In the world of data analytics, managing and manipulating data can be a tedious and time-consuming process. Sigma Computing’s Input Tables aim to solve these pain points by providing a powerful and intuitive way to work with data.
With Sigma’s Input Tables, users can efficiently add data from any source, then use it to create visualizations, reports, and other useful insights.
In this blog post, we’ll explore how Sigma’s Input Tables can help users overcome common data management challenges and examine some of the most common use cases for this powerful tool.
Note: At the time of this writing, Input Tables are in Beta and are subject to change.
What are Input Tables in Sigma Computing?
Input Tables open your analysis to the influence of human intelligence. No longer solely dependent on automated sources, they offer the ability for users to enter data points directly into your analysis.
Input tables are workbook data elements that allow manual data entry to be used for basic data entry, integrating data outside the warehouse into Sigma analysis and what-if analysis.
What are Linked Input Tables?
Linked Input Tables are an extension of Input Tables, where users can derive data from a table element to be combined with manual data entry.
They can be used to create relationships between tables, such as one-to-one or one-to-many relationships. Linked Input Tables allow you to create more complex analyses, such as combining data from different sources or performing more advanced calculations.
With linked Input Tables, you can analyze and manipulate data more efficiently, and the relationships between the tables are automatically maintained.
What is the difference between an Input Table and Linked Input Table?
The primary difference between Input Tables and Linked Input Tables is that Input Tables are standalone tables that do not have any source relationships with other tables. On the other hand, Linked Input Tables can be sourced from other tables in the workbook, and they can have relationships with other tables.
Linked Input Tables are used for more advanced data analyses and allow for more complex calculations and data manipulations.
They are particularly useful when working with data from different sources, where relationships between multiple tables are required.
Overall, Input Tables and Linked Input Tables are powerful tools that enable users to analyze and manipulate data efficiently while maintaining relationships between tables.
How to Create an Input Table in Sigma
Creating an input table in Sigma Computing involves the following steps:
1. Enter Edit mode of a workbook.
2. Navigate to the elements pane on the left-hand side of the Sigma Computing interface.
3. Click the “Input Table” button to create a new table.
4. Select a connection to use to write the Input Table data to the Snowflake Data Cloud.
- Note, you must have written access to this connection
- Learn more about Sigma Account Types here:
5. Define the columns by specifying the name, data type, and other properties.
- You can choose from a range of data types, such as text, date, or number.
6. Once you have defined the columns, you can add data to your table. You can copy and paste data from various sources, or manually enter data into the table.
How to Create a Linked Input Table
Creating a Linked Input Table in Sigma involves the following steps:
1. Enter Edit mode of a workbook.
2. Navigate to the elements pane on the left-hand side of the Sigma Computing interface.
3. Click the “Linked Input Table” button to create a new table.
4. Select what element you’d like as the source or link.
5. Choose which column(s) from the data source to identify unique rows. This can be one or more columns and at a different level of granularity than the data source.
6. Next, choose if additional column(s) should be included in the Input Table.
7. Once you have defined the columns, you can add data to your table. You can import data from various sources or manually enter data directly into the table.
Note with Linked Input Tables, the source columns have a darker gray background.
How to Combine Input Tables with Non-Input Tables
To combine an Input Table with a different data source, you can use a lookup or an in-workbook join depending on the type.
With a non-Linked Input Table, you can use either a lookup or an in-workbook join to combine the two elements. If it is a Linked-Input Table, you must use an in-workbook join because lookups can not be referenced from a target table back into the original source table (this creates a loop in the parent-child relationship).
Learn more about the differences between Lookups and In-Workbook joins with this helpful blog!
What are Some Scenarios to use Input Tables?
Sigma’s Input Tables provide a powerful tool for non-technical business users to enter data, perform calculations, and analyze results in a spreadsheet format. These Input Tables offer a wide range of use cases, including data editing at the cell level, cohort analysis, sessionization, and augmentation with user-created data.
Input Tables can be used to manage inventory levels, customer engagement metrics, website traffic, and user behavior, financial data for forecasting, and much more.
The benefits of Input Tables for organizations are numerous. They allow non-technical users to work within a familiar spreadsheet interface, reducing the need for external data management software or IT support.
Additionally, Input Tables democratize the data analytics workflow, enabling business users to take ownership of their data and make informed decisions based on insights gleaned from their analyses.
Overall, Sigma’s Input Tables provide a powerful tool for business users to easily and effectively manage their data and gain valuable insights into their operations.
20 Ideas for Using Input Tables to Drive Data-Driven Decisions in Your Organization
- Recording survey responses and analyzing feedback for market research.
- Tracking customer engagement metrics to optimize the customer experience.
- Inputting financial data for budgeting and forecasting future revenue streams.
- Keeping track of employee time and attendance for payroll management.
- Managing inventory levels in a retail store for supply chain optimization.
- Collecting and evaluating customer feedback to improve product design.
- Storing and reviewing sales data for business performance analysis.
- Tracking website traffic and user behavior to enhance online marketing efforts.
- Recording medical research data for analysis and future medical advancements.
- Inputting and reviewing supply chain data for logistic optimization.
- Storing and interpreting social media analytics to enhance social media marketing strategies.
- Managing project tasks and timelines to ensure the timely completion of projects.
- Recording and interpreting student data in an education setting to improve learning outcomes.
- Inputting and analyzing scientific research data for research analysis and development.
- Tracking and reviewing customer support tickets to improve customer support services.
- Recording and analyzing product defects in a manufacturing setting to improve product quality.
- Inputting and reviewing HR data such as employee performance and salaries for HR management.
- Tracking and reviewing fundraising efforts for a non-profit organization to optimize donor outreach.
- Storing and interpreting energy usage data for utilities to optimize energy consumption.
- Inputting and interpreting logistics data for transportation companies to optimize delivery routes.
Conclusion
In summary, Input Tables are an incredibly powerful tool for businesses of all sizes and industries to easily manage their data and gain valuable insights into their operations.
Whether you are tracking customer engagement metrics, managing inventory levels, or analyzing scientific research data, Input Tables can help you make sense of your data and drive data-driven decisions.
With the ability to link and combine Input Tables with non-Input Tables, the possibilities are endless!
If you are interested in learning more about how to leverage Input Tables in your organization, reach out to our Sigma consulting services team today.
Don’t forget to check out our other blogs about data modeling in Sigma for more tips and best practices.
What is a data join in Sigma Computing?
How to connect Snowflake to Sigma Computing
An Advanced Data Modeling Use Case: Creating Patient Cohorts in Sigma Computing
