Hey @dpc 

I don't know if you can do it without customizing a query parser... I don't have this exact script but maybe this could help. First step would be to find out which tables haven't been queried a lot in the past days (in this case, 90 days). 

with used_tables as (
select
  source_table_catalog,
  source_table_schema,
  source_table_name,
  count(distinct created_by) as downstream_users,
  count(*) as downstream_dependents
from
  system.access.table_lineage
where
  true
  and source_table_full_name is not null
  and event_time >= date_add(now(), -90)
group by
  all
)

select
  tabelas.table_catalog
  ,tabelas.table_schema
  ,tabelas.table_name
  ,tabelas.table_type
  ,tabelas.table_owner
  ,tabelas.`comment` as table_comment
  ,tabelas.created as table_created_at
  ,tabelas.created_by as table_created_by
  ,tabelas.last_altered as table_last_update_at
  ,tabelas.last_altered_by as table_last_altered_by
from
  system.information_schema.`tables` as tabelas
  left join used_tables as ut on ut.source_table_catalog = tabelas.table_catalog and ut.source_table_schema = tabelas.table_schema and ut.source_table_name = tabelas.table_name
where
  true
  and ut.downstream_dependents is null
  and tabelas.table_catalog != "system"
  and tabelas.table_catalog != "__databricks_internal"
  and tabelas.table_schema != "information_schema"

 You could then go deeper into the SQL queries, parsing the statement to see whether people are using "*" or specific columns.  

SELECT 
       l.source_table_full_name,
       l.entity_type,
       q.statement_text,
       q.executed_by,
       q.end_time
  FROM system.access.table_lineage  l
  JOIN system.query.history q
  ON l.entity_run_id = q.statement_id
WHERE source_table_full_name = '< insert table name >'