I'm designing a Ruby on Rails reservation system for our small tour agency. It needs to accommodate a number of things, and the table structure is becoming quite complex.
Has anyone encountered a similar problem before? What sort of issues might I come up against? And are performance/ validation likely to become issues?
In simple terms, I have a customer table, and a reservations table. When a customer contacts us with an enquiry, a reservation is set up, and related information added (e.g., paid/ invoiced, transport required, hotel required, etc).
So far so good, but this is where is gets complex. Under each reservation, a customer can book different packages (e.g. day trip, long tour, training course). These are sufficiently different, require specific information, and are limited in number, such that I feel they should each have a different model.
Also, a customer may have several people in his party. This would result in links between the customer table and the reservation table, as well as between the customer table and the package tables.
So, if customer A were to make a booking for a long trip for customers A,B and C, and a training course for customer B, it would look something like this.
CUSTOMERS TABLE
CustomerA
CustomerB
CustomerC
CustomerD
CustomerE
etc
RESERVATIONS TABLE
1. CustomerA
LONG TRIP BOOKINGS
CustomerA - Reservation_ID 1
CustomerB - Reservation_ID 1
CustomerC - Reservation_ID 1
TRAINING COURSE BOOKINGS
CustomerB - Reservation_ID 1
This is a very simplified example, and omits some detail. For example, there would be a model containing details of training courses, a model containing details of long trips, a model containing long trip schedules, etc. But this detail shouldn't affect my question.
What I'd like to know is:
1) are there any issues I should be aware of in linking the customer table to the reservations model, as well as to bookings models nested under reservations.
2) is this the best approach if I need to handle information about the reservation itself (including invoicing), as well as about the specific package bookings.
On the one hand this approach seems to be complex, but on the other, simplifying everything into a single package model does not appear to provide enough flexibility.
Please let me know if I haven't explained this issue very clearly, I'm happy to provide more information. Grateful for any ideas, suggestions or comments that would help me think through this rather complex database design.
Many thanks!
I have built a large reservation system for travel operators and wholesalers, and I can tell you that it isn't easy. There seems to be similarity yet still large differences in the kinds of product booked. Also, date-sensitivity is a large difference from other systems.
1) In respect to 'customers' I have typically used different models for representing different concepts. You really have:
a. Person / Company paying for the booking
b. Contact person for emergencies
c. People travelling
a & b seem like the same, but if you have an agent booking, then you might want to separate them.
I typically use a => 'customer' table, then some simple contact-fields for b, and finally for c use a 'passengers' table. These could be setup as different associations to the same model, but I think they are different enough, and I tend to separate them - perhaps use a common address/contact model.
2) I think this is fine, but depends on your needs. If you are building up itineraries for a traveller, then it makes sense to setup 'passengers' on the 'reservation', then for individual itinerary items, with links to which passenger is travelling on/using that item.
This is more complicated, and you must be careful to track dependencies, but the alternative is to not track passenger names, and simply assign quantities to each item (1xAdult, 2xChildren). This later method is great for small bookings, so it seems to depend on if your bookings are simple, or typically built up of longer itineraries.
other) In addition, in respect to different models for different product types, this can work well. However, there tends to be a lot of cross over, so some kind of common 'resource' model might be better -- or some other means of capturing common behaviour.
If I haven't answered your questions, please do ask more specific database design questions, or I can add more detail about specific examples of what I've found works well.
Good luck with the design!
Related
I denormalising a OLTP database for use in a DWH.
At the moment I am denormalising studygroups.
Each studygroup has a key pointing towards 1 project.
Each project has a key pointing towards 1 department.
Each department has a key pointing towards 1 university.
Each universityhas a key pointing to 1 city.
Now I know that you are supposed to denormalize the sh*t out your OLTP but in this dwh department will be a dimension on its own. This goes for university also. Would it suffise to add a key from studygroup pointing at department or is it wiser to denormalize as far as you can and add all attributes from the department and all attributes from its M:1 related tables to the dimension studygroup? Even when department and university will be dimensions by themselves?
In other words: how far/deep do you go when denormalizing?
The key concept behind a dimensional model is:
Keep your fact tables in 3NF (third normal form);
De-normalize your dimensions into 2NF (second normal form)
So ideally, the only joins you should have in your model are the joins between fact tables and relevant dimensions.
As part of this philosophy:
Avoid "snow flake" designs, where dimensions contain keys to other dimensions. It's always possible to come up with a data model that allows the same functionality as the snow flakes, without violating 3NF/2NF rule;
Never have any direct joins between 2 separate dimensions (i.e, department and study group) directly. All relations among dimensions must be resolved via fact tables;
Never have any direct joins between 2 separate fact tables. Any relations among fact tables must be resolved via shared dimensions.
Finally, consider that dimensional design, besides optimization of the data for querying, serves a second important purpose: it's a semantic model of the business (or whatever else it represents). So, when making decisions about combining data elements into dimensions and facts, consider their "logical affinity" - they should make intuitive sense to the end users. If you have hard times explaining to a BI analyst the meaning of your dimension or fact table, most likely you've made a modeling mistake.
For example, in your case you should consider logical relations between universities, departments, study groups, etc. It's very likely that University/Department form a natural hierarchy. If so, they should belong to the same dimension. Study group, on the other hand, might not - let's assume, it's possible to form study groups across multiple universities and/or multiple departments. Such Many:Many relations are clear indication that they should be resolved via fact tables. In addition, relations between universities and departments are stable (rarely change), while study groups are formed and dissolved very often, and thus should be modeled separately.
In general, if you see 1:1 or 1:M relations between dimensional elements, it's often an indication that they should be de-normalized into the same table (again, only if their combination makes logical sense). If the relations are M:M, most likely they belong to different tables (you can force them into the same table, but often such tables look like Frankenstein creatures).
You can get much better help by making your question more specific - draw your dimensional model, post it, and ask for specific issues/challenges you have. For general concepts, books from Kimball and Inmon are your best friends.
I am building a ruby on rails application where a user can learn words from a story (having many stories on his list of stories to learn from), and conversely, a story can belong to many users. Although the story is not owned by the user (it's owned by the author), the user can track certain personal things about each story that relate to him and only to him, such as how many words are left to learn in each of his stories (which will obviously differ from user to user).
Currently, I have a has_many :through relationship set up through a third table called users_stories. My concern/question has to do with "calculated fields": is it really necessary to store things like words_learnt_in_this_story (or conversely, words_not_yet_learnt_in_this_story) in the database? It seems to me that things like this could be calculated by simply looking at a list of all the words that the user has already learnt (present on his learnt_words_list), and then simply contrast/compare that master list with the list of words in the story in order to calculate how many words are unlearnt.
The dilemma here is that if this is the case, if all these fields can simply be calculated, then there seems to be no reason to have a separate model. If this is the case, then there should just be a join model in the middle and have it be a has_and_belongs_to_many relationship, no? Furthermore, in such a scenario, where do calculated attributes such as words_to_learn get stored? Or maybe they don't need to get stored at all, and rather just get calculated on the fly every time the user loads his homepage?
Any thoughts on this would be much appreciated! Thanks, Michael.
If you're asking "is it really necessary to store calculated values in the DB" I answer you. No, it's not necessary.
But it can give you some pros. For example if you have lots of users and the users call those values calculating a lot then it could be more winnable strategy to calculate them once in a while. It will save your server resources.
Your real question now is "What will be more effective for you? Calculate values each time or calculate them once in a while and store in DB?"
In a true relational data model you don't need to store anything that can be calculated from the existing data.
If I understand you correctly you just want to have a master word list (table) and just reference those words in a relation. That is exactly how it should be modelled in a relational database and I suggest you stick with it for consistency reason. Just make sure you set the indices right in the database.
If further down the road you run into performance issue (usually you don't) you can solve that problems then by caching/views etc.
It is not necessary to store calculated values in the DB, but if the values are often used in logic or views its good idea to store it in Database once(calculate again on change) and use from there rather then calculating in views or model.
Suppose I have a user who can take zero or more questionnaires. A questionnaire has zero or more questions, and the user can have one response to each question.
A questionnaire is defined by the application, and where or how is where I am stuck. I can imagine tables such as these:
User (has many UserQuizzes)
UserQuiz (belongs to a QuizTemplate, has many UserQuizQuestionResponses)
UserQuizQuestionResponse (which belongs to a QuizTemplateQuestion)
QuizTemplate (has many QuizTemplateQuestions)
QuizTemplateQuestion (belongs to QuizTemplate)
However, the QuizTemplate and QuizTemplateQuestion data would be infrequently changed. Also, suppose that there are not that many - maybe 5 QuizTemplates with 20 QuizTemplateQuestions each. I think they are more like configuration and fixtures for the application rather than user-specified data. Would it be sensible to build the questions more like "configuration" at the application layer (big hashes? YML?)? Are physical tables the necessarily more robust option?
I'm struggling to understand the best way to model a particular scenario for a data warehouse.
I have a Person dimension, and a Tenancy dimension. A person could be on 0, 1 or (rarely) multiple tenancies at any one time, and will often have a succession of tenancies over time. A tenancy could have one or more people associated with it. The people associated with a tenancy can change over time, and tenancies generally last for many years.
One option is to add tenancy reference, start and end dates to the Person Dimension as type 2 SCD columns. This would work well as long as I ignore the possibility of multiple concurrent tenancies for a person. However, I have other areas of the data warehouse where I am facing a similar design issue and ignoring multiple relationships is not a possibility.
Another option is to model the relationship as an accumulating snapshot fact table. I'm not sure how well this would work in practice though as I could only link it to one version of a Person and Tenancy (both of which will have type 2 SCD columns) and that would seem to make it impossible to produce current or historical reports that link people and tenancies together.
Are there any recommended ways of modelling this type of relationship?
Edit based on the patient answer and comments given by SQL.Injection
I've produced a basic model showing the model as described by SQL.Injection.
I've moved tenancy start/end dates to the 'junk' dimension (Dim.Tenancy) and added Person tenancy start/end dates to the fact table as I felt that was a more accurate way to describe the relationship.
However, now that I see it visually I don't think that this is fundamentally any different from the model that I started with, other than the fact table is a periodic snapshot rather than an accumulating snapshot. It certainly seems to suffer from the same flaw that whenever I update a type 2 slowly changing attribute in any of the dimensions it is not reflected in the fact.
In order to make this work to reflect current changes and also allow historical reporting it seems that I will have to add a row to the fact table every time a SCD2 change occurs on any of the dimensions. Then, in order to prevent over-counting by joining to multiple versions of the same entity I will also need to add new versions of the other related dimensions so that I have new keys to join on.
I need to think about this some more. I'm beginning to think that the database model is right and that it's my understanding of how the model will be used that is wrong.
In the meantime any comments or suggestions are welcome!
Your problem is similar to to the sale transactions with multiple item. The difference, is that a transaction usually has multiple items and your tenancy fact usually has a single person (the tenant).
Your hydra is born because you are trying to model the tenancy as a dimension, when you should be modeling it as a fact.
The reason why I think you have a tenancy dimension, is because somewhere you have a fact rent. To model the fact rent consider use the same approach i stated above, if two persons are tenants of the same property two fact records should be inserted each month:
1) And now comes some magic (that is no magic at all), split the value of the of the rent by the number of tenants and store it the fact
2) store also the full value of the rent (you don't know how the data scientist is going to use the data)
3) check 1) with the business user (i mean people that build the risk models); there might be some advanced rule on how to do the spliting (a similar thing happens when the cost of shipping is to be divided across multiple item lines of the same order -- it might not be uniformly distributed)
I am fairly new to Ruby and Rails, made a few blogs etc. I am slowy learning the ruby language and rails framework. I am wanting to create a workout journal/tracker application and need help establishing the models and or to get me started on the right path. I basically want to be able to create a workout/different types of workouts (back, arms, legs, etc), be able to use the # of sets and reps used for that workout, how many days/which days a week, add, edit, delete the workouts, track weight loss/weight, track the workouts, reps, sets you did prior, set goals in the journal, track progress, eventually be able to share workouts etc. I know what I am looking to do just need help getting started and establishing what models to use and what associations to use. I know it seems like alot of info. Any help getting at all getting going would be awesome. Thanks all!
This might be a bit tricky, since there are many styles of exercises -- N sets of M reps, pyramid, max lifts, etc. You may want polymorphic associations in the final version.
But I think you'll have a more clear vision of where to take the project once you've built a few tables and classes; I think I'd start with a Workout class that has_many WOSets (don't use Set; having class names that conflict with built-in class names is way more irritating than you may think), and each WOSet has_many Reps. Then your Reps will keep track of count and weight. Store the order of the reps in the WOSet.
You'll also need a Station class for all the machines and exercises; probably your WOSet will belongs_to the Station, and the Station will has_many WOSet. (So you can retrieve all the sets ever performed on a specific station.)
I hope this quick sketch gets you to the point of playing with creating new workouts, new stations, and playing with the interface in script/console.
Models = Tables
You should have a look at database design and normalization. Its paramount you get the basics right. Otherwise you might end up with database with common errors like performance issues and redundancy (which is is a bad thing).
One you understand what it is you need to store, mapping it to Rails is easy.
http://en.wikipedia.org/wiki/Database_normalization