I have this table (Day, Employee no, Employee Name, Client no, Client name, Product no, Product Description, Unit Price, Quantity Sold, Total Sales)
Example data :
22nd, e123, Dave, c1264, Sheila, p15462, Hoover, 4.50, 5, --
----, ----, -----, c64402, Jovek, p673431, Kettle, 2.25, 10, 45
----, e4215, Johnny, c785, Keith, p15462, Hoober, 4.50, 2, 9
23rd, e123, Dave, c64402, Jovek, p673431, Kettle, 2.25, 20, --
So basically, there is only data for the day if its a new day entry, and there is only a total for total sales, after all the sales that an employee has made.
So far, I have got :
Product(ProdNo#,ProductDesc,Price)
Client(ClientNo#, ClientName)
Employee(EmployeeNo#, EmployeeName)
However, I'm unsure what to do regarding the individual sales and total sales for every day?
Thanks for any help!
This is typical example for the use of a star- or snowflake schema.
The tables Product, Customer, Employee are called dimension tables.
The fact table has foreign keys to the dimension table and contains a quantity, e.g. the concrete sale.
Sales(ProdNo#, ClientNo#, EmployeeNo#, Sale)
The primary key of is a compound key of ProdNo#, ClientNo#, EmployeeNo#.
Total sales would not be modelled explicitly but queried via aggregation, e.g.
SELECT P.ProdNo, SUM(S.sale)
FROM Products P, Sales S
WHERE P.Price > 1000 AND S.ProdNo = P.ProdNo
GROUP BY P.ProdNo
The RDBMS or data warehouse will optimize the query, so total sales do need to be modeled explicitly (no denormalization).
Related
I am trying to find churned customer in the adventureworks2012 sample database. Churned customer in my case is a customer who used to be active in a period of six months, then has not made any transaction in a later period of time.
My attributes are customer ID, product category, product subcategories, price, order dates, online order flag etc
Can you please provide some hints on how to define teacher customer as either churned or not churned.
Thank you in advance.
If you're trying to loop through them all:
SELECT TEACHER_ID, MAX(ORDER_DATE) FROM ORDERS GROUP BY TEACHER_ID
Will give you each teachers last order date, and then you can loop through and compare them to whatever date range you want (if you're doing a loop).
If you're trying to figure out an individual teacher just see if the count is > 0:
SELECT COUNT(*) AS COUNT FROM ORDERS WHERE TEACHER_ID = ? AND ORDER_DATE > (NOW() - INTERVAL 6 MONTH)
Best I can do w\o a better idea what language you're using and what the application is.
I have a SQL Server database with a table dbo.sales with 7 columns.
First column contains different sales person names, on column 2 to 6 other information, on column 7, sales average.
Question: what I need is a query to get all sales person details (all seven columns in Excel) if their sales average is more than 60% between a given date.
For example: in my database, I have data from 01/05/2016 to 31/05/2016, if I enter a period in my Excel sheet between 25/05/2016 to 31/05/2016 and my required average for ex. 60% (should be changed as per my need), then I need all the sales person details who continuously have sales average of more than 60% between 25 to 31st May 2016.
If a sales man average was dropped below 60% on 28th May, then I don't want to see him on my report. In simple words, I need all sales person who continuously hitting 60% or more on average sales within my search period.
Not sure if the sales period date is within the table, but if it is, that query should work for you:
;WITH PeriodSales as (
SELECT * FROM Sales
WHERE SalseDate between #StartDt and #EndDt)
SELECT * FROM PeriodSales
WHERE SalesPerson not in (
SELECT SalesPerson FROM PeriodSales
WHERE CASE WHEN IsNumeric(salesavg) = 1
THEN CAST(salesavg as Decimal) ELSE 0 END <= 60.
);
I have two tables in my MS Access Database database inventory and Orders
My tables:
Inventory
ProductID,
Product (Shirts, Pants),
Amount
Orders
OrderID,
CustomerID,
CustomerName,
Date Order Was Made,
Date Order is For,
ProductID,
Product,
Amount,
I have my database connected to my program and saving the orders works perfect. I just want that when the order is saved in the database, the Amount from the Orders table is subtracted from the amount in Inventory
E.G If Bob order 10 shirts and 50 were in Inventory that 50 should turn to 40
BTW I'm very sorry if I'm not clear enough I'm very new to VB.Net so I may not understand everything said and thank you for the help
I want to create a small database for my inventory but I have some problems on picking a structure. The inventory will be updated daily at the end of the day.
The problem I am facing is the following.
I have a table for my products, having an
id, name, price, quantity.
Now I have another table for my sales, but there is my problem. What kind of fields do I need to have. At the end of the day I want to store a record like this:
20 product_x $ 5,00 $ 100,-
20 product_y $ 5,00 $ 100,-
20 product_z $ 5,00 $ 100,-
20 product_a $ 5,00 $ 100,-
-------------------------------------------------
$ 400,-
So how do I model this in a sales record. Do I just create a concatenated record with the product id's comma separated.
Or is there another way do model this the right way.
This is a model which supports many aspects,
Supports Sites, Locations and Warehouses etc.
Supports Categorization and Grouping
Support Generic Product (Ex. "Table Clock" and specific product "Citizen C123 Multi Alarm Clock" )
Also support Brand Variants (by various manufacturers)
Has CSM (color / size / model support) Ex. Bata Sandles (Color 45 Inch Blue color)
Product Instances with serials (such as TVs , Refrigerators etc.)
Lot control / Batch control with serial numbers.
Pack Size / UOM and UOM Conversion
Manufacturer and Brands as well as Suppliers
Also included example transaction table (Purchase order)
There are many other transaction types such as Issues, Transfers, Adjustments etc.
Hope this would help. Please let me know if you need further information on each table.
Cheers...!!!
Wajira Weerasinghe.
Sites
id
site_code
Site_name
Warehouse
id
site_id
warehouse_code
warehouse_name
Item Category
id
category_code
category_name
Item Group
id
group_code
group_name
Generic Product
id
generic_name
Product
id
product_code
category_id
group_id
brand_id
generic_id
model_id/part_id
product_name
product_description
product_price (current rate)
has_instances(y/n)
has_lots (y/n)
has_attributes
default_uom
pack_size
average_cost
single_unit_product_code (for packs)
dimension_group (pointing to dimensions)
lot_information
warranty_terms (general not specific)
is_active
deleted
product attribute type (color/size etc.)
id
attribute_name
product_attribute
id
product_id
attribute_id
product attribute value (this product -> red)
id
product_attribute_id
value
product_instance
id
product_id
instance_name (as given by manufacturer)
serial_number
brand_id (is this brand)
stock_id (stock record pointing qih, location etc.)
lot_information (lot_id)
warranty_terms
product attribute value id (if applicable)
product lot
id
lot_code/batch_code
date_manufactured
date_expiry
product attribute value id (if applicable)
Brand
id
manufacturer_id
brand_code
brand_name
Brand Manufacturer
id
manufacturer_name
Stock
id
product_id
warehouse_id, zone_id, level_id, rack_id etc.
quantity in hand
product attribute value id (if applicable) [we have 4 red color items etc.]
Product Price Records
product_id
from_date
product_price
Purchase Order Header
id
supplier_id
purchase_date
total_amount
Purchase Order Line
id
po_id
product_id
unit_price
quantity
Supplier
id
supplier_code
supplier_name
supplier_type
product_uom
id
uom_name
product_uom_conversion
id
from_uom_id
to_uom_id
conversion_rule
I'd have a table with a row per item per day - store the date, the item ID, the quantity sold, and the price sold at (store this even though it's also in the product table - if that changes, you want the value you actually sold at preserved). You can compute totals per item-day and totals per day in queries.
Tables:
create table product (
id integer primary key,
name varchar(100) not null,
price decimal(6,2) not null,
inventory integer not null
);
create table sale (
saledate date not null,
product_id integer not null references product,
quantity integer not null,
price decimal(6,2) not null,
primary key (saledate, product_id)
);
Reporting on a day:
select s.product_id, p.name, s.quantity, s.price, (s.quantity * s.price) as total
from product p, sale s
where p.id = s.product_id
and s.saledate = date '2010-12-5';
Reporting on all days:
select saledate, sum(quantity * price) as total
from sale
group by saledate
order by saledate;
A nice master report over all days, with a summary line:
select *
from (
(select s.saledate, s.product_id, p.name, s.quantity, s.price, (s.quantity * s.price) as total
from product p, sale s
where p.id = s.product_id)
union
(select saledate, NULL, 'TOTAL', sum(quantity), NULL, sum(quantity * price) as total
from sale group by saledate)
) as summedsales
order by saledate, product_id;
Try modelling your sales as a transaction - with a "header", i.e. who sold to, when sold, invoice # (if applicable), etc. and "line items", i.e. 20 * product_x # $5 = $100. The safest approach is to avoid relying upon prices etc. from the products table - as these will presumably change over time, and instead copy much of the product information (if not all) into your line item - so even when prices, item descriptions etc. change, the transaction information remains as was at the time the transaction was made.
Inventory can get quite complex to model. First you need to understand that you need to be able to tell the value of the inventory onhand based on what you paid for it. This means you cannot rely on a product table that is updated to the current price. While you might want such a table to help you figure out what to sell it for, there are tax reasons why you need to know the actual vlaue you paid for each item in the warehouse.
So first you need the product table (you might want to make sure you have an updated date column in this, it can be handy to know if your prices seem out of date).
Then you need a table that stores the actual warehouse location of each part and the price at purchase. If the items are large enough, you need a way to individually mark each item, so that you know what was taken out. Usually people use barcodes for that. This table needs to be updated to record that the part is no longer there when you sell it. I prefer to make the record inactive and have a link to my sales data to that record, so I know exactly what I paid for and what I sold each part for.
Sales should have at least two tables. One for the general information about the sale, the customername (there should also be a customer table most of the time to get this data from), the date, where it was shipped to etc.
Then a sales detail table that includes a record for each line item in the order. Include all the data you need about the part, color, size, quantity, price. This is not denormalizing, this is storing historical data. The one thing you do not want to do is rely on the prices in the product table for anything except the inital entry to this table. You do not want to do a sales report and have the numbers come out wrong becasue the product prices changed the day before.
Do not design an inventory database without consulting with an accountant or specialist in taxes. You also should do some reading on internal controls. It is easy to steal from a company undetected that has not done their work on internal controls in the database.
I think you need a table with fields showing the transaction properties per customer
OR
a table with fields - date, product(foreign), quantity - this way you'll have no problem with new products
Try multiple tables with links
table_products
id
name
table_product_sales
id
product_id
quantity
price_per
transaction_time AS DATETIME
SELECT table_product_sales.*, table_product.name
FROM table_product
JOIN table_product_sales
ON table_product_sales.product_id = table_product.id
GROUP BY DATE(transaction_time)
Haven't tried it but will something like that work? That allows you to keep each transactions separate so you can query things like average number sold per sale, total sold per date, total sales each day, etc.
Assuming a schema structure as such.
-----------------------------------------
Stock (ID, Description, blah blah)
-----------------------------------------
StockBarcode (ID, StockID, Barcode, Price, blah blah)
-----------------------------------------
What is the optimal way of storing units of measure for your stock items? Given that the StockBarcode Price may be for 1 item, for 10 Items, for 10 grams or for 10 pounds?
Stock to StockBarcode is a one to many relationship. (Although Im sure you didnt need me telling you that)
Cheers :)
You might think about putting an additional UOM column on ALL tables where Qty fields are and additional Currency column on all money columns.
ALL entry screens should ask Qty and UOM.
Item table - add Inventory/Stocking UOM, Purchasing/Receive UOM,
Pricing UOM, Shipping/Send UOM, Production UOM, Component UOM columns
new UOM table - ID, Abbrev., Description, RegionID, UOMTypeID
new UOMRegion table - ID, Code, Description (example data - 1, UK,
United Kingdom;
2, US, United States;
3, INT, International)
new UOMType table - ID, Code, Description, DefaultUOMID (example
data - 1, V, Volume, 15;
2, A, Area, 45;
3, W, Weight, 32;
etc.)
new UOMConversionFactor table - ID, FromUOMID, ToUOMID,
ConversionFactor (example data - 1, 1, 1, 1;
2, 1, 3, 0.026021066655565;
3, 3, 1, 38.430399999999000)
(notes - Conversion from UOM to same UOM is 1. May put in table or
not.
Each record I usually have an implied column FromQty which is always 1.
Make sure ConversionFactor allows for HUGE numbers so final numbers turn out more accurate when large Qty are involved)
Thoughts - 1) some UOM are not specific enough such as "barrel" (there is a US dry goods barrel, a US barrel for cranberries, U.S. fluid barrel, U.K. a beer barrel, US beer barrel, oil barrel, etc.), 2) UOM is impacted by region if you are worrying about an international application (ie. a US cup is different from UK cup that is different than the international cup), 3) I can get a receive a cartoon of item X, store it in pallets, and ship it in eaches. 4) "kit" or "build" items can be raw materials in UOM plus various components in different UOM that ultimately results in a final product in a different UOM.
I'd be adding Qty and UOMID columns to the StockBarcode table and then a new table like
StockUOM (ID, Description)
If i understand your stock table correctly, it consists of the products that you are stocking to sell.
One option to consider is that instead of stock data maybe you should consider keeping the data based on what in stock keeping parlance, is referred to as SKU (stock keeping unit) Information.
Each SKU itself can be made of more than 1 item but as it cannot be sold that way, you dont have to concern yourself with those details in most scenarios. Details like price etc are all properties that are then associated with the SKU.
Eg: If a product say beer can be sold individually / 6 pack / 12 pack then it has 3 SKU's associated with it.
Then you have relationships :
Products --> SKU's which is 1:many
SKU --> StockBarCode which is 1:1 (assuming you have the same bar code for all the units of the same SKU - if not then it can be 1: Many as well)
Is there a unique StockBarcode for every UOM? For example, is there a barcode for grams, a barcode for pounds and a barcode for individual items? If so, Andrew's solution will work.
If not, you will need to create another table that contains the StockID, Qty and UOMID's.
StockUOM (ID, Description)
StockCount (ID, StockID, UOMID, Qty)
When you scan the barcode, you will need to enter in what UOM you are scanning for. Then the software can update the StockCount table based on item scanned. This could be a good fallback in case your items don't have more than one barcode, and you are stocking more than one UOM (common).