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Getting Started with Data Model


In vuSmartMaps™, we introduce an innovative Data Model feature, designed to revolutionize the way data is handled. This feature allows users to efficiently model data through aggregation and buckets, and then transform it seamlessly.

A key capability is the ability to join two disjoint datasets, providing a cohesive view of diverse data sources. Our Data Model standardizes how Golden Signals, Metrics, and Attributes are consumed, making it an indispensable tool for end-users. This standardized approach is not just limited to data visualization; it extends to enhancing the functionality of alerts, reports, and insights, ensuring a comprehensive and intuitive data-handling experience.

Users can define and configure Data Models to enrich them with domain-specific insights. Also,

  • The Data Model simplifies the data consumption layer by eliminating the need for learning complex database queries. 
  • The Data Model empowers users to refine data by performing manipulations, massages, and facilitating joins with other datasets, thereby generating new correlated and contextualized data. 
  • Additionally, the Data Model provides users with the capability to retrieve data from various data stores, enabling them to merge and transform datasets seamlessly.

Embarking on Data Modelling Workspace

  1. Accessing Data Modelling Workspace: Navigating your Data Modelling Workspace is a breeze. Begin by visiting the vuSmartMaps homepage and selecting “Data Modelling Workspace” under the Explore section. Once you’re there, you’ll find a comprehensive overview of your data models. You can easily manage your models by performing actions such as creating, viewing, editing, and deleting them. For enhanced control, customize permissions for different roles—whether it’s granting viewing rights or permitting modifications. 
  2. Data Store: A data store is a repository for persistently storing and managing collections of data. Accessing and handling the data stores is simple and can be found at the top-left corner of the Data Models listing page. vuSmartMaps supports a variety of backend databases, making it highly adaptable to your needs. You can effortlessly query these Data Stores using a standard Query Editor or tailor your queries to the specific capabilities of each Data Store. Currently, Data Stores officially supports PostgreSQL, MySQL, Elasticsearch, and Hyperscale DB. 
  3. New Data Model Creation: Creating a new Data Model is a breeze with our intuitive platform. The process consists of four straightforward steps: Start by providing the basic information, set up your data query, apply any necessary transformations, and finally, define the properties of your Data Model. 
    • Basic Information: You are required to provide a unique and intuitive name and a brief description of the data model.
    • Prepare Data Query: This involves crafting queries to fetch data from your databases. The process allows you to choose between building queries using a user-friendly Query Builder or directly specifying a Raw query, giving you flexibility in how you model your data.
    • Do Transform: These transformations enable data manipulation to suit your specific needs. While not mandatory for data models with a single query, they become vital, especially join and concatenate transformations, when working with multiple queries.
    • Set Properties:  You can select the metrics and buckets you want to expose through this data model. In the ‘Set Properties’ step, you can choose, and define properties for the metrics and buckets to be accessible to Data Model users.

Support for Dynamic Filters in Dashboards VuNet’s dashboard lets you use dynamic filters for data viewing. The addition of the data model to the dashboard occurs indirectly via Insights. Configure your queries with custom filters to accurately filter the data on the dashboard.

Further Reading


Data Stores in vuSmartMaps are repositories designed for persistent data storage and management. Key features include:

  • Supported Databases: They support various backend databases such as MySQL, Elasticsearch, and Hyperscale DB.
  • Data Handling: You can manage and access these Data Stores through the Data Modeling Workspace, enabling you to store large volumes of data efficiently.
  • Configuration: Set up Data Stores by specifying connection details and configuration settings within the workspace.


Absolutely! You can customize your data models by defining properties, setting up data queries, applying transformations, and more. This allows you to tailor data models to your unique requirements.

  • Check Credentials: Ensure that hostname, username, and password are correctly entered. Incorrect credentials are a common cause of connection failures.
  • Network Configuration: Verify that network settings and firewall rules allow connections to the Data Store.

The Query Builder offers:

  • Intuitive Interface: An easy-to-use interface for creating basic select queries without needing deep SQL knowledge.
  • Cross-Database Compatibility: Supports various databases, allowing you to create queries for MySQL, Hyperscale, and others.
  • Efficiency: Streamlines the query creation process, saving time and reducing the likelihood of errors.

To filter time series data:

  • Timestamp Field: Select the appropriate timestamp field in your query.
  • Time Range: Specify the time range for the data you want to retrieve, ensuring the results are relevant to your analysis period.

Dynamic Filters enable:

  • Real-Time Filtering: Configure filters that adjust based on real-time data, allowing dynamic analysis as criteria change.
  • Enhanced Flexibility: Provides the ability to apply and modify filters without altering the base query.
  • Interactive Dashboards: Use dynamic filters to create more interactive and responsive dashboards.


To run and preview queries:

  • Individual Query Execution: Run each query individually to check for accuracy and correctness.
  • Collective Execution: Execute all queries within a data model collectively to see combined results.
  • Preview Results: Use the preview feature to view query results and make necessary adjustments before finalizing.

If validation errors occur due to unavailable data, you can click on skip validation to proceed to the next step.

Yes, you can perform operations like Copy, Delete, Disable, and use Saved Search to manage queries within your data model.

Yes, you can add new fields using the “Add Field” transformation. You have options like Arithmetic Operations, Custom values, or Expressions to create new fields

Severity rules allow you to:

  • Value Ranges: Define value ranges for metrics that require monitoring or alerting.
  • Thresholding: Choose between no thresholding, dynamic thresholding (auto-baselining using machine learning), or static thresholding with specific numeric values.
  • Notifications: Set up notifications based on the defined thresholds to ensure timely alerts for critical metrics.



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