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 1. Home
    
 2. Product FAQs
    
 3. Input Tables
    
 4. How to use input tables, a practical guide to dynamic calculations and
    scenario modeling
    


HOW TO USE INPUT TABLES, A PRACTICAL GUIDE TO DYNAMIC CALCULATIONS AND SCENARIO
MODELING

Alton Wells

Director of Product Marketing

Input Tables are a powerful new feature in Sigma that enable direct access to
your cloud data warehouse via managed warehouse tables. With Input Tables, you
can directly interface with live production data in a way not previously
possible.

> “If you want to jump straight into building input tables into your analysis
> and already know how to create a new input table jump down to “How to use
> Input Tables in your calculations and scenario models” 


HOW INPUT TABLES WORK

Input Tables in Sigma work by allowing users to manually enter data at the cell
level, alongside their existing warehoused data, to create a more comprehensive
analysis. Users can create empty Input Tables for data entry or generate them
from live source elements. The entered data is stored in Sigma-managed system
tables within the user's Cloud Data Warehouse (CDW). Input Tables can also be
integrated into existing analyses using lookups and joins, supporting use cases
like data entry, data augmentation with external information, and performing
what-if analyses or scenario modeling.

How to create an input table 

1. Check requirements:


Ensure that you meet the following requirements before proceeding:

-You have a Snowflake connection with write access enabled.

-You have the necessary permissions: Admin, Creator, or a custom account type
with permission to create Input Tables.



2. Create an Empty Input Table:

 1. Enter Edit mode in the workbook.
 2. Open the workbook's ADD NEW panel.
 3. Under INPUT TABLES, select EMPTY.

A new Input Table will appear on the page.



3. Create Columns, Add Data, Do Validations

 1. To add a new column, open a column's menu and select a column type from the
    "Add new column" submenu.
 2. Click any cell and type a value. Make sure the cell value matches the
    column's type. You can also copy and paste data into one or more cells at a
    time.
 3. Open the column's menu, select "Data Validation", add your value options,
    and click "Save".


DIFFERENT TYPES OF INPUT TABLES AND THEIR USES

In Sigma, there are two types of Input Tables: empty Input Tables and linked
Input Tables.

Empty Input Tables: These are created as blank tables, allowing users to
manually enter data at the cell level. Users can add columns, input data, and
set data validation rules as required. Empty Input Tables can be integrated into
existing analyses using lookups and joins with warehouse-sourced data.

Linked Input Tables: These are created from existing data in the user's cloud
data warehouse. Users can select a source element and choose the desired columns
to include in the Input Table. While certain columns from the source data cannot
be edited, users can add new editable columns, input data, and set data
validation rules as needed. Linked Input Tables can also be integrated with
existing analyses using lookups and joins.


HOW TO USE AN INPUT TABLE IN YOUR CALCULATIONS & SCENARIO MODELING

For this portion of the how-to-guide, we are going to take a practical approach
and a very simple use-case that can show the power of input tables dynamically
updating calculations in Sigma and creating a simple  scenario model.

In this example, we’ve taken historical transaction data from a hypothetical
retail business and our existing orders from inside our Snowflake instance for
prior years and the current year to date, then used them to create a projection
model. On the left hand side, you’ll see an input table with 13 months,
representing the entire fiscal year of 2023.  You’ll also notice a growth
estimate column that we have manually created at each month based upon our own
best ability to forecast data. Now let’s watch what happens when we develop two
different scenarios in our table.



The growth estimate column was manually added and will be used to input
different scenarios.

‍The rainy day scenario

As a business facing increasing external pressure from changing interest rates
and tightened financial conditions, it’s essential we be able to understand and
project the potential downside for our companies. Let's take a look at what our
forecast looks like if we have net negative growth over the next year.



In the above image, I’m inputting a negative growth estimate for each month,
then looking at the effect on the year as a whole.

While not the best or happiest charts to look at, understanding our potential
downside from real historic data and the future possibilities of our business is
essential to managing risk and ensuring continuity of our organizations.


The growth scenario

Now, let's flip this scenario on its head.

Assume we have signal that our growth is on an upward trend. That means our
current orders (living in Snowflake) as well as our own best estimates of our
business show growth.  We can now input  those projections on a monthly basis to
give us a total revenue growth number relevant to our current numbers and show
where we may need to source more inventory, hire a larger team, etc.



In the above image, I’m inputting a positive growth estimate for each month,
then looking at the effect on the year as a whole.

‍Changing our underlying assumptions‍

With Input Tables, it’s easy to create and model your data against both live
warehouse data and human-generated inputs. In the example below, you can see
that our growth estimates are appended against real live orders in a single
table. You’ll also notice that in the formula bar above this table, we built our
own custom function against our own internal assumptions for how growth should
occur in the upcoming year. It’s as easy as writing a new function or a new
column to change the underlying mathematical assumptions behind your forecasts
and models. No python or SQL required.



Using the growth estimate added in the input table, I can look at next year’s
estimate by month. We built our own custom function against our own internal
assumptions for how growth should occur in the upcoming year

‍Frequently Asked Questions 

Q: What are the main use cases for Input Tables in Sigma?

A: Input Tables can be used for data entry, integrating external data with
warehouse data, what-if analysis, and scenario modeling.

Q: What are the requirements for using Input Tables in Sigma?

A: To use Input Tables, you must have a Snowflake connection with write access
enabled, and you need to be an Admin, Creator, or have a custom account type
with permission to create and edit Input Tables.

Q: Can I import data from external sources into Input Tables?

A: Yes, you can copy and paste data from external sources or other elements in
your workbook into the cells of Input Tables, subject to a 500-cell limit.

Q: How can I ensure data consistency when entering data in Input Tables?

A: You can add data validation rules to restrict the values allowed in a column,
ensuring that the input data is consistent with your requirements.

Q: How do I join Input Tables with existing warehouse data for analysis?

A: You can use lookups or joins to integrate Input Tables with existing data
from your cloud data warehouse, allowing for seamless analysis of the combined
data.

Q: Can I grant other users permission to edit data in Input Tables?

A: Yes, workbook editors can grant permission to explorers to edit Input Table
values by enabling the "Allow data editing in explore mode" setting in the Input
Table's more (•••) menu. This permission will apply to all users with “Can
Explore” access to the workbook.

Q: How can I add calculated columns or perform calculations using data from
Input Tables?

A: Child tables of Input Tables have all of the same capabilities of standard
tables in sigma. You can create calculated columns or perform calculations using
standard Sigma functions and formulas, combining data from the Input Table and
your warehouse data as needed.

Q: How secure is the data stored in Input Tables, and where is it stored?

A: Input Table data is stored in managed system tables within your cloud data
warehouse (CDW), ensuring that the data remains secure and in line with your
organization's data security policies. 




WHERE CAN I LEARN MORE ABOUT SIGMA FEATURES AND USE CASES?

Our online documentation is a great way to get high-level information on product
features along with as much fine detail as you want.

Sigma QuickStarts provide “step-by-step” guides to using Sigma, exploring
specific features and use-cases.




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