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Aug 23, 2022 03:21 AM
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Data Science
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Data Warehousing
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Jason Ching Yuen Siu
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Level of Aggregations and Data Warehousing Architecture
Summary
- The higher the level of aggregation, the more aggregation in the fact measure.
- A data warehouse is built primarily used for drilling down some interesting data for business decision.
- It is common when we design a data warehouse, we start from a high level of aggregation, where fact measures contain aggregated values. Lowering down the level of aggregation can be done by changing the granularity of the dimension, or by simply adding new dimensions.
- Determining whether a star schema is in Level-0 or not can be tricky. Not having an aggregated fact measure does not always mean that the star schema is on Level-0. Hence, it is important to understand the concept of transaction recorded in the E/R diagram of the operational database
What does levels of granularity imply?
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F6be532d3-9ed7-40a3-ad23-a4cd23e26a1a%2FUntitled.png%3Ftable%3Dblock%26id%3Db8eb45c3-56ba-412f-b6c8-8020dee59947%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3D9fr7sgJS_ecXKdN7LeV6pvAHAo-4lK1nwvp5dkK4dMk?table=block&id=b8eb45c3-56ba-412f-b6c8-8020dee59947&cache=v2)
Aggregate values have different levels of granularity.
- The lower the level of granularity:
- The higher the level of aggregation (e.g., level 0,1,2)
- The more specific information we can get. (越低越細)Level 0 is the highest level (Most detail).
In another words, the granularity (or details) of dim is low, so the level of agg is high.
Example:
- Total Sales per Year has lower granularity than Total Sales per Quarter.
- Number of Logins in the lab per Semester has different level of focus (or granularity) than Number of Logins in the lab per Month
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F76282b9f-9732-4793-a0c3-0b0e5de207b7%2FUntitled.png%3Ftable%3Dblock%26id%3D84c26372-6975-4049-ab49-c069a282eb7d%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3Dpb8kx0is-lNfYX9woDgLjb9dW4bIBv1wBKiaid8o7qI?table=block&id=84c26372-6975-4049-ab49-c069a282eb7d&cache=v2)
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2Fd756398d-37be-4b44-a289-9bd7796500ed%2FUntitled.png%3Ftable%3Dblock%26id%3Dfee17c44-a32d-4ff3-b6ab-1fcf9d94021e%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DT1Xa_FKTxY-keZXOZM4wEWk2phjyz0OzG4vSupCiQFk?table=block&id=fee17c44-a32d-4ff3-b6ab-1fcf9d94021e&cache=v2)
How to lower down the level of aggregations
- Add a new dimension. When we add a new dimension, each value in the fact measure will literally be broken down more details on each record of the new dimension.
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F3c9997d8-aedb-46a5-8050-3dc0ff209417%2FUntitled.png%3Ftable%3Dblock%26id%3Db4c13bc1-2142-474d-8e50-7e611efd1633%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DBD4JdgVURONgqHzkmZOhAvmeL3A8mT810xUvOnbo7Fc?table=block&id=b4c13bc1-2142-474d-8e50-7e611efd1633&cache=v2)
- Replace an existing dimension with a higher granularity dimension. The values of the fact measures will also be broken down more details because the fact measure has a lower detail dimension
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2Fbc3dfa6e-8ac2-44da-b4a9-fda35ccd926c%2FUntitled.png%3Ftable%3Dblock%26id%3D42abb3c4-67ba-42c1-a560-3d8b476f106c%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3D7HgZ7u52KSLN-ikWqaanGkQyF-sCpPYrcHiNWW-nC0o?table=block&id=42abb3c4-67ba-42c1-a560-3d8b476f106c&cache=v2)
How do we know if the schema is in its lowest level (i.e., Lv 0)?
- Op = Schema. Attributes are the same as the ones in the operation database.
- Unaggregated fact measures. Lv 0 has no aggregation so values of fact measures are 1.
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2Fe7a3deb9-a35f-44e2-afae-99eb596a748c%2FUntitled.png%3Ftable%3Dblock%26id%3D3829970c-5e72-4d3c-a663-d0fbf78c774c%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3D-pQ_yYPJnMyIMk-LEGruOqYbGst94cMpt6OsU9q7GR8?table=block&id=3829970c-5e72-4d3c-a663-d0fbf78c774c&cache=v2)
What are the case when level of aggregation CANNOT be compared?
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2Fb3c29235-261b-460f-94f3-ea64a9830eb8%2FUntitled.png%3Ftable%3Dblock%26id%3Dccfa8076-c035-4e55-b686-751546ef39e8%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DErmoSMJ0DuICqebqbapDfs72VwmXuFBnf2aZMWBtiZI?table=block&id=ccfa8076-c035-4e55-b686-751546ef39e8&cache=v2)
Case Studies
Case study 1: The number of logins per hour at night?
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2Fd08bdb7b-6679-4487-bc53-857e556ddd2f%2FUntitled.png%3Ftable%3Dblock%26id%3D2a48a80a-cd26-4e66-a699-e975eda3760e%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DCNmX1z-dMOpf5o-g55WMPaC9mSuvBRDbOJ6S8Co2up0?table=block&id=2a48a80a-cd26-4e66-a699-e975eda3760e&cache=v2)
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2Fa6dadd13-3fc3-4c9b-b4d4-efdcbbb4539c%2FUntitled.png%3Ftable%3Dblock%26id%3D03a076c8-7b6f-42bd-8c24-4361b949f7fd%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3D0dwVqtNfp-LrSMYSZmQwbx6Zc5nyoo0HDDnvfXACrPY?table=block&id=03a076c8-7b6f-42bd-8c24-4361b949f7fd&cache=v2)
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F502dde6d-1666-4afa-91d8-38f7d006d28e%2FUntitled.png%3Ftable%3Dblock%26id%3D66dc79dd-49e7-4a15-a1a9-07f07e9497cc%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DMq7CU-drtQ8-F8qx4Dqt-I4SX7oZQm7-Ysc_jMxigGo?table=block&id=66dc79dd-49e7-4a15-a1a9-07f07e9497cc&cache=v2)
Star schema
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F671364eb-e1ec-4984-815f-9d0713701a4d%2FE1572D4B-9AE9-4594-B693-0DAE5F7DC51F.jpeg%3Ftable%3Dblock%26id%3Dbef41779-4ed1-482a-a147-5b9ac8275790%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DUSM_1UInMw_NUEhMfKnNztRbc1JcYkPDiTVPDnZvrf4?table=block&id=bef41779-4ed1-482a-a147-5b9ac8275790&cache=v2)
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F80025a42-3bd1-425f-a327-de8a248ec12e%2FC8FAF388-9B29-4C8E-8B98-11BB5819BC7C.jpeg%3Ftable%3Dblock%26id%3Dd2577068-34cf-4b64-a342-83c4a4d67895%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3Do03jcCkMUH99M2utlTZ8cir6ll-8LIOKlquiVhbIeKM?table=block&id=d2577068-34cf-4b64-a342-83c4a4d67895&cache=v2)
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2Ffa4a87aa-3db2-4af0-8083-3682bf75cecf%2F4083E778-5C64-47E7-B338-0DC1D029BE8D.jpeg%3Ftable%3Dblock%26id%3De7ea5253-798c-48e7-9990-0ef54ccc3e98%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DszqntxGlIICsc31qO7qIfyRUgMqdNNGO8Oa93wGZQjg?table=block&id=e7ea5253-798c-48e7-9990-0ef54ccc3e98&cache=v2)
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F3965d4db-3c66-46f0-9446-6f5a735fe204%2F1958FF3F-107D-4FD0-94F6-5BB898527E89.jpeg%3Ftable%3Dblock%26id%3D52aca0ab-2fdc-4108-8f6e-d8b4a52f0d77%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DodlAr31SwdqJtd0fb5TM4bNaCWJ3mIN7E_8ar2q-17s?table=block&id=52aca0ab-2fdc-4108-8f6e-d8b4a52f0d77&cache=v2)
Case study 2 (Lab) : Clothing Company
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F550e36d1-a609-4f72-943f-ea8f6384d9c3%2FUntitled.png%3Ftable%3Dblock%26id%3D58ed19f2-0dfe-44c6-962a-88ce91991e6e%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DDBy8-lDOACsepdupFqfcTzNvgl-_Swqj6_V-Tbf7Nf4?table=block&id=58ed19f2-0dfe-44c6-962a-88ce91991e6e&cache=v2)
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F92aa3193-4d6c-49d6-bdfc-53d9fa6feb1d%2FUntitled.png%3Ftable%3Dblock%26id%3D35a716e6-e1b5-49a8-894c-03b64c1a49a9%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DZ-OpT_F6M29aHEZDDN6voa6uQKg0T83Nn5Dhg7MGnJA?table=block&id=35a716e6-e1b5-49a8-894c-03b64c1a49a9&cache=v2)
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2Fe6d1aa13-4ba8-4a8c-ab76-b63ed90a9c80%2FUntitled.png%3Ftable%3Dblock%26id%3Dbb33b2d5-b9b0-495c-a65e-d84365a6bdf4%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DxgDgWgF-zGWLm25PiCrGsnpbSfMBxXVbZZwHL6txp4U?table=block&id=bb33b2d5-b9b0-495c-a65e-d84365a6bdf4&cache=v2)
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F74f1e44a-edf9-4fa7-8dc2-cb7e0d71af85%2FUntitled.png%3Ftable%3Dblock%26id%3D399726af-b198-4ec8-9283-23dc70f9cc51%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3Dshoe1i1-w9AXWuY83XrHpp8jJENlkrZBks6D-s2lgFQ?table=block&id=399726af-b198-4ec8-9283-23dc70f9cc51&cache=v2)
Case study 3 (Lab) : Toll Way
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F56adde89-bdb1-4130-9702-251f0beca14f%2FUntitled.png%3Ftable%3Dblock%26id%3Deacc83a2-4ea8-4eec-a6d5-cb89b9bfa378%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DQgWiqmtTWCuiR2VdyAxaHr5kyQ_AUP_JvnoTFlDTA2g?table=block&id=eacc83a2-4ea8-4eec-a6d5-cb89b9bfa378&cache=v2)
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F74d92ea1-1562-4119-a54b-0b7ecaea041c%2FUntitled.png%3Ftable%3Dblock%26id%3Dd94d89eb-783e-4fd3-9f3e-c72978ab331b%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DxumjugfU4KgX75zdkLLg5TzL5MxY92FL12TT4t6WIsI?table=block&id=d94d89eb-783e-4fd3-9f3e-c72978ab331b&cache=v2)
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F7abcb10c-c94b-46d5-b0c5-94a79d1547a2%2FUntitled.png%3Ftable%3Dblock%26id%3D7f8037a5-7233-48e0-abfa-4dfdcad9a406%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DHPCryQGX6blyPSYXQ-JdJ8NIhhjRHN7fnLJuN4So37s?table=block&id=7f8037a5-7233-48e0-abfa-4dfdcad9a406&cache=v2)
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2Fc9f8ffcd-5a85-405c-8651-46b2dfd23990%2FUntitled.png%3Ftable%3Dblock%26id%3Df0286ee1-a6c8-40fa-bccc-8efb5c8bdc22%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3D8Lmey23KbnR-7N6efiBjcl4qotEFKQb3N7-aIjhNxfQ?table=block&id=f0286ee1-a6c8-40fa-bccc-8efb5c8bdc22&cache=v2)
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2Fea98ad8f-a48a-402c-8787-b77430765fdb%2FUntitled.png%3Ftable%3Dblock%26id%3Ddbf7d02f-7ed3-483a-856d-fdffb0e2349b%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DhQo7t5hbZoIdYwcqQIZVQrAQtRNuzhM0w_VJJeHRNkY?table=block&id=dbf7d02f-7ed3-483a-856d-fdffb0e2349b&cache=v2)
Star Schemas with No Aggregation (i.e., Level 0 )
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F4db0840e-f4a0-4b48-893f-541a0263b1e4%2FUntitled.png%3Ftable%3Dblock%26id%3Dd9d5e5a8-cada-457b-ae8d-bcd86a3e7238%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3D_t-uS6i06yUW6UrQHcPYT3GAxcj6UTx_Od4NOOB1RX0?table=block&id=d9d5e5a8-cada-457b-ae8d-bcd86a3e7238&cache=v2)
Although dims cannot be broken down, having lowest dims does NOT gurantee that the values of FM is Unaggregated. So, these are NOT in lv 0.
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F5ab798b8-0446-4b11-9476-061b32087978%2FUntitled.png%3Ftable%3Dblock%26id%3Dbd738a9f-cca2-4d86-a15b-7226533b6ce1%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DRBa46UZtbkajuC0jyaQxFlHLPcQ5-sDF85U3U8IQbXA?table=block&id=bd738a9f-cca2-4d86-a15b-7226533b6ce1&cache=v2)
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F7610a84f-61d4-4b69-b34c-9b7df5109a8b%2FUntitled.png%3Ftable%3Dblock%26id%3Dbfeb3ac6-5264-4cfe-a560-cc8b6d5f49fc%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DKrGJwZQAPHsVLxiY3i52dMq2Xn1bv0JCxRfCqNu8zrw?table=block&id=bfeb3ac6-5264-4cfe-a560-cc8b6d5f49fc&cache=v2)
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2Fdf215065-611f-4d63-ba24-8b6b786aaaf8%2FUntitled.png%3Ftable%3Dblock%26id%3D1ed1cac3-7d9f-4f64-80e0-aca7c3357907%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DbBDdRd5WXU5FwaRXoW8CZKfHXQ4h7zXavVI4-ofA0rU?table=block&id=1ed1cac3-7d9f-4f64-80e0-aca7c3357907&cache=v2)
This is not Level-0 because the fact measures do not capture both sides of the m-m relationship between Purchase Order and Item entities in the E/R diagram; rather, it captures one side only, which is from the Purchase Order side and not from the Item side.
There are three possible lv0 schemas
If we need to include all possible dimensions in the star schema, we can add Product Dimension to the star schema.
And Level-0 star schema must have the Purchase Order Dimension and Item Dimension as its core.
Since the star schemas below come with these two core dimensions, it is at lv 0.
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F1f461c34-e80f-403d-8e37-f7f29d5eeebb%2FUntitled.png%3Ftable%3Dblock%26id%3Dce7e71ec-dea4-49bc-8ff2-e5c600d009e3%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DpWit_FCgZfxp8L1On0kbecHUGeWJ7Bt7Vo2vMgmJS3E?table=block&id=ce7e71ec-dea4-49bc-8ff2-e5c600d009e3&cache=v2)
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F112827a8-cca8-4e1c-bd12-41bd4180843b%2FUntitled.png%3Ftable%3Dblock%26id%3D76ecd844-38b9-4e36-bf9b-82a0610f62b2%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3DGIbYdgQvTOc4_bHPeY4yQe4mXO9Qs5SaULbyRIQeTiw?table=block&id=76ecd844-38b9-4e36-bf9b-82a0610f62b2&cache=v2)
The most complete star schema with Customer Dimension and Product Dimension
or with either Customer Dimension (Fig. 14.14) or Product Dimension only
![notion image](https://www.notion.so/image/https%3A%2F%2Ffile.notion.so%2Ff%2Ff%2Fe1c5ba0e-562a-49b0-8505-ce5e38fc061b%2F6bb73595-b0be-4bbe-adb9-27aa6a3f989e%2FUntitled.png%3Ftable%3Dblock%26id%3De8db5762-15fb-4c19-9580-8b30e71e204d%26spaceId%3De1c5ba0e-562a-49b0-8505-ce5e38fc061b%26expirationTimestamp%3D1725789600000%26signature%3Dp9xvdFrkq18iwTDJ22bmJKtg65LvXBjmpk56O5Jwt2g?table=block&id=e8db5762-15fb-4c19-9580-8b30e71e204d&cache=v2)
Conclusion
The Level-0 star schema should focus on the transaction level of the E/R diagram, which is denoted by the m-m relationship.
Understanding the Relationship between Transactions and Fact Measures
- Author:Jason Siu
- URL:https://jason-siu.com/article/851e0123-12a5-4628-bda2-45f9f260dd29
- Copyright:All articles in this blog, except for special statements, adopt BY-NC-SA agreement. Please indicate the source!
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