Data Loading Techniques in Infoveave

Discover the simplicity of Batch Upload, the convenience of Email Upload, and the structured approach of NGauge Form. Transform data into actionable insights with Infoveave in a dynamic data upload option.

Data Upload Methods

Infoveave supports various data upload methods for file based Datasources, offering flexibility and convenience. Data uploads are generally categorized as batch and real-time uploads:  

• Real-time (IoT) Data Upload

  • Description: Real-time data upload, also known as IoT (Internet of Things) data upload, involves the continuous streaming of data from connected devices or sensors directly into Infoveave Datasources, enabling instantaneous data analysis and insights.
  • Example: Imagine a smart monitoring system(sensors) installed in a production unit. These sensors continuously collect data on energy consumption, temperature levels, and equipment performance. By integrating this system with Infoveave using real-time data upload, the data is instantly transmitted to the Datasource, allowing plant managers to monitor operations in real-time.

• Manual Upload

  • Description: Efficiently upload a batch of data by utilizing the ‘Upload Data’ option within Infoveave Datasources.
  • Example: Imagine having a spreadsheet with customer feedback that you want to upload all at once. The batch upload method allows you to seamlessly add the entire dataset to the relevant Datasource.

• Email Upload

  • Description: Send your data as an attachment via email to a specified email address in the predefined format and Infoveave will automatically integrate this data into the appropriate Datasource.
  • Example: If you receive daily sales reports via email attachments, the email upload method streamlines the process, automatically incorporating the data into the relevant Datasource without manual intervention.

• NGauge Form

  • Description: Use NGauge forms to update file based Datasources as individual rows or as a batch, providing a structured approach to data input.
  • Example: Suppose you have a standardized form for collecting data on sales agent performance. By utilizing NGauge forms, you can systematically update the file based Datasource, ensuring consistency in data entry, facilitating easier analysis.

• Automated Batch Upload

  • Description: Automated batch upload enables seamless data incorporation into Datasources through scheduled or triggered workflows.
  • Example: Consider a scenario where you receive daily sales reports from multiple regional offices. By setting up automated batch upload, these reports can be automatically ingested into the respective Datasources at specified intervals, eliminating manual intervention and ensuring up-to-date data availability for analysis.

Datasource Batch Uploading

Data batch upload and ingestion are fundamental processes in Infoveave that empower you to populate your datasets, facilitating meaningful analyses and insights. Let us delve into the detailed steps and methods for seamless data batch upload and ingestion.

1. Navigate to the Studio module in the Infoveave main menu.
2. Select Datasources from the drop-down options.
3. Locate and identify the specific Datasource to which you intend to upload batch data. In our case, the Datasource name is “Sales Data”.
4. Once you have identified the target Datasource (Sales Data), click on the upload icon associated with that Datasource.

5. You will be redirected to the data upload window specific to the chosen Datasource.
6. Locate the field labeled Batch Data in the upload window.
7. Assign a descriptive and unique name to your dataset upload in this field. This name aids in easily identifying and managing data batches.
8. Click on the option Select Your Data to select the dataset from your local storage.
9. Utilize the file picker dialog box to choose the exact local file containing the batch data.
10. Upon successful upload, the file picker will reflect the name of the uploaded file, confirming the completion of the upload process.
11. Initiate the upload process by clicking on Start Processing. It allows the system to process and integrate the data into the relevant Datasource.

12. You will receive a confirmation notification upon successful data upload. In case of any encountered issues, an error notification will provide insights into potential problems.

13. Navigate to the Previous tab to view a history of previous data uploads.

    • Options to download or delete previous uploads will be available.

14. Click on the Edit Datasource icon to navigate to the Datasource designer.
15. Choose the Preview Data option to inspect the uploaded data within the data table.

16. You can now see the uploaded data in the data table.

• You have successfully uploaded and previewed the data in the designated Datasource.

Best Practices for Efficient Batch Uploading in Infoveave

In Infoveave, adhering to best practices ensures smooth and error-free data loading. Here are key best practices to consider:

• Consistent Column Names

  • Ensure that column names in your data source match the corresponding columns in Infoveave.
  • Consistent naming conventions streamline the mapping process and prevent data loading errors.

• Existence of Column Names

  • Verify that all column names referenced in your data loading configurations exist in the specified data source.
  • Missing or mistyped column names can lead to mapping issues and hinder the loading process.

• Data Type Consistency

  • Confirm that the data types of columns in your data source match the expected data types in Infoveave.
  • Mismatched data types can result in errors during data loading and affect the accuracy of analytics.

Efficient data loading practices in Infoveave offer several advantages. Here are key advantages:

• Accuracy and Reliability

  • Ensures accurate data representation by preventing errors related to mismatched column names and data types.
  • Enhances the reliability of analytics outcomes, as the loaded data aligns seamlessly with the intended configurations.

• Time Savings

  • Streamlines the data loading process by avoiding time-consuming troubleshooting and debugging.
  • Enables quick and efficient data integration, saving time for analysis and decision-making.

• Consistency in Analysis

  • Maintains consistency between the source data and Infoveave configurations, reducing the likelihood of discrepancies.
  • Promotes reliable and uniform analysis, contributing to better-informed decision-making.

• User Confidence

  • Builds confidence among users in the accuracy and integrity of the loaded data.
  • Users can trust that the data loaded into Infoveave reflects the intended structure and content.

• Minimized Errors

  • Mitigates the risk of loading errors and data inconsistencies, leading to a smoother data processing experience.
  • Minimizes the need for manual interventions and corrections, reducing the chance of human errors.

Conclusion

In conclusion, Infoveave provides versatile data upload methods, including Batch Upload for efficient mass data incorporation, Email Upload for seamless attachment integration, and NGauge Form for structured data input. These options empower users to transform data into actionable insights within the dynamic Infoveave platform, offering flexibility and convenience in managing diverse datasets.