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			113 lines
		
	
	
		
			7.3 KiB
		
	
	
	
		
			Markdown
		
	
	
	
	
	
|   | --- | |||
|  | title: Day 1 | |||
|  | slug: /getting-started/day-1 | |||
|  | collate: true | |||
|  | --- | |||
|  | 
 | |||
|  | # Getting Started: Day 1
 | |||
|  | 
 | |||
|  | Let’s get started with your Collate service in five steps: | |||
|  | 1. Set up a data connector | |||
|  | 2. Ingest metadata | |||
|  | 3. Invite users | |||
|  | 4. Add roles | |||
|  | 5. Create teams and add users | |||
|  | 
 | |||
|  | ## Requirements
 | |||
|  | 
 | |||
|  | You should receive your initial Collate credentials from Collate support, or from your existing Collate admin.  | |||
|  | For any questions, please contact support@getcollate.io The following steps will provide initial set up information, | |||
|  | with links to more detailed documentation. | |||
|  | 
 | |||
|  | ## Step 1: Set up a Data Connector
 | |||
|  | 
 | |||
|  | Once you’re able to login to your Collate instance, set up a data connector to start bringing metadata into Collate.  | |||
|  | There are [80+ turnkey connectors](/connectors) to various services: data warehouses, data lakes, databases, dashboards, | |||
|  | messaging services, pipelines, ML models, storage services, and other Metadata Services. | |||
|  | Connections to [custom data sources](/connectors/custom-connectors) can also be created via API. | |||
|  | 
 | |||
|  | There's two options on how to set up a data connector: | |||
|  | 1. **Run the connector in Collate SaaS**: In this scenario, you'll get an IP when you add the service. You need to give | |||
|  |   access to this IP in your data sources. | |||
|  | 2. **Run the connector in your infrastructure or laptop**: In this case, Collate won't be accessing the data, but rather | |||
|  |   you'd control where and how the process is executed and Collate will only receive the output of the metadata extraction. | |||
|  |   This is an interesting option for sources lying behind private networks or when external SaaS services are not allowed to | |||
|  |   connect to your data sources. You can read more about how to extract metadata in these cases [here](/getting-started/day-1/hybrid-saas). | |||
|  | 
 | |||
|  | You can easily set up a database service in minutes to run the metadata extraction directly from Collate SaaS: | |||
|  | - Navigate to **Settings > Services > Databases**. | |||
|  | - Click on **Add New Service**. | |||
|  | - Select the database type you want. Enter the information, like name and description, to identify the database. | |||
|  | - Enter the Connection Details. You can view the documentation available in the side panel. | |||
|  | - Test the connection to verify the connection status. | |||
|  | 
 | |||
|  | ## Step 2: Ingest Metadata
 | |||
|  | 
 | |||
|  | Once the connector has been added, set up a [metadata ingestion pipeline](/how-to-guides/admin-guide/how-to-ingest-metadata)  | |||
|  | to bring in the metadata into Collate at a regular schedule. | |||
|  | 
 | |||
|  | - Go to **Settings > Services > Databases** and click on the service you have added. | |||
|  | - Navigate to the Ingestion tab to **Add Metadata Ingestion**. | |||
|  | - Make any necessary configuration changes or filters for the ingestion, with documentation available in the side panel. | |||
|  | - Schedule the pipeline to ingest metadata regularly. | |||
|  | - Once scheduled, you can also set up additional ingestion pipelines to bring in lineage, profiler, or dbt information. | |||
|  | - Once the metadata ingestion has been completed, you can see the available data assets under **Explore** in the main menu. | |||
|  | - You can repeat these steps to ingest metadata from other data sources. | |||
|  | 
 | |||
|  | ## Step 3: Invite Users
 | |||
|  | 
 | |||
|  | Once the metadata is ingested into the platform, you can [invite users](/how-to-guides/admin-guide/teams-and-users/invite-users)  | |||
|  | to collaborate on the data and assign different roles. | |||
|  | 
 | |||
|  | - Navigate to **Settings > Team & User Management > Users**. | |||
|  | - Click on **Add User**, and enter their email and other details to provide access to the platform. | |||
|  | - You can organize users into different Teams, as well as assign them to different Roles. | |||
|  | - Users will inherit the access defined for their assigned Teams and Roles. | |||
|  | - Admin access can also be granted. Admins will have access to all settings and can invite other users. | |||
|  | - New users will receive an email invitation to set up their account. | |||
|  | 
 | |||
|  | ## Step 4: Add Roles and Policies
 | |||
|  | 
 | |||
|  | Add well-defined roles based on the user’s job description, such as Data Scientist or Data Steward.  | |||
|  | Each role can be associated with certain policies, such as the Data Consumer Policy. These policies further comprise  | |||
|  | fine-grained Rules to define access. | |||
|  | 
 | |||
|  | - Navigate to **Settings > Access Control** to define the Rules, Policies, and Roles. | |||
|  | - Refer to [this use case guide](/how-to-guides/admin-guide/roles-policies/use-cases) to understand the configuration for different circumstances. | |||
|  | - Start by creating a Policy. Define the rules for the policy. | |||
|  | - Then, create a Role and apply the related policies. | |||
|  | - Navigate to **Settings > Team & User Management** to assign roles to users or teams. | |||
|  | 
 | |||
|  | For more detailed instructions, refer to the [Advanced Guide for Roles and Policies](/how-to-guides/admin-guide/roles-policies). | |||
|  | 
 | |||
|  | ## Step 5: Create Teams and Assign Users
 | |||
|  | 
 | |||
|  | Now that you have users added and roles defined, grant users access to the data assets they need. The easiest way to  | |||
|  | manage this at scale is to create teams with the appropriate permissions, and to invite users to their assigned teams. | |||
|  | 
 | |||
|  | - Collate supports a hierarchical team structure with [multiple team types](/how-to-guides/admin-guide/teams-and-users/team-structure-openmetadata). | |||
|  | - The root team-type Organization supports other child teams and users within it. | |||
|  | - Business Units, Divisions, Departments, and Groups are the other team types in the hierarchy. | |||
|  | - Note: Only the team-type Organization and Groups can have users. Only the team-type Groups can own data assets. | |||
|  | 
 | |||
|  | Planning the [team hierarchy](/how-to-guides/admin-guide/teams-and-users/team-structure-openmetadata) can help save time  | |||
|  | later, when creating the teams structure in **Settings > Team and User Management > Teams**. Continue to invite additional  | |||
|  | users to onboard them to Collate, with their assigned teams and roles. | |||
|  | 
 | |||
|  | ## Next Steps
 | |||
|  | 
 | |||
|  | You now have data sources loaded into Collate, and team structure set up. Continue to add more data sources to gain a | |||
|  | more complete view of your data estate, and invite users to foster broader collaboration. You can check out  | |||
|  | the [advanced guide to roles and policies](/how-to-guides/admin-guide/roles-policies) to fine-tune role or team access to data. | |||
|  | 
 | |||
|  | From here, you can further your understanding and management of your data with Collate: | |||
|  | 
 | |||
|  | - Trace your data flow with [column-level lineage](/how-to-guides/data-lineage) graphs to understand where your data comes from, how it is used, and how it is managed. | |||
|  | - Build [no-code data quality tests](how-to-guides/data-quality-observability/quality/tab) to ensure its technical and  | |||
|  |   business quality, and set up an [alert](/how-to-guides/data-quality-observability/observability) for any test case failures to be quickly notified of critical data issues. | |||
|  | - Write [Knowledge Center](/how-to-guides/data-collaboration/knowledge-center) articles associated with data assets to document key information for your team, such as technical details, business context, and best practices. | |||
|  | - Review the different [Data Insights Reports](/how-to-guides/data-insights/report) on Data Assets, App Analytics, KPIs, and [Cost Analysis](/how-to-guides/data-insights/cost-analysis) to understand the health, utilization, and costs of your data estate. | |||
|  | - Build no-code workflows with [Metadata Automations](https://www.youtube.com/watch?v=ug08aLUyTyE&ab_channel=OpenMetadata) to add attributes like owners, tiers, domains, descriptions, glossary terms, and more to data assets, as well as propagate them using column-level lineage for more automated data management. | |||
|  | 
 | |||
|  | You can also review additional [How-To Guides](/how-to-guides) on popular topics like data discovery, data quality, and data governance.  |