Im struggling to understand how to make an inventory application:
Store inventory data (item name, sku, descriptions, prices, inventory counts)
Allow computers access from different networks
Keep computers updated. By that I dont understand how they communicate to each other across different networks/connections, so that if one computer makes a change to say inventory count how does it let the other computers know to subtract say 5 of an item bc 5 were sold.
question 1 I can understand how storage works to a degree, but when it comes to 2 and 3 how would you approach it? I figured servers would be the answer but then the question becomes what kind? AWS RDS? If you have links to tutorials that can explain this process and different approaches please feel free to link
Ive been trying to figure this out for a few months now and I think im getting more confused than answers (I swear I get more inventory application ADs crap than actual information, like no joke try searching "how inventory applications store and update data and keep computers updated" or any phrase like that... and its a bazillion freaking ads lol)
Related
I have a simple django project and I am trying to keep track of ranks for certain objects to see how they change over time. For example, what was the rank of US GDP (compared to other countries) over last 3 years. Below is the postgres db structure I am working with:
Below is what I am trying to achieve:
What I am finding challenging is that the previous period value may or may not exist and it's possible that even the entity may or may not be in the pervious period. Period can be year, quarter or months but for a specific record it can be either of one and stays consistently same for all the years for that record.
Can someone guide me in the right direction to write a query to achieve those tables? I am trying to avoid writing heavy forloop queries because there may be 100s of entities and many years of data.
So far I have only been able to achieve the below output:
I am just trying to figure out how to use annotate to fetch previous period values and ranks but I am pretty much stuck.
At my work we have two systems, one that collects the customers payments automatically every month. And one that manages the memberships of those customers. Sadly our outdated technology doesn’t communicate to each other so we don’t know if a customer actually paid for their membership without manually auditing them.
I’ve been put in charge of this process and boy does it take awhile to do.
I have limited knowledge of C++ and was looking into maybe writing a program to do the comparisons for me.
I have two ideas on how to implement this, and was wondering what you guys thought. If these would be best or if it’s even possible or if there’s a better solution?
Current Setup: We have a list of all members in excel, with how much each should be paying, we then go through the actual money collected and check to make sure everyone’s payment went through and was processed and not declined.
Option 1: have a multi-dimensional array of strings. Read the excel file into this array it would have three Columns, first name, last name, amount they should be paying. This would be put in alphabetical order to help with the searching. I would then export the transactions in css file format and read each line one at a time. When it reads a line it would search the array for the same first and last name. Once found it would take the amount paid confirm it said processed and not declined and if so would subtract it from the customers amount they should be paying. In the end if every customers amount they should be paying is equal to 0 then everyone paid.
Option 2: is similar to option 1 just instead of using a multidimensional array it would use two css files. And not put the items into the array at the start.
Thoughts? Is this a smart way to combat this problem? I’m a newbie programmer so I’m just looking for suggestions/advice.
Your solutions would work, but are suited for small datasets. I don't now what your constraints are, but I think that a more elegant solution would be to setup a database on the first system first(instead of the excel file).
Are you allowed to create a database? How many customers are in the excel file?
I have a bit of a unique problem here. I currently have two warehouses that I ship items out of for selling on Amazon, my primary warehouse and my secondary warehouse. Shipping out of the secondary warehouse takes significantly longer than shipping from the main warehouse, hence why it is referred to as the "secondary" warehouse.
Some of our inventory is split between the two warehouses. Usually this is not an issue, but we keep having a particular issue. Allow me to explain:
Let's say that I have 10 red cups in the main warehouse, and an additional 300 in the secondary warehouse. Let's also say it's Christmas time, so I have all 310 listed. However, from what I've seen, Amazon only allows one shipping time to be listed for the inventory, so the entire 310 get listed as under the primary warehouse's shipping time (2 days) and doesn't account for the secondary warehouse's ship time, rather than split the way that they should be, 10 at 2 days and 300 at 15 days.
The problem comes in when someone orders an amount that would have to be split across the two warehouses, such as if someone were to order 12 of said red cups. The first 10 would come out of the primary warehouse, and the remaining two would come out of the secondary warehouse. Due to the secondary warehouse's shipping time, the remaining two cups would have to be shipped out at a significantly different date, but Amazon marks the entire order as needing to be shipped within those two days.
For a variety of reasons, it is not practical to keep all of one product in one warehouse, nor is it practical to increase the secondary warehouse's shipping time. Changing the overall shipping date for the product to the longest ship time causes us to lose the buy box for the listing, which really defeats the purpose of us trying to sell it.
So my question is this: is there some way in MWS to indicate that the inventory is split up in terms of shipping times? If so, how?
Any assistance in this matter would be appreciated.
Short answer: No.
There is no way to specify two values for FulfillmentLatency, in the same way as there is no way to specify two values for Quantity in stock. You can only ever have one inventory with them (plus FBA stock)
Longer answer: You could.
Sign up twice with Amazon:
"MySellerName" has an inventory of 10 and a fulfillment latency of 2 days
"MySellerName Overseas Warehouse" has an inventory of 300 and a fulfillment latency of 30 days
I haven't tried by I believe Amazon will then automatically direct the customer to the best seller for them, which should be "MySellerName" for small orders and "MySellerName Overseas Warehouse" for larger quantities.
I need to create a stats sheet that records the amount of touchdowns performed by a certain team. I have it working for the first round when it records all 8 teams, however in the semifinals since only 4 teams make it, it does not keep track of what index the winning teams were on and just couts the stats in a regular order from 0 - 4. Ive been thinking for a couple days now on how I could possibly overcome this but I havent been able to find a solution yet.
the stats table that is outputted
Please let me know if i can contribute anymore information to make my question less vague and easier for you to understand. I appreciate all the help, thank you.
Having implemented an algorithm to recommend products with some success, I'm now looking at ways to calculate the initial input data for this algorithm.
My objective is to calculate a score for each product that a user has some sort of history with.
The data I am currently collecting:
User order history
Product pageview history for both anonymous and registered users
All of this data is timestamped.
What I'm looking for
There are a couple of things I'm looking for suggestions on, and ideally this question should be treated more for discussion rather than aiming for a single 'right' answer.
Any additional data I can collect for a user that can directly imply an interest in a product
Algorithms/equations for turning this data into scores for each product
What I'm NOT looking for
Just to avoid this question being derailed with the wrong kind of answers, here is what I'm doing once I have this data for each user:
Generating a number of user clusters (21 at the moment) using the k-means clustering algorithm, using the pearsons coefficient for the distance score
For each user (on demand) calculating their a graph of similar users by looking for their most and least similar users within their cluster, and repeating for an arbitrary depth.
Calculating a score for each product based on the preferences of other users within the user's graph
Sorting the scores to return a list of recommendations
Basically, I'm not looking for ideas on what to do once I have the input data (I may need further help with that later, but it's not the point of this question), just for ideas on how to generate this input data in the first place
Here's a haymaker of a response:
time spent looking at a product
semantic interpretation of comments left about the product
make a discussion page about a product, brand, or product category and semantically interpret the comments
if they Shared a product page (email, del.icio.us, etc.)
browser (mobile might make them spend less time on the page vis-à-vis laptop while indicating great interest) and connection speed (affects amt. of time spent on the page)
facebook profile similarity
heatmap data (e.g. à la kissmetrics)
What kind of products are you selling? That might help us answer you better. (Since this is an old question, I am addressing both #Andrew Ingram and anyone else who has the same question and found this thread through search.)
You can allow users to explicitly state their preferences, the way netflix allows users to assign stars.
You can assign a positive numeric value for all the stuff they bought, since you say you do have their purchase history. Assign zero for stuff they didn't buy
You could do some sort of weighted value for stuff they bought, adjusted for what's popular. (if nearly everybody bought a product, it doesn't tell you much about a person that they also bought it) See "term frequency–inverse document frequency"
You could also assign some lesser numeric value for items that users looked at but did not buy.