The database has a table called "categories" with columns CATEGORY_ID(primary key) and CATEGORY_NAME.
I have subcategories for each category.
For better accessing which is the best method from the below methods.
Method 1: The "CATEGORY_ID" column in the "categories" table is a FOREIGN KEY in the "subcategories " table.
Method 2: Maintaining a separate table for each category representing the subcategories.
I prefer to use same table for category and sub category
like
Table Categories
[CATEGORY_ID, CATEGORY_NAME, PARENT_CATEGORY_ID]
In case you don't know how many sub categories are there.
This scenario is just an example, the scenario is as follows: We have a product table where all the records of products are stored. Same way we will have customer table where records of customers are stored. The daily sales keep the record of all the sales. This sales table will keep record of which product who has purchased. So linking is to be done from Sales table to product table and customer table.
The query to link the two tables is as follows:SELECT product_name, customer.name, date_of_sale FROM sales, product, customer WHERE product.product_id = sales.product_id and customer.customer_id >= sales.customer_id LIMIT 0, 30
It is better to go with Method 1 since it is more scalable.
Let me elaborate on this. If we go with method 1, we need to maintain 2 tables only that is Categories and Subcategories. In future if we have new categories or subcategories we can directly deal with this 2 tables.
If we consider same situation with Method2 then we need to create new tables every time, this may become maintenance overhead.
Let me be a bit more direct. You explain in a comment that Method 2 is a separate table for each category. If so, then Method 2 -- in general -- is just wrong.
There are two methods for storing this type of information. One is a Categories table with a (single) Subcategories table. The Subcategories table would have CategoryId, a foreign key reference back to Categories. This is the normalized data model.
The second method is to store everything in one table. Each row would be a category/subcategory combination. Information about a given category would be duplicated across multiple rows, so this is not a normalized approach. However, this is a typical approach when doing dimensional modeling for decision support systems.
If the subcategories are just names of things, there is a third approach, which would be to store a list of the subcategories within each Category row. The list would not be a delimited string. It would be JSON, a nested table, XML, array, or similar collection data type supported by the database you are using. I am mentioning this as a possibility, but not recommending it.
New to VBA and Access so hope I can explain this correctly.
I have two tables , Orders and Deliveries.
Orders include OrderNo, CustomerName, CustomerAddress, CustomerContact and so on.
Deliveries include DeliveryNo, OrderNo, DeliveryDate, DeliveryType and so on.
I have created a relationship between these two tables linking them between OrderNo as I require the CustomerName when creating a Delivery from an Order.
However sometimes a Delivery is manually inserted into the table using a form. A CustomerName is required for this record but there is now no corresponding OrderNo.
I am not sure how to set up my table to accommodate manual entries.
Appreciate the help, thanks
It sounds like the business requirement is to be able to insert deliveries into the delivery table without a corresponding order number. If this is the case, you need to relax the constraints on the table and remove relationship between Delivery.OrderNo and the Orders table. Otherwise, you could populate this field with a special number (0 or -1) to indicate no order in this circumstance if you need to enforce the foreign key relationship for other reasons. It all depends on how you wish to enforce the business logic.
What if you just added a CustomerName field to the form?
For what I understood of your question, you use the Orders table to generate the Deliveries, so for each order in the Orders table you would add/generate a record to the Deliveries table. Now, when you add a delivery manually(using the form) I suppose there is no order associated with it, hence no Customer Name. In that case the only solution would be to add a field called CustomerName to the mentioned form (I suppose the person who is manually inserting the Delivery knows the name of the customer) and any other field you need, and if your business logic requires it you can create a "virtual" Order with the same OrderNo as the inserted delivery.
I am using MS-Access database.
I am trying to make relationship with two tables, Old Customer table having data and Newly added coupon table.
As my client want to introduce new concept of coupon, where customer come with coupon instead of giving cash.
I have inserted Coupon code in coupon table in bulk.
Now, I am confused about what kind of relationship I should create with these two tables ?
I have to consider the below things...
customer can give either cash or coupon.
IF customer show the coupon, there will be an entry in CouponID column
as well in cash column (to know the value of that coupon.)
The CouponID should be unique in the customer table, Coupon Code should
not be repeated.
I am confused whether it should be one-To-One or One-To-Many ?
This image will help you to understand the problem.
I would not include "CouponID" in the customer table at all (nor "Cash" for that matter). The customer table models a customer, the coupon table models a coupon.
You need another table to model the transaction:
[CustomerTransaction]
id
date
customer_id
coupon_id
etc...
Every type of independent "thing" should be modeled by a discrete table. and "things" should be related to each other by other tables that create the 1:N relationship.
The relationship of customer to coupon is an optional (ie nullable) one-to-one; your data model looks good.
Some other comments:
The table would be better named sale rather than customer, since if the same customer comes back again, there will be a new row (but with the same name)
You could create a unique index on couponID that ignores nulls
You could rename Cash to Amount; the amount is either "cash" or coupon - the couponID column tells you the type of the amount
To create a unique index that ignores nulls:
CREATE UNIQUE INDEX idx1 ON customer (couponID) WITH IGNORE NULL;
I am creating a purchase order system where someone can store details of their purchase. So I created a database, with tables for supplier information from which we will buy stuff and another table where we store what we are buying.
In the PurchaseOrder table, there are columns for :
PurchaseOrderNo (Primary)
BuyerInitials
DateOfPurchase
ProjectCode
Items (linking to the PurchaseItems table)
I want to add another column with Items' details, so I created another table PurchaseItems which has the following columns:
PurchaseOrderNo. (this would be repeat for each part)
PartNo
Description
Quantity
UnitAmount
VATAmount
TotalAmount
Logically it seems simple, but I can't seem to get my head around on how I would link the tables. Thank you very much for the help :)
Create a seperate table say OrderedItems which maps the PartNo and PurchaseOrderNo. This avoids the repetition of PurchaseOrderNo in each row and also maintains the relation between PurchaseOrder and PurchaseItems table.
Preface:
I was thinking the other day about a new database structure for a new application and realized that we needed a way to store historical data in an efficient way. I was wanting someone else to take a look and see if there are any problems with this structure. I realize that this method of storing data may very well have been invented before (I am almost certain it has) but I have no idea if it has a name and some google searches that I tried didn't yield anything.
Problem:
Lets say you have a table for orders, and orders are related to a customer table for the customer that placed the order. In a normal database structure you might expect something like this:
orders
------
orderID
customerID
customers
---------
customerID
address
address2
city
state
zip
Pretty straightforward, orderID has a foreign key of customerID which is the primary key of the customer table. But if we were to go and run a report over the order table, we are going to join the customers table to the orders table, which will bring back the current record for that customer ID. What if when the order was placed, the customers address was different and it has been subsequently changed. Now our order no longer reflects the history of that customers address, at the time the order was placed. Basically, by changing the customer record, we just changed all history for that customer.
Now there are several ways around this, one of which would be to copy the record when an order was created. What I have come up with though is what I think would be an easier way to do this that is perhaps a little more elegant, and has the added bonus of logging anytime a change is made.
What if I did a structure like this instead:
orders
------
orderID
customerID
customerHistoryID
customers
---------
customerID
customerHistoryID
customerHistory
--------
customerHistoryID
customerID
address
address2
city
state
zip
updatedBy
updatedOn
please forgive the formatting, but I think you can see the idea. Basically, the idea is that anytime a customer is changed, insert or update, the customerHistoryID is incremented and the customers table is updated with the latest customerHistoryID. The order table now not only points to the customerID (which allows you to see all revisions of the customer record), but also to the customerHistoryID, which points to a specific revision of the record. Now the order reflects the state of data at the time the order was created.
By adding an updatedby and updatedon column to the customerHistory table, you can also see an "audit log" of the data, so you could see who made the changes and when.
One potential downside could be deletes, but I am not really worried about that for this need as nothing should ever be deleted. But even still, the same effect could be achieved by using an activeFlag or something like it depending on the domain of the data.
My thought is that all tables would use this structure. Anytime historical data is being retrieved, it would be joined against the history table using the customerHistoryID to show the state of data for that particular order.
Retrieving a list of customers is easy, it just takes a join to the customer table on the customerHistoryID.
Can anyone see any problems with this approach, either from a design standpoint, or performance reasons why this is bad. Remember, no matter what I do I need to make sure that the historical data is preserved so that subsequent updates to records do not change history. Is there a better way? Is this a known idea that has a name, or any documentation on it?
Thanks for any help.
Update:
This is a very simple example of what I am really going to have. My real application will have "orders" with several foreign keys to other tables. Origin/destination location information, customer information, facility information, user information, etc. It has been suggested a couple of times that I could copy the information into the order record at that point, and I have seen it done this way many times, but this would result in a record with hundreds of columns, which really isn't feasible in this case.
When I've encountered such problems one alternative is to make the order the history table. Its functions the same but its a little easier to follow
orders
------
orderID
customerID
address
City
state
zip
customers
---------
customerID
address
City
state
zip
EDIT: if the number of columns gets to high for your liking you can separate it out however you like.
If you do go with the other option and using history tables you should consider using bitemporal data since you may have to deal with the possibility that historical data needs to be corrected. For example Customer Changed his current address From A to B but you also have to correct address on an existing order that is currently be fulfilled.
Also if you are using MS SQL Server you might want to consider using indexed views. That will allow you to trade a small incremental insert/update perf decrease for a large select perf increase. If you're not using MS SQL server you can replicate this using triggers and tables.
When you are designing your data structures, be very carful to store the correct relationships, not something that is similar to the correct relationships. If the address for an order needs to be maintained, then that is because the address is part of the order, not the customer. Also, unit prices are part of the order, not the product, etc.
Try an arrangement like this:
Customer
--------
CustomerId (PK)
Name
AddressId (FK)
PhoneNumber
Email
Order
-----
OrderId (PK)
CustomerId (FK)
ShippingAddressId (FK)
BillingAddressId (FK)
TotalAmount
Address
-------
AddressId (PK)
AddressLine1
AddressLine2
City
Region
Country
PostalCode
OrderLineItem
-------------
OrderId (PK) (FK)
OrderItemSequence (PK)
ProductId (FK)
UnitPrice
Quantity
Product
-------
ProductId (PK)
Price
etc.
If you truly need to store history for something, like tracking changes to an order over time, then you should do that with a log or audit table, not with your transaction tables.
Normally orders simply store the information as it is at the time of the order. This is especially true of things like part numbers, part names and prices as well as customer address and name. Then you don;t have to join to 5 or six tables to get teh information that can be stored in one. This is not denormalization as you actually need to have the innformation as it existed at the time of the order. I think is is less likely that having this information in the order and order detail (stores the individual items ordered) tables is less risky in terms of accidental change to the data as well.
Your order table would not have hundreds of columns. You would have an order table and an order detail table due to one to many relationships. Order table would include order no. customer id 9so you can search for everything this customer has ever ordered even if the name changed), customer name, customer address (note you don't need city state zip etc, put the address in one field), order date and possibly a few other fields that relate directly to the order at a top level. Then you have an order detail table that has order number, detail_id, part number, part description (this can be a consolidation of a bunch of fields like size, color etc. or you can separate out the most common), No of items, unit type, price per unit, taxes, total price, ship date, status. You put one entry in for each item ordered.
If you are genuinely interested in such problems, I can only suggest you take a serious look at "Temporal Data and the Relational Model".
Warning1 : there is no SQL in there and almost anything you think you know about the relational model will be claimed a falsehood. With good reason.
Warning2 : you are expected to think, and think hard.
Warning3 : the book is about what the solution for this particular family of problems ought to look like, but as the introduction says, it is not about any technology available today.
That said, the book is genuine enlightenment. At the very least, it helps to make it clear that the solution for such problems will not be found in SQl as it stands today, or in ORMs as those stand today, for that matter.
What you want is called a datawarehouse. Since datawarehouses are OLAP and not OLTP, it is recommended to have as many columns as you need in order to achieve your goals. In your case the orders table in the datawarehouse will have 11 fields as having a 'snapshot' of orders as they come, regardless of users accounts updates.
Wiley -The Data Warehouse Toolkit, Second Edition
It's a good start.
Our payroll system uses effective dates in many tables. The ADDRESSES table is keyed on EMPLID and EFFDT. This allows us to track every time an employee's address changes. You could use the same logic to track historical addresses for customers. Your queries would simply need to include a clause that compares the order date to the customer address date that was in effect at the time of the order. For example
select o.orderID, c.customerID, c.address, c.city, c.state, c.zip
from orders o, customers c
where c.customerID = o.customerID
and c.effdt = (
select max(c1.effdt) from customers c1
where c1.customerID = c.customerID and c1.effdt <= o.orderdt
)
The objective is to select the most recent row in customers having an effective date that is on or before the date of the order. This same strategy could be used to keep historical information on product prices.
I myself like to keep it simple. I would use two tables: a customer table and a customer history table. If you have the key (e.g. CustomerID) in the history table there is no reason to make a joining table, a select on that key will give you all records.
You also don't have audit information (e.g. date modified, who modified etc) in the history table as you show it, I expect you want this.
So mine would look something like this:
CustomerTable (this contains current customer information)
CustomerID (distinct non null)
...all customer information fields
CustomerHistoryTable
CustomerID (not distinct non null)
...all customer information fields
DateOfChange
WhoChanged
The DateOfChange field is the date the customer table was changed (from the values in this record) to the values in a more recent record of the values in the CustomerTable.
You orders table just needs a CustomerID if you need to find the customer information at the time of the order it is a simple select.