Intelligent Data Insight
Intelligent Data Insight
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Intelligent Data InsightQuick StartUser Learning Paths
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Download PDFCopy pageDownload PDFIntelligent Data Insight DataWind is a platform for detail-level, big data-enhanced analytics. It is designed to address the needs of three distinct business stages—exploration, rapid growth, and mature scale—by providing corresponding DataWind products and services based on varying data analysis and data product requirements, enabling one-stop data analysis and collaboration. It offers advantages such as high performance, big data capability, high availability, and real-time processing, allowing for higher data application efficiency, smoother multi-party collaboration, and faster business decision-making.
Users within an enterprise can generally be categorized into three roles: data analysts, data builders, and platform administrators. Each role has different areas of focus and usage objectives during the learning and usage process. This document shares tailored learning paths and abundant learning resources for different types of users, enabling targeted learning according to each role and ensuring systematic mastery of the product's core features and application techniques.
- To request a trial without a purchase, contact sales personnel to apply. After sales personnel enable the experience allowlist, the trial can begin.
- For companies or individuals who have already purchased the SaaS version, contact the administrator to 1. Add users.
- For companies or individuals who have already purchased the self-hosted deployment version, contact the administrator to 1. Add users.
Process | Process name | Process definition | Overview |
|---|---|---|---|
Step 1 | Connect to data sources | Supports two data connection methods: extraction and direct connection, see Connection methods, and supports more than 40 types of data sources, including local file upload, API connection, content management platforms, and more. | |
Step 2 | Data integration | Drag-and-drop, easy-to-use, and intelligent data processing for initial datasets enables data to be cleaned, transformed, and loaded to produce datasets better suited for business analysis. | |
Step 3 | Data querying and exploration | Perform self-service visual analysis on the connected data to gain data insights. | |
Step 4 | Display analysis results |
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4.1 Data analyst learning path
4.1.1 Role definition
Data analysts are typically members of business teams within the enterprise, dedicated data analysts, or members of big data teams. Their main tasks involve querying and analyzing business data, with a daily focus on abnormal fluctuations in key business metrics. Business team members are generally the core of this group.
4.1.2 Goals and vision
To acquire the essential foundational skills as a data analyst, you can gain the following through the current learning path:
- Become proficient in using the Smart Data Insight data analysis and visualization tool, and master techniques for visual queries and dashboard construction.
- Learn how to query and filter data to extract target information quickly and accurately.
- Learn how to subscribe to dashboards, share them, and configure alert rules to ensure timely information delivery and effective risk prevention and control.
- Understand how to present data across multiple platforms or devices, making data viewing and decision-making more flexible and convenient, and enjoy an intelligent collaborative experience.
4.1.3 Learning path
Learning phase | Chapter | Learning task | Task introduction |
|---|---|---|---|
Getting started phase | Chapter 1 Quick overview | ||
1 | Learn about the product, its advantages, and workflow | ||
2 | Learn about the product application scenarios | ||
3 | Learn the core knowledge from importing data and performing visual queries to building dashboards to gain an overall understanding of the product | ||
Chapter 2 Official use | |||
1 | Try connecting a data source | ||
2 | Try creating a dataset using the connected data source | ||
3 | Try using visual modeling on two initial datasets to merge two tables and output as one dataset | ||
4 | Perform self-service visual analysis on the connected data | ||
5 | Present comprehensive data reports based on multiple data charts | ||
6 | Share the dashboard with others | ||
7 | Data Subscription | Subscribe to dashboards to receive scheduled system push notifications and keep up with the latest data status | |
8 | Monitoring and Alerting | Learn how to configure monitoring rules, set monitoring frequency, and configure real-time monitoring metrics | |
Chapter 3 Case demonstration | |||
1 | Independently complete a dashboard through a "Sales representative GMV analysis case" | ||
Chapter 4 Frequently asked questions | |||
1 | Understand relevant product terminology | ||
2 | FAQs | ||
Advanced stage | Chapter 5 Advanced topics | ||
1 | Data preparation advanced - visual modeling | Learn to use visual modeling for data cleaning and other data processing operations | |
2 | Visualization query advanced - table topics | Learn to create Trend Analysis Table, Pivot Table, OKR Table, and Raw-Data Table. | |
3 | Visualization query advanced - chart topics | Learn to create Measure Trend Chart, Funnel Map, Radar Chart, Sankey Diagram, Progress Chart and Progress Bar, Waterfall Chart, Sparkline, and Pivot Chart. | |
4 | Dashboard construction advanced | Learn Drill Up and Drill Down, Chart Linkage, Chart Redirect, and Intelligent Attribution. | |
5 | Function calculation | Learn how to use Introduction to Commonly Used Functions and LOD Expression. | |
6 | Digital large screen(advanced elective) | Learn to build a digital large screen from a template or a blank canvas | |
7 | Overview of Attribution Decision (advanced elective) | Learn to use the automated data attribution and intelligent reporting provided by attribution decision | |
4.2 Data builder learning path
4.2.1 Role definition
Data builders are typically members of an enterprise's big data team or professional data analysts and data engineers, mainly responsible for data ingestion, data preparation, data processing task scheduling, and data warehouse construction and development. These roles are generally filled by dedicated IT or data teams.
4.2.2 Target vision
To acquire the essential foundational skills as a data builder, you can gain the following through the current learning path:
- Become familiar with this product's data ingestion methods and understand the integration processes for different data sources.
- Learn the functional modules for data preparation, including dataset processing, data cleansing, and multi-table association.
- Master the operations for creating and managing tasks in visual modeling to ensure stable operation of data processing tasks.
- Master the operations of the advanced modules of this product, including attribution analysis.
4.2.3 Learning path
Section | Learning tasks | Task introduction |
|---|---|---|
Chapter 1 Quick overview | ||
1 | Understand the product introduction, product advantages, and product workflow | |
2 | Understand product application scenarios | |
3 | Understand relevant terminology concepts | |
4 | Understand the core knowledge from data import, visualization query, to dashboard, and gain an overall view of the product | |
5 | Master some commonly used advanced features | |
Chapter 2 Getting started | ||
1 | Try integrating a data source | |
2 | Create datasets from the data source tables that need to be analyzed | |
3 | Create a new visual modeling task | |
4 | 4.2 Rapid integration of multiple tables for easy multi-source data association and computation | Use the merge rows operator in visual modeling to perform a two-table association |
5 | After associating the two tables, output a dataset for frontline business consumption | |
6 | Visual modeling permissions support delegated assignment within the organization | |
7 | Visual Query Overview - Simple chart creation | Learn to flexibly use charts to visually present data |
8 | Visual Query Overview - Complex table creation | Learn to create Trend Analysis Table, Pivot Table, OKR Table, and Raw-Data Table. |
9 | Function calculation | Learn how to use Introduction to Commonly Used Functions, LOD Expression and Common Functions Usage. |
10 | Present high-quality data reports using multiple data charts | |
11 | Dashboard building | Learn Drill Up and Drill Down, Chart Linkage, Chart Redirect, and Intelligent Attribution. |
12 | Share dashboards with others | |
13 | Data Subscription | Subscribe to dashboards to regularly receive updates pushed by the system and keep up with the latest data |
14 | Monitoring and Alerting | Learn to configure monitoring rules and set monitoring frequency |
Chapter 3 Advanced learning | ||
1 | Learn to quickly obtain data results using SQL statements | |
2 | Subject datasets | Learn to Apply CDP Thematic Datasets, Apply DataFinder Themed Datasets, and Apply Dataset Association and Analysis. |
3 | Digital dashboard | Learn to build a digital dashboard from a template or blank canvas |
4 | Overview of Attribution Decision(optional) | Learn to use the automated data attribution and intelligent reporting provided by attribution decision |
5 | Overview of Custom Visualization(optional) | Learn to create custom data visualizations |
Chapter 4 Frequently asked questions | ||
1 | Understand relevant product terminology | |
2 | FAQs | |
4.3 Platform administrator learning path
4.3.1 Role definition
Platform administrators are typically members of an enterprise's big data team or IT team, mainly responsible for the daily operation and maintenance of this product, user management, permission allocation, system integration, platform promotion, product Q&A, and so on, generally consisting of technical personnel.
4.3.2 Target vision
As a data builder, the following are the essential foundational skills you can acquire through the current learning path:
- Become familiar with the platform's daily monitoring and maintenance, promptly identify and resolve potential issues, and ensure stable platform operation and data security.
- Learn methods for user management and permission assignment to ensure proper data access control.
- Master techniques for system integration and interoperability to easily achieve collaboration with other systems.
- Master methods for system adoption and operation, enabling more personnel within the enterprise to use the product effectively and maximize data value.
4.3.3 Learning path
Section | Learning tasks | Task overview |
|---|---|---|
Chapter 1: Quick start | ||
1 | Learn about the product introduction, product advantages, and product workflow | |
2 | Learn about the product application scenarios | |
3 | Learn about common administrator operations, such as adding users, adding project administrators, adding project global viewers, adding resource administrators, adding regular users, and enabling data row and column permissions | |
Chapter 2: Project management | ||
1 | Create and manage projects | Learn about basic Project Information and perform project-level settings |
2 | Create and manage users | Learn about User Management, User Group Management, Role Management, and User Properties. |
3 | Learn how to view and manage monitoring tasks configured in the current project | |
4 | Learn how to view your own and project members' subscription records, and modify dashboard subscriptions with management permissions | |
5 | Learn how to rename and delete charts with management permissions | |
6 | Learn how to trace and understand the origin, flow, and evolution of data throughout the system or process | |
7 | Learn how to monitor the usage of existing datasets, dashboards, and charts to evaluate the utilization of current resources | |
8 | Learn how to view user operations on the platform to facilitate tracing user actions and related issues | |
9 | Learn about resource deletion, restoration, remaining time, and other functions in the recycle bin | |
10 | Learn how to configure multilingual settings to meet multilingual office requirements | |
Chapter 3: System management | ||
1 | Learn how to create and manage users in the system | |
2 | Learn how to configure watermarks, system controls, copy and download, and network zone access control | |
3 | Learn how to enable or disable product features based on specific business requirements | |
4 | Learn how to efficiently manage and maintain various tasks | |
5 | Overview of Custom Visualization (optional) | Learn how to create personalized data visualization plugins |
6 | Learn about office system integration, embedded analytics, and API List | |
Chapter 4: Permissions | ||
1 | Understand the permissions system | Learn about Permission Overview and Detailed Explanation of Permission Features |
2 | Resource permissions | Learn about Permission Management and Resource Authorization to grant resources to users or user groups |
3 | User permissions | Learn about Authorization and Sharing to easily complete sharing operations and permissions management |
4 | Permissions integration with IM | |
Chapter 5: Frequently asked questions | ||
1 | Understand the relevant terminology of the Intelligent Data Insight product | |
2 | FAQs | |
5.1 Getting started guide
Manual name | Applicable roles | Manual introduction |
|---|---|---|
Data builders, data analysts | From data import and visualization queries to dashboards, this guide helps you build dashboards from scratch | |
Beginner's guide to digital large screens | Data builders, data analysts | Build a data command center with zero barriers and easily integrate heterogeneous data sources |
Data builders, data analysts | Introduces the core process of visual modeling to help you quickly understand data processing and modeling features | |
Platform administrators | Introduces common issues for administrators to help platform administrators get started quickly | |
Data builders, data analysts | Covers visualization queries, dashboards, datasets, SQL queries, attribution analysis, and more |
