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Analyses

In Entrusy, an Analysis is the process of examining your uploaded text data to identify underlying topics and trends. Analyses utilize advanced natural language processing techniques to automatically group text data into meaningful categories, allowing you to extract insights without manual effort.

Types of Analyses​

Entrusy offers several types of analyses to cater to different needs:

  • Analyze New Source Data: This analysis processes newly uploaded text data to identify topics and trends. It is the most commonly used analysis type.
  • Smart Merge Topics: This analysis combines similar topics from previous analyses to create a more refined and consolidated view of the data.
  • Scheduled Analyses: You can set up recurring analyses to automatically process new data at specified intervals, ensuring your insights remain up-to-date.

Creating an Analysis​

To create an analysis in Entrusy, navigate to your project dashboard and click on "Start Analysis". Your project must have at least one uploaded data source to initiate an analysis. Select the desired analysis type and configure any necessary settings. Once ready, click "Start Analysis" to begin processing your data.

Credits​

Each analysis consumes a certain number of credits based on the volume of data processed and the complexity of the analysis type. You can monitor your credit usage in your account dashboard.

As a general rule of thumb, each data point processed typically consumes one credit. If each data point contains text exceeding 500 characters, additional credits will be consumed based on the length of the text.

As Entrusy is still in its testing phase, there is no way to add more credits at this time. If you run out of credits, please contact us.

Best Practices​

The main goal of using Entrusy is to extract meaningful insights from your text data. The primary action each analysis performs is grouping text data into topics. To achieve the best results, consider the following best practices:

  • Data Quality: Ensure that your uploaded text data is clean and relevant. Remove any unnecessary noise or irrelevant information that may skew the analysis results.
  • Project Context: When creating a project, provide a brief context or description of the data. This helps the analysis algorithms better understand the nature of the text and improve topic identification.
  • Topic Management: While Entrusy automatically groups text data into topics, we provide many manual controls to help you manage and refine these topics. You can add, merge, save, or delete topics as needed to better suit your analysis goals. Our system prioritizes your manual adjustments in future analyses to enhance topic accuracy.
  • Iterative Analysis: Run multiple analyses with different configurations or data subsets to explore various perspectives and insights. We recommend utilizing the scheduling feature to break down large datasets into smaller, manageable chunks for more effective analysis.
  • Review and Refine: After each analysis, review the generated topics and refine your data or analysis settings as needed to improve the quality of insights.