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What is the difference between Junk and Confirmed Dimention?
where can be used htat one in Informatica?
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Answer / prabhu
Junk dimension contains the data which are currently not
useful. we have to keep these data for feature analysis
purpose.
Whereas Confirm dimentions are common for multiple fact
table.
| Is This Answer Correct ? | 4 Yes | 0 No |
Answer / sarvesh
merge two or more dimensional tables which are having the
low cardinality colomns into a single table is known
as "junk dimensional tables,
two or more fcat tables can be shared with a single
dimensional table is known as "conformed dimension"
| Is This Answer Correct ? | 2 Yes | 2 No |
Answer / chaitanya
An interesting use for a junk dimension is to capture the context of a specific transaction. While our
common, conformed dimensions contain the key dimensional attributes of interest, there are likely
attributes about the transaction that are not known until the transaction is processed.
| Is This Answer Correct ? | 0 Yes | 0 No |
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Design a mapping to get year of join for each employee.
rank() over (partition by opt2.dim_plat_site_id, opt2.dim_site_opt_sid order by case when opt2.dm_market_flg in ('Y', 'U') then 1 else 2 end, lkp.contact_rank) as rank1, case opt2.contact_type when 'Buyer' then row_number() over (partition by opt2.dim_plat_site_id, opt2.dim_site_opt_sid, lkp.contact_rank order by has_name_flg desc, ship_to_flg desc , last_order_dt desc) when 'Decision Maker' then row_number() over (partition by opt2.dim_plat_site_id, opt2.dim_site_opt_sid, lkp.contact_rank order by has_name_flg desc , last_quote_dt desc , mailability_score desc , source_ranking desc) when 'Influencer' then row_number() over (partition by opt2.dim_plat_site_id, opt2.dim_site_opt_sid, lkp.contact_rank order by has_name_flg desc, mailability_score desc, source_ranking desc) when 'Payer' then row_number() over (partition by opt2.dim_plat_site_id, opt2.dim_site_opt_sid, lkp.contact_rank order by has_name_flg desc, mailability_score desc, source_ranking desc) --elu 05/28/2013 else row_number() over (partition by opt2.dim_plat_site_id, opt2.dim_site_opt_sid, lkp.contact_rank order by has_name_flg desc, mailability_score desc, source_ranking desc) end rank2 row_number() over (partition by opt3.dim_plat_site_id, opt3.dim_site_opt_sid order by rank1,rank2) as "rank", case when "rank"<= opt3.maximum_value then 'Y' else 'N' end as include_flg
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