I'm developing a simple survey module for an ASP application I'm working on and I'd like to get some suggestions on the data model.
Questions can be one of three types - multiple choice, multiple answer; multiple choice, single answer, and free response.
I'm thinking of the following tables:
Question - with a question type discriminator ifeld
PossibleAnswers- with a questionID and answer text field
SurveyQuestionResponse- with a questionID, a clientID, and answer text
Am I making this too simple?
Take a look at the
Data Model library at databaseanswers.org
Models #76 thru #81 seem pertinent, if only for "inspiration".
A lot depends on the level of sophistication of the surveys you manage, as some surveys in particular dynamic ones (aimed at removing some of the bias) require additional fields for storing properties such as the probabilities with which a particular question (or reply) is used, the many forms of a question and associated probability, and also the recording of the questions and suggested replies that were effectively offered for a give surveyee.
The model the above link:
Related
I am doing an to-B app which I have to meet the different needs of many customers.For example,such as people,one client has two tags, age and position，the other has a tag habits,but I only has a system.
I have tried many methods to solve this question:
Horizontal plus multiple spare fields
EAV model (entity attributes Value)
Stored in json structure
Because I hope that the code is set by the user, I will not use method 1.
As for method 2,I tested a million-level data and the query speed is slow, who can give me a better way to solve this? Or directions can be optimized to make method 2 and method 3 better? which database is good for my question? MySQL, MongoDB or other?
My question is that in a to B project, because each customer's needs are different, multiple custom fields are required. So, how will the database structure be designed and how to make the search
better and faster?
I am currently working on creating a database for a community partnership program for educational purposes. The structure of the DB should be simple be as stated above, the data tends to overlap in various of ways. There are four main categories; Internships, Jobs, Summer/Yearly Programs, and Other. Followed by an Address book/Contacts list.
This is the part where the data is difficult to structure. The employer and has relate to the "employment posting" and doing so relates to the school's academic departments, 6. But some employers require more than one. This data will then be followed by, how many openings?, posting date, follow up contact date, Student hired? if so, student evaluation, and Notes.
I'm not asking how to create the DB, but how would I organize and structure such a complex data collection? I have managed DB's, (putting in information) and I know how to build from scratch as needed. But I have been tasked with structuring somethings like this.
Here is an image of information needed to collect. (More or less)
Click me!
If you are stuck at the "How do I get started?" stage, I suggest that you start at a very high level (the conceptual data model), then refine only a bit to the logical data model, then to physical data model. Here is a short explanation of the 3 different kinds of data model. (Don't worry that it appears to be about data warehouses - these bits aren't specific to data warehouses.)
For a bit more detail, there is another article on data modeling - again, don't worry that it appears in the context of Agile - this is generally useful stuff even if you're not using Agile.
Another two things that might help are these questions (in this order):
What questions do I need the database to answer?
What information does it need to provide a home for? (Why? If it's not covered by part of the answer to the first question, challenge why it's needed.)
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Closed 9 years ago.
I face the following problem.
I'm creating a database for (say) human beings' info. All the human beings may be classified in one of the three categories: adult female, adult male, child. It is clear that the parameters like "height" and "weight" are applicable to all of the categories. The parameter "number of children" is applicable only to adults, while the parameter "number of pregnancies" is applicable to females only. Also, each parameter may be classified as mandatory or optional depending on the category (for example, for adults the parameter "number of ex-partners" is optional).
When I load (say) "height" and "weight", I check whether the info in these two fields is self-consistent. I.e., I mark as a mistake the record which has height=6'4'' and weight=10 lb (obviously, this is physically impossible). I have several similar verification rules.
When I insert a record about a human being, I need to reflect the following characteristics of the info:
the maximum possible info for the category of this particular human being (including all the optional parameters).
the required minimum of information for the category (i.e., mandatory fields only)
what has actually been inserted for this particular human being (i.e., it is possible to insert whatever I have for this person no matter whether it is smaller than the amount of required minimum of info or not). The non-trivial issue here is that a field "XXX" may have NULL value because I have never inserted anything there OR because I have intentionally inserted exactly NULL value. The same logic with the fields that have a default value. So somewhere should be reflected that I have processed this particular field.
what amount of inserted information has been verified (i.e., even if I load some 5 fields, I can check for self-consistency only 3 fields while ignoring the 2 left).
So my question is how to technically organize it. Currently, all these required features are either hardcoded with no unified logic or broken into completely independent blocks. I need to create a unified approach.
I have some naive ideas in my head in this regard. For example, for each category of human beings, I can create and store a list of possible fields (I call it "template"). A can mark those fields that are mandatory.
When I insert a record about a human being, I copy the template and mark what fields from this templates have actually been processed. At the next stage, I can mark in this copy of the template those fields that will be currently verified.
The module of verification is specially corrected in the following way: for each verification procedure I create a list of fields that are being used in this particular verification procedure. Then I call only those verification procedures that have those fields that are actually marked "to be verified" in the copy of the template for the particular human being that is to be verified (see the previous passage).
As you see, this is the most straightforward way to solve this problem. But my guess is that there are a lot of quite standardized approaches that I'm not aware of. I really doubt that I'm the first in the world to solve such a problem. I don't like my solution because it is really painfull to write the code to correctly reflect in this copied template all the "updates" happening with a record.
So, I ask you to share your opinion how would you solve this problem.
I think there are two questions here:
how do I store polymorphic data in a database?
how do I validate complex business rules?
You should address them separately - trying to solve both at once is probably too hard.
There are a few approaches to polymorphic data in RDBMSes - ORMs use the term inheritance mapping, for instance. The three solutions here - table per class hierarchy, table per subclass and table per concrete class - are "pure" relational solutions. You can also use the "Entity-Attribute-Value" design, or use a document approach (storing data in structured formats such as XML or JSON) - these are not "pure" relational options, but have their place.
Validating complex business rules is often done using rule engines - these are super cool bits of technology, but you have to be sure that your problem really fits with their solution - deciding to invest in a rules engine means your project changes into a rules engine project, not a "humans" project. Alternatively, most mainstream solutions to this embody the business logic about the entities in the application's business logic layer. It sounds like you're outgrowing this.
This exact problem, both in health terms and in terms of a financial instrument, is used as a primary example in Martin Fowlers book Analysis Patterns. It is an extensive topic. As #NevilleK says you are trying to deal with two questions, and it is best to deal with them separately. One ultra simplified way of approaching these problems is:
1 Storage of polymorphic data - only put mandatory data that is common to the category in the category table. For optional data put these in a separate table in 1-1 relationship to the category table. Entries are made in these optional tables only if there is a value to be recorded. The record of the verification of the data can also be put in these additional tables.
2 Validate complex business rules - it is useful to consider the types of error that can arise. There are a number of ways of classifying the errors but the one I have found most useful is (a) type errors where one can tell that the value is in error just by looking at the data - eg 1980-02-30. (b) context errors where one can detect the error only by reference to previously captured date - eg DoB 1995-03-15, date of marriage 1996-08-26. and (c) lies to the system - where the data type is ok; the context is ok; but the information can only be detected as incorrect at a later date when more information comes to light eg if I register my DoB as 1990-12-31, when it is something different. This latter class of error typically has to be dealt with by procedures outside the system being developed.
I would use the Party Role pattern (Silverston):
Party
id
name
Individual : Party
current_weight
current_height
PartyRole
id
party_id
from_date
to_date (nullable)
AdultRole : PartyRole
number_of_children
FemaleAdultRole : AdultRole
number_of_pregnancies
Postgres has a temporal extension such that you could enforce that a party could only play one role at a time (yet maintain their role histories).
Use table inheritance. For simplicity use Single Table Inheritance (has nulls), for no nulls use Class Table Inheritance.
Hi I am trying to design a database for an e-commerce website but I can't seem to find a way to do this right, this is what I have so far:
The problem appears at the products.I have 66 types of products most of them having different fields.I have to id's but both of them don't seem very practical:
OPTION A:
At first I thought I to make a table for each product type, but that would result in 66 tables which is not very easy to maintain. I already started to do that I created the Product_Notebook and Product_NotebookBag tables. And then I stopped and thought about it a bit and this solution is not very good.
OPTION B
After thinking about it a bit more I came up with option B which is storing the data into a separate field called description. For example:
"Color : Red & Compatibility : 15.6 & CPU : Intel"
In this approach I could take the string and manipulate it after retrieving it from the database.
I know this approach is also not a very good idea, that's why I am asking for a more practical approach.
See my answer to this question here on Stack Overflow. For your situation I recommend using Entity Attribute Value (EAV).
As I explain in the linked answer, EAV is to be avoided almost all of the time for many good reasons. However, tracking product attributes for an online catalog is one application where the problems with EAV are minimal and the benefits are extensive.
Simply create a ProductProperties table and put all the possible fields there. (You can actually just add more fields to your Products table)
Then, when you list your products, just use the fields you need.
Surely, there are many fields in common as well.
By the way, if you're thinking of storing the data in array (option B?) you'll regret it later. You won't be able to easily sort your table that way.
Also, that option will make it hard to find a particular item by a specific characteristic.
I am planning to make Q&A system (quite specific, has nothing to do with IT)
I was looking for Stackoverflow database map: https://meta.stackexchange.com/questions/2677/anatomy-of-a-data-dump/2678#2678
And I am thinking is not it is better practice to make separate table for questions titles. With "firstPostId".
Instead of
|- PostTypeId
| - 1: Question
| - 2: Answer
So I want to know, why stackoverflow did not use separate table for questions title. Is it "Do not optimize yet" or does it have any logic behind it?
Based just on the schema as shown in your link, I surmise that Questions and Answers have so many attributes in common that it was convenient to model it as was done. In short, symmetry and failing to multiply entities unnecessarily seem credible reasons for the approach.
I also suspect they use a key/value (a.k.a. nosql) database for the backing store which allows entries to not possess all possible attributes. For example, a question can have tags but an answer will not. Key/value databases don't fret over differences like that.
Disclaimer: I have no actual knowledge of how SO is implemented.