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