Integrate with Analytics Tools
๐๏ธ Looker Studio
Looker Studio, a powerful reporting and business intelligence tool under Google, was formerly known as Google Data Studio. At the Google Cloud Next conference in 2022, Google renamed it to Looker Studio. This tool offers a convenient data reporting experience with its rich data visualization options and diverse data connection capabilities. Users can easily create data reports based on preset templates to meet various data analysis needs.
๐๏ธ Microsoft Power BI
Power BI is a business analytics tool provided by Microsoft. By configuring the use of the ODBC connector, Power BI can quickly access data from TDengine. Users can import tag data, raw time-series data, or time-aggregated time series data from TDengine into Power BI to create reports or dashboards, all without the need for any coding.
๐๏ธ Seeq
Seeq is advanced analytics software for the manufacturing and Industrial Internet of Things (IIOT). Seeq supports innovative new features using machine learning in process manufacturing organizations. These features enable organizations to deploy their own or third-party machine learning algorithms to advanced analytics applications used by frontline process engineers and subject matter experts, thus extending the efforts of a single data scientist to many frontline staff.
๐๏ธ Superset
Apache Superset is a modern enterprise level business intelligence (BI) web application primarily used for data exploration and visualization.
๐๏ธ Tableau
Tableau is a well-known business intelligence tool that supports multiple data sources, making it easy to connect, import, and integrate data. And through an intuitive user interface, users can create rich and diverse visual charts, with powerful analysis and filtering functions, providing strong support for data decision-making. Users can import tag data, raw time-series data, or time-series data aggregated over time from TDengine into Tableau via the TDengine ODBC Connector to create reports or dashboards, and no code writing is required throughout the entire process.
๐๏ธ Excel
By configuring the use of the ODBC connector, Excel can quickly access data from TDengine. Users can import tag data, raw time-series data, or time-aggregated time series data from TDengine into Excel to create reports or dashboards, all without the need for any coding.
๐๏ธ Spark
Apache Spark is an open - source big data processing engine. Based on in - memory computing, it can be applied in various scenarios such as batch processing, stream processing, machine learning, and graph computing. It supports the MapReduce computing model and a rich variety of computing operators and functions, boasting powerful distributed processing and computing capabilities for extremely large - scale data.
๐๏ธ SSRS
SQL Server Reporting Services (SSRS), a built-in component of the Microsoft SQL Server database platform, provides powerful support for enterprise-class report creation, viewing, and management. It provides powerful support for enterprise-level report creation, viewing, and management. SSRS is better suited for traditional fixed-format reports than Power BI, another Microsoft tool for flexible reporting.
๐๏ธ Ontop
Ontop is an open-source virtual knowledge graph system developed by the KRDB research group at the Free University of Bozen-Bolzano, Italy. It dynamically transforms relational database content into knowledge graphs without requiring data migration from original sources.
๐๏ธ Pandas
Pandas is the most popular data processing and analysis library in the Python programming language. Since its creation in 2008 by Wes McKinney, it has become an indispensable core tool in the field of data science. Designed specifically to address real-world data analysis tasks, Pandas makes handling structured data in Python exceptionally straightforward. Whether dealing with business reports, scientific research data, or conducting financial analysis, Pandas provides professional solutions. With its intuitive API and extensive functionality, Pandas significantly lowers the technical barrier to data processing, enabling users to focus more on uncovering the value within the data rather than getting bogged down in technical intricacies.