def METHOD_NAME(dest_dir: str) -> None:
    log.info(f"{DATASET_SHORT_NAME}.start")
    #
    # Load data.
    #
    # Load ingested raw data from walden.
    walden_ds = WaldenCatalog().find_one(
        namespace=NAMESPACE,
        short_name=WALDEN_DATASET_SHORT_NAME,
        version=WALDEN_VERSION,
    )
    local_file = walden_ds.ensure_downloaded()
    raw_data = pd.read_json(local_file, lines=True)
    #
    # Process data.
    #
    # Extract total energy consumption from the raw data.
    data = extract_variable_from_raw_eia_data(raw_data=raw_data, variable_name=VARIABLE_NAME, unit_name=UNIT_NAME)
    #
    # Save outputs.
    #
    # Create new dataset using metadata from walden.
    ds = Dataset.create_empty(dest_dir)
    ds.metadata = convert_walden_metadata(walden_ds)
    # Update metadata appropriately.
    ds.metadata.short_name = DATASET_SHORT_NAME
    ds.metadata.title = DATASET_TITLE
    ds.metadata.description = DATASET_DESCRIPTION
    ds.save()
    # Create a table in the dataset with the same metadata as the dataset.
    table_metadata = TableMeta(
        short_name=DATASET_SHORT_NAME,
        title=DATASET_TITLE,
        description=DATASET_DESCRIPTION,
    )
    tb = Table(data, metadata=table_metadata)
    # Ensure all columns are lower-case and snake-case.
    tb = underscore_table(tb)
    # Add table to a dataset.
    ds.add(tb)
    log.info(f"{DATASET_SHORT_NAME}.end")