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In addition to this site, `}<a parentName=\"p\" {...{\n        \"href\": \"http://preset.io/\"\n      }}>{`Preset.io`}</a>{` maintains an updated set of end-user\ndocumentation at `}<a parentName=\"p\" {...{\n        \"href\": \"https://docs.preset.io/\"\n      }}>{`docs.preset.io`}</a>{`.`}</p>\n    <p>{`This tutorial targets someone who wants to create charts and dashboards in Superset. We’ll show you\nhow to connect Superset to a new database and configure a table in that database for analysis.\nYou’ll also explore the data you’ve exposed and add a visualization to a dashboard so that you get a\nfeel for the end-to-end user experience.`}</p>\n    <h3 {...{\n      \"id\": \"connecting-to-a-new-database\"\n    }}>{`Connecting to a new database`}</h3>\n    <p>{`Superset itself doesn't have a storage layer to store your data but instead pairs with\nyour existing SQL-speaking database or data store.`}</p>\n    <p>{`First things first, we need to add the connection credentials to your database to be able\nto query and visualize data from it. If you're using Superset locally via\n`}<a parentName=\"p\" {...{\n        \"href\": \"/docs/installation/installing-superset-using-docker-compose\"\n      }}>{`Docker compose`}</a>{`, you can\nskip this step because a Postgres database, named `}<strong parentName=\"p\">{`examples`}</strong>{`, is included and\npre-configured in Superset for you.`}</p>\n    <p>{`Under the `}<strong parentName=\"p\">{`Data`}</strong>{` menu, select the `}<em parentName=\"p\">{`Databases`}</em>{` option:`}</p>\n    <img src=\"/images/tutorial_01_sources_database.png\" />{' '} <br /><br />\n    <p>{`Next, click the green `}<strong parentName=\"p\">{`+ Database`}</strong>{` button in the top right corner:`}</p>\n    <img src=\"/images/tutorial_02_add_database.png\" />{' '} <br /><br />\n    <p>{`You can configure a number of advanced options in this window, but for this walkthrough you only\nneed to specify two things (the database name and SQLAlchemy URI):`}</p>\n    <img src=\"/images/tutorial_03_database_name.png\" />\n    <p>{`As noted in the text below\nthe URI, you should refer to the SQLAlchemy documentation on\n`}<a parentName=\"p\" {...{\n        \"href\": \"https://docs.sqlalchemy.org/en/12/core/engines.html#database-urls\"\n      }}>{`creating new connection URIs`}</a>{`\nfor your target database.`}</p>\n    <p>{`Click the `}<strong parentName=\"p\">{`Test Connection`}</strong>{` button to confirm things work end to end. If the connection looks good, save the configuration\nby clicking the `}<strong parentName=\"p\">{`Add`}</strong>{` button in the bottom right corner of the modal window:`}</p>\n    <img src=\"/images/tutorial_04_add_button.png\" />\n    <p>{`Congratulations, you've just added a new data source in Superset!`}</p>\n    <h3 {...{\n      \"id\": \"registering-a-new-table\"\n    }}>{`Registering a new table`}</h3>\n    <p>{`Now that you’ve configured a data source, you can select specific tables (called `}<strong parentName=\"p\">{`Datasets`}</strong>{` in Superset)\nthat you want exposed in Superset for querying.`}</p>\n    <p>{`Navigate to `}<strong parentName=\"p\">{`Data ‣ Datasets`}</strong>{` and select the `}<strong parentName=\"p\">{`+ Dataset`}</strong>{` button in the top right corner.`}</p>\n    <img src=\"/images/tutorial_08_sources_tables.png\" />\n    <p>{`A modal window should pop up in front of you. Select your `}<strong parentName=\"p\">{`Database`}</strong>{`,\n`}<strong parentName=\"p\">{`Schema`}</strong>{`, and `}<strong parentName=\"p\">{`Table`}</strong>{` using the drop downs that appear. In the following example,\nwe register the `}<strong parentName=\"p\">{`cleaned_sales_data`}</strong>{` table from the `}<strong parentName=\"p\">{`examples`}</strong>{` database.`}</p>\n    <img src=\"/images/tutorial_09_add_new_table.png\" />\n    <p>{`To finish, click the `}<strong parentName=\"p\">{`Add`}</strong>{` button in the bottom right corner. You should now see your dataset in the list of datasets.`}</p>\n    <h3 {...{\n      \"id\": \"customizing-column-properties\"\n    }}>{`Customizing column properties`}</h3>\n    <p>{`Now that you've registered your dataset, you can configure column properties\nfor how the column should be treated in the Explore workflow:`}</p>\n    <ul>\n      <li parentName=\"ul\">{`Is the column temporal? (should it be used for slicing & dicing in time series charts?)`}</li>\n      <li parentName=\"ul\">{`Should the column be filterable?`}</li>\n      <li parentName=\"ul\">{`Is the column dimensional?`}</li>\n      <li parentName=\"ul\">{`If it's a datetime column, how should Superset parse\nthe datetime format? (using the `}<a parentName=\"li\" {...{\n          \"href\": \"https://en.wikipedia.org/wiki/ISO_8601\"\n        }}>{`ISO-8601 string pattern`}</a>{`)`}</li>\n    </ul>\n    <img src=\"/images/tutorial_column_properties.png\" />\n    <h3 {...{\n      \"id\": \"superset-semantic-layer\"\n    }}>{`Superset semantic layer`}</h3>\n    <p>{`Superset has a thin semantic layer that adds many quality of life improvements for analysts.\nThe Superset semantic layer can store 2 types of computed data:`}</p>\n    <ol>\n      <li parentName=\"ol\">{`Virtual metrics: you can write SQL queries that aggregate values\nfrom multiple column (e.g. `}<inlineCode parentName=\"li\">{`SUM(recovered) / SUM(confirmed)`}</inlineCode>{`) and make them\navailable as columns for (e.g. `}<inlineCode parentName=\"li\">{`recovery_rate`}</inlineCode>{`) visualization in Explore.\nAgggregate functions are allowed and encouraged for metrics.`}</li>\n    </ol>\n    <img src=\"/images/tutorial_sql_metric.png\" />\n    <p>{`You can also certify metrics if you'd like for your team in this view.`}</p>\n    <ol {...{\n      \"start\": 2\n    }}>\n      <li parentName=\"ol\">{`Virtual calculated columns: you can write SQL queries that\ncustomize the appearance and behavior\nof a specific column (e.g. `}<inlineCode parentName=\"li\">{`CAST(recovery_rate) as float`}</inlineCode>{`).\nAggregate functions aren't allowed in calculated columns.`}</li>\n    </ol>\n    <img src=\"/images/tutorial_calculated_column.png\" />\n    <h3 {...{\n      \"id\": \"creating-charts-in-explore-view\"\n    }}>{`Creating charts in Explore view`}</h3>\n    <p>{`Superset has 2 main interfaces for exploring data:`}</p>\n    <ul>\n      <li parentName=\"ul\"><strong parentName=\"li\">{`Explore`}</strong>{`: no-code viz builder. Select your dataset, select the chart,\ncustomize the appearance, and publish.`}</li>\n      <li parentName=\"ul\"><strong parentName=\"li\">{`SQL Lab`}</strong>{`: SQL IDE for cleaning, joining, and preparing data for Explore workflow`}</li>\n    </ul>\n    <p>{`We'll focus on the Explore view for creating charts right now.\nTo start the Explore workflow from the `}<strong parentName=\"p\">{`Datasets`}</strong>{` tab, start by clicking the name\nof the dataset that will be powering your chart.`}</p>\n    <img src=\"/images/tutorial_launch_explore.png\" /><br /><br />\n    <p>{`You're now presented with a powerful workflow for exploring data and iterating on charts.`}</p>\n    <ul>\n      <li parentName=\"ul\">{`The `}<strong parentName=\"li\">{`Dataset`}</strong>{` view on the left-hand side has a list of columns and metrics,\nscoped to the current dataset you selected.`}</li>\n      <li parentName=\"ul\">{`The `}<strong parentName=\"li\">{`Data`}</strong>{` preview below the chart area also gives you helpful data context.`}</li>\n      <li parentName=\"ul\">{`Using the `}<strong parentName=\"li\">{`Data`}</strong>{` tab and `}<strong parentName=\"li\">{`Customize`}</strong>{` tabs, you can change the visualization type,\nselect the temporal column, select the metric to group by, and customize\nthe aesthetics of the chart.`}</li>\n    </ul>\n    <p>{`As you customize your chart using drop-down menus, make sure to click the `}<strong parentName=\"p\">{`Run`}</strong>{` button\nto get visual feedback.`}</p>\n    <img src=\"/images/tutorial_explore_run.jpg\" />\n    <p>{`In the following screenshot, we craft a grouped Time-series Bar Chart to visualize\nour quarterly sales data by product line just be clicking options in drop-down menus.`}</p>\n    <img src=\"/images/tutorial_explore_settings.jpg\" />\n    <h3 {...{\n      \"id\": \"creating-a-slice-and-dashboard\"\n    }}>{`Creating a slice and dashboard`}</h3>\n    <p>{`To save your chart, first click the `}<strong parentName=\"p\">{`Save`}</strong>{` button. You can either:`}</p>\n    <ul>\n      <li parentName=\"ul\">{`Save your chart and add it to an existing dashboard`}</li>\n      <li parentName=\"ul\">{`Save your chart and add it to a new dashboard`}</li>\n    </ul>\n    <p>{`In the following screenshot, we save the chart to a new \"Superset Duper Sales Dashboard\":`}</p>\n    <img src=\"/images/tutorial_save_slice.png\" />\n    <p>{`To publish, click `}<strong parentName=\"p\">{`Save and goto Dashboard`}</strong>{`.`}</p>\n    <p>{`Behind the scenes, Superset will create a slice and store all the information needed\nto create your chart in its thin data layer\n(the query, chart type, options selected, name, etc).`}</p>\n <img src=\"/images/tutorial_first_dashboard.png\" />\n    <p>{` To resize the chart, start by clicking the pencil button in the top right corner.`}</p>\n <img src=\"/images/tutorial_pencil_edit.png\" />\n    <p>{`Then, click and drag the bottom right corner of the chart until the chart layout snaps\ninto a position you like onto the underlying grid.`}</p>\n <img src=\"/images/tutorial_chart_resize.png\" />\n    <p>{` Click `}<strong parentName=\"p\">{`Save`}</strong>{` to persist the changes.`}</p>\n    <p>{`Congrats! You’ve successfully linked, analyzed, and visualized data in Superset. There are a wealth\nof other table configuration and visualization options, so please start exploring and creating\nslices and dashboards of your own`}</p>\n\n    </MDXLayout>;\n}\n;\nMDXContent.isMDXComponent = true;\n      "],"sourceRoot":""}