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Introduction to Table View

In this guide, we will understand the concept of reviewing the trained documents and different ways to interact with the data collected by your applications.

This view presents the data in a structured table format like a spreadsheet. This allows you to easily filter, sort, and analyze large amounts of data. It's like having all your data organized as a neat and searchable table.

Let's see this in action!

Imagine having all your information laid out like a spreadsheet, with clear rows and columns. That's exactly what this structured table view offers! Here's what makes it so helpful:

Easy Organization: Think of it like filing all your data neatly in folders. Each column acts like a label (like "Name", "Date", or "Amount"), and each row holds a specific record. This makes finding what you need a breeze!

Powerful Search: Just like searching the web, you can filter this table and can filter by any column to instantly narrow down the data you see.

Analysis at Your Fingertips: Because everything is organized, you can easily analyze large amounts of data. Imagine comparing sales figures across months or spotting customer trends – all within this table view!

In short, this structured table format is like having a supercharged filing cabinet and search engine for your data. It keeps everything organized, searchable, and ready for you to analyze!

Creating a Table Data View: A Step-by-Step Guide

Let's walk through the process of creating a table Data View, a powerful tool that allows you to tailor data specifically for your AI model training needs.

1. Accessing Data Views:

Head over to the top navigation bar and click on the "Data Views" option.
Within the Data Views section, you'll see a tile labeled "Data Verification/Validation". Clicking on this tile.

2. Finding Your Table Data View:

Users should click on the "Table Data View" tab and see a list view of existing Data Views.
This list view allows you to search for specific Data Views, download the entire list for reference, or change how the list is displayed by clicking on the "View Columns" button.

3. Creating a New Table Data View:

If you need a new Data View, click the "Create Table View" button within the Data Views section.

4. Filling in the Details:

Table View Name: Give your Data View a unique and descriptive name using only letters, numbers, and underscores up to 45 characters (no spaces or special characters).

Also, users can not create a name starting with “auto_”

Table View Description: Here's your chance to explain what this Data View represents. A detailed description will be crucial for training your AI model accurately.
Relative Past Days: This lets you specify how many days' worth of data you want to include from the past.
Record Created Date: Define a specific date range to narrow down the data you want to use.
Include Line Items/Table Data: Check this box to include detailed data entries alongside the overall summary.
Use in Dataflow Rules (Optional): Check this box if you want to incorporate this Data View into your data flow rules.
Default No. of Records: This sets the number of data entries displayed by default (currently set to 1000). You can modify this number to fit your needs.
Application ID: Select the type of application this Data View pertains to, such as Training, Email, Data Flow, or Form.
Table line items: Choose the table line items you want to include from the dropdown menu.
Once you've filled in all the details, click the "Save" button to create your new Table Data View.

That's it! Now you have a custom-built Table Data View ready to use for training your AI model.

From the list view let's understand the concept of Data View editing and deletion:

Viewing and Managing Data Views

Listing View: You can now see a list of all your created data views.

Edit and Delete Options: On the right side of each data view listing, you'll find icons for Edit and Delete.

Edit: Click the Edit icon to modify an existing data view. This will take you to the edit view for that specific data view.

Delete: Click the Delete icon to remove a data view from the list.

Editing Data Views

Here's how to edit the number of days used in your data view:

Access Data View: Navigate to the "Data Validation/Verification" section and select the tab containing the data view you want to edit.

Edit Relative Past Days: Locate the field where you define the number of past days considered in your data view. You can then adjust the value to your desired timeframe.

Save Changes: Click the "Save" button to confirm your edits. The data view will be updated with the new settings.

Deleting Data Views

To permanently remove a data view, simply click the "Delete" icon next to it in the listing view. This action cannot be undone, so please be sure you want to delete the data view before confirming.

Additional Notes:

This explanation focuses on editing the "relative past days" for now, but the edit view might allow for more modifications depending on the specific features of our data view system.

I hope this explanation clarifies the process of editing and deleting data views!

Viewing Extracted Data and Performing Validation

When you create a data view, you'll see a list of them on the data view page. Each data view will have its name displayed. Clicking on a specific data view name will take you to a detailed view of that data set.

This detailed view provides two key functionalities:

Examining Extracted Data: Here, you'll be able to see the actual data that has been extracted from your source. This data will be presented in a clear and organized table format, allowing you to easily browse through individual records and specific data points.

Validating and Verifying Data: Having direct access to the extracted data empowers you to perform important data quality checks. You can visually inspect the data for accuracy, completeness, and consistency. This allows you to ensure that the information retrieved by the data view matches your expectations and can be used for further analysis with confidence.

Understanding Top Navigation Options

In addition to the detailed data view, you'll also find a set of options on the top navigation bar. Each of these options serves a specific purpose in managing your data view:

These options will likely vary depending on the specific data view tool you're using, but they typically provide functionalities like:

Verifying Extracted Data

Upload/Download: Upload your original documents (when data flow is assigned) and download the data in various formats (CSV, Excel, etc.) for comparison.
Train & Predict: Leverage built-in models to train on your data and predict classifications for new information.

Rules:

Function Rules: Cleanse and manipulate data using functions like Find & Replace, Concatenate, Split, and Date conversion.
Calculation Rules: Perform calculations on your data with formulas and aggregations (totals & subtotals).
Cross-reference & Verification: Ensure data accuracy by cross-referencing documents and applying verification methods like mandatory fields, threshold values, and duplicate checks.

Taking Action on Your Data

Verify & Duplicate Management: Manually verify data, filter and manage duplicates with ease.
Review & Annotate: Deep dive into specific data points by reviewing the document and adjusting as needed.
Send & Design: Share data insights with colleagues through quick reports or custom email designs (requires email design setup).
PDF Preview: Generate a PDF preview of your data for clear presentation (requires PDF design setup).
Save & Delete: Make permanent changes to your data or remove unwanted rows.
Undo & Redo: Navigate through changes with undo and redo functionality.
Refresh: Restore the data view to its original state.
Actions: Set data relevance, mark duplicates, and reset column settings for better organization.

Customization and Preferences

Settings:

Train text classification models for more precise data handling.
Set up data flows for automated data processing.

Design custom email templates for data sharing.
Choose preferred date format.
Control the display of total rows and long text for optimal data visualization.

By utilizing these features, you can confidently verify, manage, and leverage your data for informed decision-making.

Potentially exporting the data for further use in other tools or applications.

By understanding the detailed view and the functionalities offered by the top navigation options, you can effectively manage your data views, ensure data quality, and leverage the extracted information for further analysis and insights.

This explanation uses a clear breakdown, an engaging example, and highlights the benefits of reviewing trained documents. It also smoothly transitions to the next section on data interaction.