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Datasources

Datasources in the Infoveave Studio Module serve as the foundation for data connectivity and integration. They enable you to establish links to various external data sources, such as databases, cloud services, and APIs. With Datasources, you can efficiently manage, import, and manipulate data, setting the stage for effective data analysis, visualization, and reporting.

Table of Contents

1. Overview

Datasources in the Infoveave Studio Module serve as the foundation for data connectivity and integration. They enable you to establish links to various external data sources, such as databases, cloud services, and APIs. With Datasources, you can efficiently manage, import, and manipulate data, setting the stage for effective data analysis, visualization, and reporting.

2. Infoveave Datasource Classification

2.1 File Based Datasources

File-based datasources in Infoveave provide a versatile way to connect and work with various file formats, enhancing your data management capabilities. These datasources cover different file types and structures to suit your needs:

  • Delimited: Suitable for CSV, TSV, PSV, and custom delimited files, allowing flexible data separation and analysis.
  • Excel: Supports both XLS and XLSX formats, enabling direct interaction with Microsoft Excel files.
  • Fixed Length: Efficiently separates data into columns using positional information, helpful for structured data.
  • JSON: Connects to JSON-based APIs and automations, offering seamless integration with JSON data sources.
  • Multi File: Allows you to combine multiple file types within a single datasource, simplifying complex data setups.
  • Plugin Parser: Enables the upload of custom C# plugins for parsing specific file formats, enhancing data interpretation.
2.2 Databases

Databases in Infoveave provide a solid foundation for storing and managing your data efficiently. Here are some of the key database options available:

  • Apache Cassandra: Offering decentralized storage, Cassandra ensures reliable and scalable data management.
  • MariaDB: An open-source version of MySQL, MariaDB is a powerful choice for enterprise-level database needs.
  • Microsoft SQL: Microsoft’s relational database solution supports both on-premises and cloud environments.
  • MongoDB: A NoSQL database, MongoDB is designed for flexible and dynamic data handling.
  • MySQL: Oracle’s relational database management system is widely used for structured data management.
  • Oracle: An enterprise-grade database, Oracle is available for both on-premises and cloud deployments.
  • Percona: A variant of MySQL, Percona offers enhanced features for MySQL-based data management.
  • Postgres: An open-source database, Postgres is versatile and adaptable for both on-premises and cloud usage.
2.3 Cloud Services

Infoveave offers seamless integration with various powerful tools to enhance your data analysis capabilities. Here’s a glimpse of the cloud services available:

  • Amazon Athena: A serverless solution by Amazon for interactive analytics, Athena enables you to query data effortlessly.
  • Amazon Redshift: Managed by Amazon, Redshift provides a scalable and high-performance data warehouse service suitable for large datasets.
  • Data World: With Data World, you can manage and explore your data catalog effectively, catering to the modern data landscape.
  • Druid: Druid is designed for real-time analytics, allowing you to swiftly analyze and visualize data in dynamic ways.
  • Google Analytics: Infoveave seamlessly connects to Google Analytics properties, supporting both V3 and V4 versions, enabling you to gain insights from web analytics data.
2.4 Others

Infoveave offers diverse data integration options beyond the conventional, providing you with flexibility and adaptability. Explore these unique Datasource types:

  • Custom File Parser: Take control of parsing unstructured text files with custom code. This option empowers you to tailor data extraction to match your specific file formats.
  • IoT: Create IoT Datasource that listens to devices, capturing real-time data streams. This dynamic approach enables you to harness insights from the world of connected devices.
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