15 posts tagged with "metad"

We have released a new version 2.2.0 with the following major updates:

1. ER Diagram for Cube Designer​

We have added the ER diagram feature to the cube designer. You can now view the data relationship model of cubes through the ER diagram, including fact tables, dimensions, measures, and relationships. This allows you to intuitively understand the data structure of cubes, facilitating data modeling and analysis.

We have released version 2.1.0, with the following major updates:

1. Upgraded the state management framework, using @ngneat/elf, a reactive immutable state management solution.
   1. Upgraded the state management framework of the semantic model module, making semantic model operations more stable, and supporting State History and Undo/Redo functions. Refer to Shortcuts - Modeling Workspace
   2. Upgraded the state management framework of the story module, supporting State History and Undo/Redo functions. Refer to Shortcuts - Story Preferences
2. Changed olap data request method from Http requests to Websocket requests, improving the efficiency of data concurrent queries. Refer to WebSocket Request - Server Agent
3. The dimension designer data preview interface supports tree structure display. Refer to Tree Preview - Dimension Designer
4. Story designer interface updates:
   1. Support for fixing Toolbar to the sidebar: Refer to Toolbar - Story Workspace
   2. Optimized Zoom in / Zoom out mode, allowing individual page zoom and pan. Refer to Shortcuts - Story Preferences
   3. When opening a story in full-screen mode, it only goes full-screen within the webpage, no longer full-screening the browser.
5. The indicator registration page supports real-time data trend preview of indicators. Refer to Preview - Indicator Registration
6. Dimension/Measure selector component upgrade:
   1. Support for loading entity type status and error message display.
   2. Support for customizing member tag fields as hierarchical attributes or member intrinsic attributes. Refer to Member Label - Dimension Selector
7. In the indicator application, the drill-down chart displays the name of the current level as the title.

We are happy to announce Metad Analytics Cloud 2.0.

We believe Metad Analytics Cloud will help you analysis your big data with minimal effort, letting you focus on what really matters: indicators.

This is a new major version of Metad Analytics Cloud, coming with new exciting features and new experiences.

Hello everyone!

We are excited to announce that the SaaS data analytics platform, Metad Analytics Cloud, from the Metad Analytics Cloud team, is now open source! This is a significant milestone, and we take pride in our ability to collaborate with the global developer community to drive innovation in the field of data analytics.

In this article, we will introduce some basic information about Metad Analytics Cloud and how you can join our community to contribute to the development of the data analytics field.

In today's data-driven business environment, data analysis has become a key part of business decision-making. The Metad Analytics Cloud provides you with an intelligent data query experience, through its powerful AI copilot function based on ChatGPT, you can more efficiently query, optimize and interpret data. This article will introduce in detail how to turn on and configure the AI copilot in the Metad Analytics Cloud, and how to use the AI copilot in the Query Lab to improve the efficiency of data query.

Query Lab provides the function of flexibly operating the data source entity (physical table view or multi-dimensional data set) by using SQL query statement, which helps users in their daily data operation and maintenance work. The query lab is built in the semantic model workspace and operates and queries data through the data sources connected by the semantic model. If the user's data source is public network accessible, you can create a data source in the metad analytics cloud to connect query. If the user's data source is deployed in the private network, you can use the desktop agent to connect and query.

Next, this article will introduce how to turn on and configure AI copilot and use it to assist in querying the data sql in the laboratory, optimizing and explaining.

Welcome back to the AdventureWorks Sales sample series! Today we will continue to explore this Metad powerful BI software, focusing on the theme template function. Through the theme template, you can create, share and apply story dashboard templates more efficiently, thus quickly revealing insights in the data.

The dashboard theme template is usually designed to cover multiple aspects, aiming to provide users with a convenient and efficient way to create consistent and professional data analysis dashboards. Here are some of the common content that dashboard theme templates may include:

1. Color and style settings: Provides predefined color schemes and styles, allowing users to easily select colors and styles that suit their analytic themes.
2. Font and text style: Allows users to select different fonts, sizes, and styles to ensure that the report content is easy to read and consistent with the corporate brand.
3. Chart template: Provides different types of chart templates, such as bar charts, line charts, pie charts, etc. Users can insert these charts directly and adjust the data source as needed.
4. Chart style: Allows users to select different chart styles, such as solid, flat, gradient, etc., to make the data more attractive and readable.
5. Background and border: Provides background image, color or texture options, and can adjust borders and fills to increase the visual appeal of the dashboard.
6. Logos and Watermarks: Allows users to add company logos, watermarks, or copyright information to protect content and enhance professionalism.
7. Data table style: Define the appearance of the data table, including the table header, cell color, border, etc., making the table easier to read and understand.
8. Interactive elements: Predefined interactive elements such as drop-down menus and buttons allow users to customize the interactive experience of the dashboard.
9. Device adaptation: Provides adaptation options on different devices to ensure the visual effect of the dashboard on different screen sizes.
10. Template Library Management: Storyboard template library, users can browse, search and select templates that suit their analytical scenarios.

Welcome back to the AdventureWorks Sales Story series! In this article, we will continue to explore the advanced features of the Story Dashboard, focusing on dynamic parameters and linked analysis between widgets. These features will allow you to dig deeper into the data, discover hidden insights, and take your analysis to a whole new level.

In many cases, we need to focus on the top N products by sales to focus on the most valuable products. With the parameter feature of metad analytics cloud, you can easily implement dynamic Pareto analysis.

You can associate the filter conditions of different widgets through the metad analytics cloud's linked slicers function.

With the arrival of the third quarter of 2023, Metad Analytics Cloud has once again stepped into a brand new version, bringing a series of exciting features and architectural upgrades. In this blog post, we will focus on the latest features of Metad Analytics Cloud 2023 Q3 and the upgrade of the software architecture.

1. Software Architecture Upgrade​

1.1 Angular 16 & Signal State Management​

The Metad analytics cloud has been successfully upgraded to the new Angular 16 version, bringing users a faster and smoother user experience. In terms of UI component state management, we have taken an important step and started to rewrite it step by step in a brand new way Signal. This will not only improve the stability and performance of the system, but also make the development process more efficient.

1.2 UI Design with Tailwind CSS​

In terms of UI design, the Metad analytics cloud 2023 Q3 version ushered in a revolutionary change. We have fully adopted Tailwind CSS to redesign the style of UI components, presenting users with a more modern and beautiful interface, and also improving the ease of operation.

This article will introduce how to deploy Metad Analytics Cloud privately and integrate it with the StarRocks data source to provide powerful multidimensional data indicator analysis capabilities for enterprises and data analysis teams. In this article, we will use tools such as Docker Compose to build and run this private deployment program.

Introduction​

Metad Analytics Cloud is an advanced data analysis platform that helps users get data from a variety of data sources and perform efficient data exploration and visual analysis. StarRocks is a fast, scalable distributed OLAP database that is particularly suitable for multidimensional data analysis. Integrating these two tools together can enhance data analysis capabilities and improve data insights.

An indicator management system is a tool for collecting, analyzing and monitoring business data of enterprises. Enterprises need an indicator management system because it can help enterprises understand their business conditions, evaluate their performance and formulate effective strategic plans.

Through the OLAP engine based on the core, the Metad Analytics Cloud establishes a unified semantic model of enterprise data, without cumbersome data transformation and ETL, and through the unified caliber indicator definition function, the enterprise operating data is uniformly managed and certified. Finally, through the indicator application provided by the Metad Analytics Cloud, the indicator is used to analyze and evaluate the business and financial data of the company.