapped in single quotes (').

Syntax: ColumnName = 'TextValue'

Example Scenario: You have a data table of employees and their departments. You want to display only the employees from the “Sales” department.

Your data might look like this:

Name	Department	Office Location
John Smith	Sales	New York
Jane Doe	Marketing	London
Peter Jones	Sales	New York
Susan Lee	Finance	London

Filter Expression: Department = 'Sales'

Result: This filter will show only the rows for John Smith and Peter Jones, because their Department is ‘Sales’.

If your column name had a space, like “Office Location”, the syntax would be:
[Office Location] = 'New York'

Filtering Numbers: Using Comparison Operators

When working with numbers, you have more options. You can check for exact matches, or see if a number is greater or less than a certain value. Note that numbers are not wrapped in quotes.

The common operators for numbers are:

• =: Equals
• >: Greater Than
• <: Less Than
• >=: Greater Than or Equal To
• <=: Less Than or Equal To
• <>: Not Equal To

Syntax: ColumnName Operator NumberValue

Example Scenario: You have a production dashboard and want to highlight assembly lines that have produced more than 500 units today.

Your data might look like this:

LineID	UnitsProduced	Status
Line 1	520	Active
Line 2	480	Active
Line 3	610	Active
Line 4	300	Idle

Filter Expression: UnitsProduced > 500

Result: This filter will display Line 1 and Line 3, as their UnitsProduced are greater than 500.

If you wanted to include lines that produced exactly 500 units, you would use >=:
UnitsProduced >= 500

To show all lines except those with 300 units, you would use <>:
UnitsProduced <> 300

Combining Filters for More Powerful Queries

What if you need to be more specific? For instance, you might want to see sales from the “North” region that are also over $10,000. You can combine multiple conditions using logical operators like AND and OR.

The AND Operator

Use AND when you need all conditions to be true for a row to be displayed.

Syntax: Condition1 AND Condition2

Example Scenario: You want to show all sales records from the “North” region where the sale amount was greater than $10,000.

Your data might look like this:

Region	Salesperson	Amount
North	Alice	12000
North	Bob	8000
South	Carol	15000
West	Alice	9500

Filter Expression: Region = 'North' AND Amount > 10000

Result: This filter will only show the first row for Alice. Bob’s sale is in the ‘North’ region but is not over 10000, and Carol’s sale is over 10000 but not in the ‘North’ region. Both conditions must be met.

The OR Operator

Use OR when you need at least one of the conditions to be true.

Syntax: Condition1 OR Condition2

Example Scenario: You want to display a list of all employees who work in either the “New York” or “London” office. Let’s assume the column is named “Office Location”.

Your data might look like this:

Name	Department	Office Location
John Smith	Sales	New York
Jane Doe	Marketing	London
Peter Jones	Sales	Chicago
Susan Lee	Finance	London

Filter Expression: [Office Location] = 'New York' OR [Office Location] = 'London'

Result: This will show the rows for John Smith, Jane Doe, and Susan Lee, as they are in one of the two specified offices. Peter Jones’s row will be hidden.

Advanced Filtering Techniques

Once you master the basics, you can start using more advanced operators and groupings to handle almost any scenario.

The LIKE Operator: Pattern Matching

Sometimes you don’t know the exact text, or you want to find anything that starts with, ends with, or contains a certain phrase. The LIKE operator, combined with a wildcard character (* or %), is perfect for this.

Example Scenario: You want to find all salespeople whose names start with ‘J’.

Filter Expression: Salesperson LIKE 'J*'

This would match ‘John’, ‘Jane’, ‘Jones’, and so on.

You can also place the wildcard at the beginning (*son to find ‘Johnson’, ‘Peterson’) or on both sides (*art* to find ‘Carter’, ‘Stewart’, ‘Marketing’).

Grouping Conditions with Parentheses

When you combine AND and OR in the same filter, things can get ambiguous. To ensure your filter works as expected, use parentheses () to group your conditions. The expressions inside the parentheses are evaluated first.

Example Scenario: You want to show all sales from the “North” region that were made by either “Alice” or “Bob”.

• Incorrect Filter: Region = 'North' AND Salesperson = 'Alice' OR Salesperson = 'Bob'
  This is ambiguous. It could be interpreted as (Region is North AND Salesperson is Alice) OR (Salesperson is Bob). This would incorrectly include Bob’s sales from any region.
• Correct Filter: Region = 'North' AND (Salesperson = 'Alice' OR Salesperson = 'Bob')
  This filter is clear. It first finds all sales made by Alice or Bob, and then from that group, it only keeps the ones where the region is ‘North’.

Putting It All Together

The custom filter option in the SignageTube Live PowerPoint plugin is a gateway to creating highly specific and relevant content for your digital screens. By understanding a few basic rules (column names, operators, and values) you can move beyond showing raw data and start telling a story with it.

Start with simple filters and gradually add more complexity as you get comfortable. Remember to check your column names for typos, wrap text values in single quotes, and use square brackets for column names with spaces. With a little practice, writing filter expressions will become second nature, giving you complete control over the information you display.