Quick Start
Follow this guide to experience uploading data and visualizing it on a dashboard in just 5 minutes. Get a quick hands-on taste of D.Hub's core features.
Before You Begin
Make sure the following items are ready:
- A D.Hub account (username and password issued by your administrator)
- A CSV file to upload (you can also create simple sample data if you don't have one)
Step 1. Log In
Access the D.Hub portal URL, enter your username and password, and click the Login button. Upon successful login, you will be taken to the home screen.
If SSO is configured in your environment, you can log in with your organization account via the Login with SSO button.
If you're having trouble logging in, refer to the Login Guide.
Step 2. Create a Collection
A collection is a group that bundles datasets, codes, pipelines, and more. Start by creating a collection as your workspace.
- Click Create Collection in the Get Started area on the home screen.
- Enter a collection name (e.g.,
My First Project). - Optionally add a description, then click the Create button.
You'll be automatically taken to the created collection's detail page. Let's add a dataset to this collection.
Collections can be freely organized by any criteria you choose — projects, departments, analysis topics, etc.
Step 3. Dataset Quick Upload
Quick Upload lets you instantly create a dataset simply by dragging and dropping a file.
- Click Collections in the sidebar and select the collection you just created.
- On the collection detail page, click the Quick Upload button.
- When the upload dialog opens, drag and drop a CSV file or click to select a file.
- Review the file list and click the Upload button.
D.Hub automatically detects the file format and creates a dataset. Once the upload is complete, success/failure results are displayed.
Quick Upload supports uploading multiple files at once. CSV, JSON, and Parquet files are automatically classified as table datasets, while other files are classified as objects.
In Add Item → Dataset → New Dataset, you can set detailed options such as dataset name, schema customization, and more. For details, see Dataset Management.
Step 4. Create a Dashboard
Let's create a dashboard to visually explore the data you uploaded.
- Click Dashboard in the sidebar.
- On the dashboard list page, click the Create Dashboard button.
- Enter a dashboard name (e.g.,
Sales Overview). - In the editor, click the Add Widget button to open the widget library.
- Select a chart type (e.g., bar chart, line chart, table).
After adding a widget, connect data to it:
- Click the Data tab in the widget settings.
- Select Simple Mode to choose a dataset and columns from the dropdown.
- Or select Query Mode to customize data with SQL queries.
- Set the columns to map to the X-axis and Y-axis, then click Apply.
You can freely arrange multiple widgets on a dashboard. Try adjusting their size and position by dragging.
Step 5. (Optional) Create Knowledge
Try out the feature for collecting unstructured documents and querying them with AI Chat.
- Navigate to Collections in the sidebar and select a collection.
- Under Add Item, select the Knowledge tab and click New Knowledge.
- Enter a Knowledge name (e.g.,
Product Manual). - On the created Knowledge detail page, choose a document collection method:
- Web Crawling — Enter a URL to automatically collect web pages
- File Upload — Upload document files such as PDF, DOCX
- Manual — Write documents directly in the editor
- Once documents are collected, chunking and embedding are processed automatically.
- In the AI Chat tab, try asking questions about the collected documents in natural language.
Knowledge's AI Chat uses RAG (Retrieval-Augmented Generation) technology to generate accurate answers based on the content of collected documents.
Done!
Congratulations! You've experienced all of D.Hub's core workflows.
Here's what you've accomplished:
- ✅ Logged in to D.Hub
- ✅ Grouped resources with a collection
- ✅ Instantly created a dataset with Quick Upload
- ✅ Visualized data on a dashboard
- ✅ Collected documents with Knowledge and tried AI Chat
Next Steps
Explore more advanced features.
- Core Concepts — Understand the relationships between D.Hub components
- Role-Based Guide — Choose a learning path that matches your role
- Pipeline Workflow Editor — Start automating data processing
- Ontology Overview — Model semantic relationships between data