I have seen many joining condition using hr_all_organization_units and mtl_parameters
but is it possible to join hr_organization_information with mtl_parameters?
In documentation I could not get difference on hr_all_organization_units and hr_organization_information
select * from hr_organization_information hou, mtl_parameters mp where
mp.organization_id=hou.organization_id;
Is the above query logically correct in Oracle EBS?
hr_all_organization_units holds all organizations, regardless of their classification, e.g. Operating Units, HR Organizations, Inventory Organizations, etc..
mtl_parameters has records only for Inventory Organizations, to store additional inventory related information.
hr_organization_information is a generic table that stores attributes for each organization, e.g. org_information_context='CLASS' to define the type of organization.
You can link this table directly with mtl_parameters as you did in the example, but you would:
only find records for inventory organizations
have duplicate records as you have more than one type of org_information_context for each organization in the hr_organization_information table.
Please note that one organization in hr_all_organization_units can have different classifications at the same time, e.g. Operating Unit and Inventory Organization.
Here is an example dataset from an Oracle Vision environment, which has one record per organization and shows their classifications in columns G to Q:
https://www.enginatics.com/example/per-organizations/
The PER Organzations Blitz Report shows the link between the organization and the org information table.
Related
I'm very new to Microsoft Access, and I'm trying to figure out how to output data from a table into a format that's more concise and easier to read.
I have transaction data throughout the year for specific customers. Based off of the Customer number and Catalog number, I would like to consolidate multiple instances of a customer purchasing the same product into one row, run a sum in the Quantity column for instances of the same product, and run a sum in the Price column for instances of the same product.
Desired Output
Input
I tried using an append Query with Customer # and Catalog # as the primary key to try to filter out duplicate entries, but this wasn't working. I'm not super familiar with writing functions in Access, but willing to try anything.
TLDR: single and multi-select choice fields: for a generic ETL tool should I model them as nodes connected with relationships or direct labels
Detail:
I am thinking through an ETL tool/workflow that I am building that pulls from an API source to create graphs on the fly. The api generally returns data structured as individual entries that belong to "lists" such as People, Company, City, etc. with individual attributes/properties also present on the entries.
I know that I want to create node labels for each 'List', BUT the thing is that multiple list types have single and multi-select choice fields on an individual entry (such as company type for the company list. Company type options might include institution, bank, school, investor, real estate company, etc. and a company can have one or many types).
I ideally would want a generic rule that can handle all choice fields across all lists when writing to the neo4j graph. (Another choice field is "Tier" for example, with Tier 1, Tier 2, Tier 3 and Tier 4 as potential values)
Would it be best practice to
create a node label for each choice field category (i.e. a node label called "CompanyType" with X instances of that node one for each company type with a "name" property equal to the company type), and then link the Company node to its one or many CompanyType nodes via a "company_type" edge
or
create a node label for each choice field option and apply that label to the Company node in question (So a Company node might then have 5-6 labels such as Company:Tier1:Tier2:Investor:Bank)
In my CouchDB database, I have the following models (implemented as documents in the database with different type fields):
Team: name, id (has many matches, has many fans)
Match: name, team_a, team_b, time (has many teams, has many tweets)
Fan: team_id (has many tweets)
Tweet: time, sentiment, fan_id
I want to average the tweet sentiment for each team. If I were using SQL I'd do it like this:
SELECT avg(sentiment)
FROM team
JOIN match on team.id = match.team_a OR team.id = match.team_b
JOIN fan on fan.team = team.id
JOIN tweet on (tweet.time BETWEEN match.time AND match.time + interval '1 hour') AND tweet.user = fan.id
GROUP BY team.id
However in CouchDB you can at best do 1 join in a view function, as explained in the docs (by emitting the join field as the key).
How can this be better modelled in CouchDB to allow for this query to work? I don't really want to denormalise too much, but I guess I will if I have to?
It's a bit complex, but I use what I call "tertiary indexes". The goal is to be able to write a view that is applied to another view. Unfortunately, the only way to do this is to use a view to write data to a secondary database and then have another view that works on that database. Doing this requires an outside process - I use a script that listens to the _changes feed of the primary database, and then updates the relevant documents in the secondary database when something changes.
So in your example your secondary database could consist of a single document for each team with all of the (or the latest) match/fan/tweet data in that one document. Then you write a view that extracts the sentiment (or whatever) from that secondary database.
I'm trying to create a ER diagram of a simple retail chain type database model. You have your customer, the various stores, inventory etc.
My first question is, how to represent a customer placing an order in a store. If the customer is a discount card holder, the company has their name, address etc, so I can have a cardHolder entity connect to item and store with an order relationship. But how do I represent an order being placed by a customer who is not really an entity in the database?
Secondly, how are conditional... stuff represented in ER diagrams, e.g. in a car dealership, a customer may choose one or more optional extra when buying a car. I would think that there is a Car entity with the relevant attributes and the options as a multi-valued attribute, but how do you represent a user picking those options (I.e. order table shows the car ordered, extras chosen and the added cost of extras) in the order relationship?
First, do you really need to model customers as distinct entities, or do you just need order, payment and delivery details? Many retail systems don't track individual customers. If you need to, you can have a customer table with a surrogate key and unique constraints on identifying attributes like SSN or discount card number (even if those attributes are optional). It's generally hard to prevent duplication in customer tables since there's no ideal natural key for people, so consider whether this is really required.
How to model optional extras depends on what they depends on. Some extras might be make or model-specific, e.g. the choice of certain colors or manual/automatic transmission. Extended warranties might be available across the board.
Here's an example of car-specific optional extras:
car (car_id PK, make, model, color, vin, price, ...)
car_extras (extra_id PK, car_id FK, option_name, price)
order (order_id PK, date_time, car_id FK, customer_id FK, payment_id FK, discount)
order_extras (order_id PK/FK, car_id FK, extra_id PK/FK)
I excluded price totals since those can be calculated via aggregate queries.
In my example, order_extras.car_id is redundant, but supports better integrity via the use of composite FK constraints (i.e. (order_id, car_id) references the corresponding columns in order, and (car_id, extra_id) references the corresponding columns in car_optional_extras to prevent invalid extras from being linked to an order).
Here's an ER diagram for the tables above:
First, as per your thought you can definitely have two kinds of customers. Discount card holders whose details are present with the company and new customers whose details aren't available with the company.
There are three possible ways to achieve what you are trying,
1) Have two different order table in the system(which I personally wouldn't suggest)
2) Have a single Order table in the system and getting the details of those who are a discount card holder.
3) Insert a row in the discount card holder table for new/unregistered customers having only one order table in the system.
Having a single order table would make the system standardized and would be more convenient while performing many other operations.
Secondly, to solve your concern, you need to follow normalization. It will reduce the current problem faced and will also make the system redundant free and will make the entities light weighted which will directly impact on the performance when you grow large.
The extra chosen items can be listed in the order against the customer by adding it at the time of generating a bill using foreign key. Dealing with keys will result in fast and robust results instead of storing redundant/repeating details at various places.
By following normalization, the problem can be handled by applying foreign keys wherever you want to refer data to avoid problems or errors.
Preferably NF 4 would be better. Have a look at the following link for getting started with normalization.
http://www.w3schools.in/dbms/database-normalization/
I am in the process of designing this E-R diagram for a shop of which I have shown part of below (the rest is not relevant). See the link please:
E-R diagram
The issue that I have is that the shop only sells two items, Socks and Shoes.
Have I correctly detailed this in my diagram? I'm not sure if my cardinalities and/or my design is correct. A customer has to buy at least one of these items for the order to exist (but has the liberty to buy any number).
The Shoe and Sock entities would have their respective ID attribute, and I am planning to translate to a relational schema like this:
(I forgot to add to my diagram the ORDER_CONTAINS relationship to have an attribute called "Quantity". )
Table: Order_Contains
ORDER_ID | SHOEID | SOCKID | QTY
primary key | FK, could be null |FK, could be null | INT
This clearly won't work since the Qty would be meaningless. Is there a way I can reduce the products to just two products and make all this work?
Having two one-to-many relationships combined into one with nullable fields is a poor design. How would you record an order containing both shoes and socks - a row per shoe with SOCKID set to NULL and vice-versa for socks, or would you combine rows? In the former case the meaning of QTY is clear though it depends on the contents of SHOEID/SOCKID fields, but what would the QTY mean in the latter case? How would you deal with rows where both SHOEID and SOCKID are NULL and the QTY is positive? Keep in mind Murphy's law of databases - if it can be recorded it will be. Worse, your primary key (ORDER_ID) will prevent you from recording more than one row, so a customer couldn't buy more than one (pair of) socks or shoes.
A better design would be to have two separate relations:
Order_Socks (ORDER_ID PK/FK, SOCKID PK/FK, QTY)
Order_Shoes (ORDER_ID PK/FK, SHOEID PK/FK, QTY)
With this, there's only one way to record the contents of an order and it's unambiguous.
You have not explained very well the context here. I'll try to explain from what I understand, and give you some hints.
Do your shop only and always (forever) sell 2 products? Do the details of these products (color, model, weight, width, etc...) need to be persisted in the database? If yes, then we have two entities in the model, SOCKS and SHOES. Each entity has its own properties. A purchase or a order is usually seen as an event on the ERD. If your customers always buys (or order) socks with shoes, then there will always be a link between three entities:
CLIENTS --- SHOES --- SOCKS
This connection / association / relationship is an event, and this would be the purchase (or order).
If a customer can buy separate shoes and socks, then socks and shoes are subtypes of a super entity, called PRODUCTS, and a purchase is an event between CUSTOMERS and PRODUCTS. Here in this case we have a partitioning relationship.
If however, your customers buy separate products, and your store will not sell forever only 2 products, and details of the products are not always the same and will not be saved as columns in a table, then the case is another.
Shoes and socks are considered products, as well as other items that can be considered in future. Thus, we have records/rows in a PRODUCTS table.
When a customer places an order (or a purchase), he (she) is acquiring products. There is a strong link between customers and products here, again usually an event, which would be the purchase (or a order).
I do not know if you do it, but before thinking of start a diagram, type the problem context in a paper or a document. Show all details present in the situation.
The entities are seen when they have properties. If you need to save the name of a customer, the customer's eye color, the customer's e-mail, and so on, then you will have certainly a CUSTOMER entity.
If you see entities relate in some way, then you have a relationship, and you should ask yourself what kind of relationship these entities form. In your case of products and customers, we have a purchasing relationship there between. The established relationship is a purchase (or an order, you call it). One customer can buy various products, and one product (not on the same shelf, is the type, model) can be purchased for several customers, thus, we have a Many-To-Many relationship.
The relationship created changes according to the context. Whatever, we'll invent something crazy here as examples. Say we have customers and products. Say you want to persist a situation where customers lick Products (something really crazy, just for you to see how the context says the relationship).
There would be an intimate connection between customers and products entities (really close... I think...). In this case, the relationship represents a history of customers licking products. This would generate an EVENT. In this event you could put properties such as the date, the amount of times a customer licked a proper product, the weather, the time, the traffic light color on the street, etc., only what you need to persist according to your context, your needs.
Remember that for N-N relationships created, we need to see if new entities (out of relationship) will emerge. This usually happens when you are decomposing the conceptual model to the logical model. Probably, product orders will generate not one but two entities: The ORDER and the products of orders. It is within the products of orders that you place the list of products ordered from each customer, and the quantity.
I would like to present various materials to study ERD, but unfortunately they are all in Portuguese. I hope I have helped you in some way. If you want to be more specific about your problem, I think I can really help you best. Anything, please ask.