def METHOD_NAME(dest_dir: str) -> None:
    #
    # Load data.
    #
    # Read all required datasets.
    ds_beis: catalog.Dataset = paths.load_dependency("uk_historical_electricity")
    ds_elec: catalog.Dataset = paths.load_dependency("electricity_mix")
    # Gather all required tables from all datasets.
    tb_beis = ds_beis["uk_historical_electricity"]
    tb_elec = ds_elec["electricity_mix"]
    # Create convenient dataframes.
    df_beis = pd.DataFrame(tb_beis).reset_index()
    df_elec = pd.DataFrame(tb_elec).reset_index()
    #
    # Process data.
    #
    # Prepare electricity mix data.
    df_elec = prepare_electricity_mix_data(df_elec=df_elec)
    # Prepare BEIS data.
    df_beis = prepare_beis_data(df_beis=df_beis)
    # Combine BEIS and electricity mix data.
    df_combined = combine_beis_and_electricity_mix_data(df_beis=df_beis, df_elec=df_elec)
    # Create a new table with combined data (and no metadata).
    tb_combined = catalog.Table(df_combined)
    #
    # Save outputs.
    #
    # Create new garden dataset.
    ds_garden = catalog.Dataset.create_empty(dest_dir)
    # Add combined table to the new dataset.
    tb_combined.metadata.short_name = "uk_historical_electricity"
    ds_garden.add(tb_combined)
    # Update the rest of the metadata from the yaml file.
    ds_garden.update_metadata(paths.metadata_path, if_source_exists="replace")
    # Save dataset.
    ds_garden.save()