--- title: "Data Sources Overview" slug: "overview-sources" description: "Learn how to manage your data source in Dataddo. Learn how to troubleshoot errors and issues, configure database as a source, manually load data and more." tags: ["Reference", "Data source"] updated: 2026-04-15T11:36:39Z published: 2026-04-15T11:36:39Z canonical: "docs.dataddo.com/overview-sources" --- > ## Documentation Index > Fetch the complete documentation index at: https://docs.dataddo.com/llms.txt > Use this file to discover all available pages before exploring further. # Data Sources Overview A ***data source*** represents an authorized connection to any third-party service from where data is extracted. Through a **data flow**, you send data from your ***data source*** to a ***data destination*** on a regular basis, based on the schedule you configured during the ***data source*** setup. You can create a ***data source*** by connecting to a variety of services including: - SaaS apps (e.g. [Salesforce](/docs/salesforce), [NetSuite](/docs/netsuite), [HubSpot](/docs/hubspot), [Stripe](/docs/stripe), [Klaviyo](/docs/klaviyo), [Facebook Ads](/docs/facebook-ads), [Google Analytics 4](/docs/google-analytics-4)) - Databases (e.g. [MySQL](/docs/mysql), Postgres, [SQL Server](/docs/universal-sql-server-source)) - Cloud data warehouses (e.g. BigQuery, Amazon Redshift, Snowflake) - File storages (e.g. [Amazon S3](/docs/s3-as-a-source), SFTP) **DATADDO TIP** For the full list of available ***sources*** and ***destinations***, see the [full list of available connectors](/docs/available-connectors). ## Creating a Data Source Starting a ***data source*** begins with choosing a connector that shapes the initial setup. Dataddo provides three kinds of connectors, catering to various requirements: - **Universal connectors**: These allow highly customizable, low-level interactions with various systems. Examples include [JSON](/docs/json-universal-connector), [XML](/docs/xml-universal-connector), [CSV](/docs/csv-universal-connector), and database options like [MySQL](/docs/mysql) and Postgres. - **Fixed-schema connectors**: These offer pre-defined schemas (datasets) making them easy to set up but they are also are less flexible. Examples include [Mailchimp](/docs/mailchimp), [ExactOnline](/docs/exact-online), and [Google Search Console](/docs/google-search-console). - **Custom-schema connectors**: These allow dynamic schema definitions tailored to services with custom attributes. Examples include [Hubspot](/docs/hubspot), [Google Analytics 4](/docs/google-analytics-4), [Salesforce](/docs/salesforce), and [Facebook Ads](/docs/facebook-ads). For more details, check out [our article on types of connectors](/docs/connectors). Ready to get started? [Create your first data source now](/docs/creating-a-data-source)! ## Source Detail On the [**Sources**](https://app.dataddo.com/sources) page, click on your ***data source*** to see your **Source Details**. On the **Basic Info** tab: - Change your ***data source*** name and add a description for internal purposes - Find your source ID for [error reporting purposes](/docs/error-reporting) - Enable the **Allow Empty** option if you are expecting days without data (for more information, see [No Data Retrieved Error Message](/docs/extraction-logs#no-data-retrieved)) ![Allow Empty](https://cdn.document360.io/084ed225-3f99-4644-a2da-39ca0cd5ef45/Images/Documentation/Source%20Action%20-%20Allow%20Empty.png) - Lock the ***source*** to prevent it from modifications ![Lock Source](https://cdn.document360.io/084ed225-3f99-4644-a2da-39ca0cd5ef45/Images/Documentation/Source%20Action%20-%20Lock%20Source.png) On the **Schema** tab: - [Edit your source schema](/docs/schema) by changing data types or data labels (= column names) On the **Snapshotting** tab: - [Configure extraction or snapshotting details](/docs/extraction) On the **Advanced Settings** tab: - Edit ***data source*** URL for e.g. [setting date range](/docs/setting-date-range) or [data backfilling](/docs/data-backfilling-to-storages) ## Other Data Source Operations ### Duplicate/Clone a Data Source **Duplicating or cloning** a ***data source*** is useful, for example when - You need to change your ***data source* schema** but want to ensure data consistency and avoid unintended disruptions in downstream systems, like your data warehouse. - You need **versioning** for your ***data source***. By cloning the existing source, you can make modifications to its parameters without affecting the original setup. This allows you to maintain various versions of a source configuration to meet different needs. Simply click on the **Clone Settings** button next to your ***source*** and proceed with the on-screen prompts. ### Delete a Source To delete a ***data source*** and its associated flows: 1. Go to the [**Sources**](https://app.dataddo.com/sources) page. 2. Click the bin icon for the relevant ***data source***. 3. In the confirmation window, view the connected flows that will also be removed. 4. Type **DELETE** to confirm your decision. ## Broken Source Operations ### Restart a Source If a ***data source*** enters a [**broken**](/docs/overview-sources#source-status) state, you can attempt to restart it. If successful, the ***source*** becomes live again, allowing manual data loading. If restarting fails, [troubleshooting options](/docs/troubleshooting) will be available. For more information, please see [how to fix a broken source](/docs/troubleshooting#how-to-fix-a-broken-source). ### Extraction Logs To ensure a transparent view of the entire extraction process, each ***data source*** maintains logs of all extraction attempts. To access these logs: 1. Click on the three-dots icon next to the relevant ***data source*** and choose **Show Logs** (available for live ***sources*** as well). 2. Alternatively, click on the **Show Logs** icon directly. For help with resolving issues, refer to the [troubleshooting guide](/docs/extraction-logs). ## Source Status A ***data source*** will have one of the following statuses. | Source Status (Color) | Meaning | | --- | --- | | **Live** (Green) | Indicates normal operation; data is being successfully extracted. | | **Reconnecting** (Orange) | Shown after a failed extraction attempt; the system will try to reconnect and extract data up to three times before changing to **Broken**. | | **Broken** (Red) | Signifies that all attempts to extract data have failed. Restarting is necessary to resume operations. Please see [how to fix a broken source](/docs/troubleshooting#how-to-fix-a-broken-source). | | **Inactive** (Gray) | The source is not in use. Manually restart to return it to **Live** status. | ![Data source status.](https://cdn.document360.io/084ed225-3f99-4644-a2da-39ca0cd5ef45/Images/Documentation/Sources%20-%20In-App%20Status.png) ## Related Articles ### Troubleshooting [Error Reporting Best Practice](/docs/error-reporting) [Troubleshooting](/docs/troubleshooting) [Extraction Logs](/docs/extraction-logs) ### Other Resources [Data Duplication](/docs/data-duplication) [Data Sampling](/docs/data-sampling) Data flows allow you to orchestrate the integration of your data from various sources to your desired destinations. You may add multiple data sources with the same schema to one flow to merge data for a consolidated output. A destination is the endpoint where the data from your sources will be loaded. Destinations include dashboarding tools, data warehouses, and other online services. Connectors allow Dataddo to extract data from your services. When you configure a connector, you define what data you want to extract and as such you create a data source in Dataddo. A data type, specified within a data source’s schema, determines the kind of value that can be stored in a column for organized data management. The available data types include integer, float, date, and string.