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Now that the business use and classification of the application is established, the application can be created using the UI. In AdminUI, set up the application by going to the Set-up Application tab, select Create New, and filling out the file structure. Since we have just one layer file system we will have just one entity in it.
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Step 2: Creating Meta Model
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Add the column names and data types from the dataset into the Create Meta Model page and then click submit. Note that you do not add the as_of_date column, as that will be added automatically.
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Step 3: Creating Analytical Model
The data flow from the source i.e. google drive to directly to BDL is achieved using analytical model. Pre-processing of data is also done using analytical model.
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Step 4: Running the Analytical Workloads
Running the analytical workload for INFLATION application will load the data directly from your local to the BDL fact db.
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Step 6: Importing Database and Dataset into Superset and creating a dashboard for the charts
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Now that the business use and classification of the application is established, the application can be created using the UI. In AdminUI, set up the application by going to the Set-up Application tab, select Create New, and filling out the file structure. ce weSince we have just one layer file system we will have just one entity in it.
...
Step 2: Creating Meta Model
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Add the column names and data types from the teams dataset into the Create Meta Model page and then click submit. Note that you do not add the as_of_date column, as that will be added automatically.
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Step 3: Creating Ingest Model
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The data is taken from the BDL fact db and is used for training the ML model onto it and making predictions on the target column using analytical model.
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Step 5: Running the Analytical Workloads
Running the analytical workload for INFLATION application will load the data directly from your local to the BDL fact db.
...
Step Step 6: Importing Database and Dataset into Superset and creating a dashboard for the charts
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