Datasaur
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  • Welcome to Datasaur
    • Getting started with Datasaur
  • Data Studio Projects
    • Labeling Task Types
      • Span Based
        • OCR Labeling
        • Audio Project
      • Row Based
      • Document Based
      • Bounding Box
      • Conversational
      • Mixed Labeling
      • Project Templates
        • Test Project
    • Creating a Project
      • Data Formats
      • Data Samples
      • Split Files
      • Consensus
      • Dynamic Review Capabilities
    • Pre-Labeled Project
    • Let's Get Labeling!
      • Span Based
        • Span + Line Labeling
      • Row & Document Based
      • Bounding Box Labeling
      • Conversational Labeling
      • Label Sets / Question Sets
        • Dynamic Question Set
      • Multiple Label Sets
    • Reviewing Projects
      • Review Sampling
    • Adding Documents to an Ongoing Project
    • Export Project
  • LLM Projects
    • LLM Labs Introduction
    • Sandbox
      • Direct Access LLMs
      • File Attachment
      • Conversational Prompt
    • Deployment
      • Deployment API
    • Knowledge base
      • External Object Storage
      • File Properties
    • Models
      • Amazon SageMaker JumpStart
      • Amazon Bedrock
      • Open AI
      • Azure OpenAI
      • Vertex AI
      • Custom model
      • Fine-tuning
      • LLM Comparison Table
    • Evaluation
      • Automated Evaluation
        • Multi-application evaluation
        • Custom metrics
      • Ranking (RLHF)
      • Rating
      • Performance Monitoring
    • Dataset
    • Pricing Plan
  • Workspace Management
    • Workspace
    • Role & Permission
    • Analytics
      • Inter-Annotator Agreement (IAA)
        • Cohen's Kappa Calculation
        • Krippendorff's Alpha Calculation
      • Custom Report Builder
      • Project Report
      • Evaluation Metrics
    • Activity
    • File Transformer
      • Import Transformer
      • Export Transformer
      • Upload File Transformer
      • Running File Transformer
    • Label Management
      • Label Set Management
      • Question Set Management
    • Project Management
      • Self-Assignment
        • Self-Unassign
      • Transfer Assignment Ownership
      • Reset Labeling Work
      • Mark Document as Complete
      • Project Status Workflow
        • Read-only Mode
      • Comment Feature
      • Archive Project
    • Automation
      • Action: Create Projects
  • Assisted Labeling
    • ML Assisted Labeling
      • Amazon Comprehend
      • Amazon SageMaker
      • Azure ML
      • CoreNLP NER
      • CoreNLP POS
      • Custom API
      • FewNERD
      • Google Vertex AI
      • Hugging Face
      • LLM Assisted Labeling
        • Prompt Examples
        • Custom Provider
      • LLM Labs (beta)
      • NLTK
      • Sentiment Analysis
      • spaCy
      • SparkNLP NER
      • SparkNLP POS
    • Data Programming
      • Example of Labeling Functions
      • Labeling Function Analysis
      • Inter-Annotator Agreement for Data Programming
    • Predictive Labeling
  • Assisted Review
    • Label Error Detection
  • Building Your Own Model
    • Datasaur Dinamic
      • Datasaur Dinamic with Hugging Face
      • Datasaur Dinamic with Amazon SageMaker Autopilot
  • Advanced
    • Script-Generated Question
    • Shortcuts
    • Extensions
      • Labels
      • Review
      • Document and Row Labeling
      • Bounding Box Labels
      • List of Files
      • Comments
      • Analytics
      • Dictionary
      • Search
      • Labeling Guidelines
      • Metadata
      • Grammar Checker
      • ML Assisted Labeling
      • Data Programming
      • Datasaur Dinamic
      • Predictive Labeling
      • Label Error Detection
      • LLM Sandbox
    • Tokenizers
  • Integrations
    • External Object Storage
      • AWS S3
        • With IRSA
      • Google Cloud Storage
      • Azure Blob Storage
    • SAML
      • Okta
      • Microsoft Entra ID
    • SCIM
      • Okta
      • Microsoft Entra ID
    • Webhook Notifications
      • Webhook Signature
      • Events
      • Custom Headers
    • Robosaur
      • Commands
        • Create Projects
        • Apply Project Tags
        • Export Projects
        • Generate Time Per Task Report
        • Split Document
      • Storage Options
  • API
    • Datasaur APIs
    • Credentials
    • Create Project
      • New mutation (createProject)
      • Python Script Example
    • Adding Documents
    • Labeling
      • Create Label Set
      • Add Label Sets into Existing Project
      • Get List of Label Sets in a Project
      • Add Label Set Item into Project's Label Set
      • Programmatic API Labeling
      • Inserting Span and Arrow Label into Document
    • Export Project
      • Custom Webhook
    • Get Data
      • Get List of Projects
      • Get Document Information
      • Get List of Tags
      • Get Cabinet
      • Export Team Overview
      • Check Job
    • Custom OCR
      • Importable Format
    • Custom ASR
    • Run ML-Assisted Labeling
  • Security and Compliance
    • Security and Compliance
      • 2FA
  • Compatibility & Updates
    • Common Terminology
    • Recommended Machine Specifications
    • Supported Formats
    • Supported Languages
    • Release Notes
      • Version 6
        • 6.111.0
        • 6.110.0
        • 6.109.0
        • 6.108.0
        • 6.107.0
        • 6.106.0
        • 6.105.0
        • 6.104.0
        • 6.103.0
        • 6.102.0
        • 6.101.0
        • 6.100.0
        • 6.99.0
        • 6.98.0
        • 6.97.0
        • 6.96.0
        • 6.95.0
        • 6.94.0
        • 6.93.0
        • 6.92.0
        • 6.91.0
        • 6.90.0
        • 6.89.0
        • 6.88.0
        • 6.87.0
        • 6.86.0
        • 6.85.0
        • 6.84.0
        • 6.83.0
        • 6.82.0
        • 6.81.0
        • 6.80.0
        • 6.79.0
        • 6.78.0
        • 6.77.0
        • 6.76.0
        • 6.75.0
        • 6.74.0
        • 6.73.0
        • 6.72.0
        • 6.71.0
        • 6.70.0
        • 6.69.0
        • 6.68.0
        • 6.67.0
        • 6.66.0
        • 6.65.0
        • 6.64.0
        • 6.63.0
        • 6.62.0
        • 6.61.0
        • 6.60.0
        • 6.59.0
        • 6.58.0
        • 6.57.0
        • 6.56.0
        • 6.55.0
        • 6.54.0
        • 6.53.0
        • 6.52.0
        • 6.51.0
        • 6.50.0
        • 6.49.0
        • 6.48.0
        • 6.47.0
        • 6.46.0
        • 6.45.0
        • 6.44.0
        • 6.43.0
        • 6.42.0
        • 6.41.0
        • 6.40.0
        • 6.39.0
        • 6.38.0
        • 6.37.0
        • 6.36.0
        • 6.35.0
        • 6.34.0
        • 6.33.0
        • 6.32.0
        • 6.31.0
        • 6.30.0
        • 6.29.0
        • 6.28.0
        • 6.27.0
        • 6.26.0
        • 6.25.0
        • 6.24.0
        • 6.23.0
        • 6.22.0
        • 6.21.0
        • 6.20.0
        • 6.19.0
        • 6.18.0
        • 6.17.0
        • 6.16.0
        • 6.15.0
        • 6.14.0
        • 6.13.0
        • 6.12.0
        • 6.11.0
        • 6.10.0
        • 6.9.0
        • 6.8.0
        • 6.7.0
        • 6.6.0
        • 6.5.0
        • 6.4.0
        • 6.3.0
        • 6.2.0
        • 6.1.0
        • 6.0.0
      • Version 5
        • 5.63.0
        • 5.62.0
        • 5.61.0
        • 5.60.0
  • Deployment
    • Self-Hosted
      • AWS Marketplace
        • Data Studio
        • LLM Labs
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On this page
  • Terms and Definitions
  • Group Table
  • Metrics
  • Segments
  • Filter
  • How to Generate a Report
  1. Workspace Management
  2. Analytics

Custom Report Builder

Make your own report by a Group Table, followed by Metrics and Segments

You can make a customized CSV report by selecting which data columns to be included and filter out the unnecessary data.

Exporting report may take time and is highly depends on how much data you generate.

Terms and Definitions

Group Table

Group table is a way to categorize the combination of Metrics and Segments.

Not every Metric can be combined with every Segment. Each metric has a scope, e.g. document-level or label-level. In most cases, it only makes sense to combine attributes that share the same scope.

For example:

  • Time spent (in Time spent table group) is a document-level metric so it can only be used up to document-level granularity segment like document name. It would not be logical to combine with label segment.

  • Labels applied (in Labeling table group) is a label-level metric and it can be combined with label type segment, which cannot be calculated together with effective time spent.

  • Progress table is a dedicated group intended to capture the completion progress for each project type. It uses a document-level granularity segment, providing a scoped result for the report.

That's why Group Table exists, i.e. to make sure the column combinations are valid.

Metrics

Metrics are quantitative measurements of data in relation to a specific segment. To see the detailed of each metric, you can hover it and see the hint that will be shown on the right side of it. On the report, metric columns will be placed last.

Segments

Segments are ways to view and classify the quantitative data. It's basically a list of columns that will used as a base reference when calculating the metrics. Again, you can hover each segment to get a more detailed explanation. On the report, segment columns will be placed first before the metrics.

Filter

It's optional but highly recommended to filter out unnecessary data to make your report more specific and speed up the report generation process. You can only filter the data by Segments. Regardless of what segment you select in the report, you can always filter the report by all segments.

How to Generate a Report

  1. Click the Configure button.\

  2. Select a group table.

  3. Select columns for both metrics and segments.

  4. Filter the date if needed.

  5. Click Save.

  6. A preview of the data will be generated for you. Use this preview to see and make sure you have the correct table structure of your report.

  7. Click on the "Export to Email" option to send the report to your email inbox.\

  8. Alternatively, click on the "Download" button to obtain the report directly to your device.\

Last updated 8 months ago