I am working in a small law firm and my boss has asked me to put a database together to help with outgoing mail. There are 5 different tables that exist in Access. (Applicants, Attorneys, Lien Claimants, Employers and Workers Compensation Boards) All of the tables include addresses only. Each Applicant has an attorney, one or possibly more lien claimants, employer and designated board. I need to create some type of database that will allow me to create a mail merge for all applicants. Keep in mind each applicant has different addresses, employers, etc..(There are roughly 500 applicants) I need to create the database so when I change/update an address on the table in Access it will change ALL of the applicant(s) it pertains to. Tryin to only update a new address in one place instead of 50. If anyone can help please let me know. I am looking for the most efficient and effective way of doing this.
Store the address in one table and then have a join to the other tables so when you update the address it is reflected in all the other places where it is used.
Have a table "addresses" that has an ID in it.
Have the "applicants" table have an ID in it that refers to the ID in the "addresses" table.
Hopefully this is making sense to you. If not add to the comments and I will try to explain in more
detail.
Just to give you some ideas on setting up a database, here is a library of free database models that cover everything from access control to zoo's.
One of the models is for Lawyers, Cases and Bills, while another is for Case Management. All of these examples give you the fields and relationships. Look over these examples and you should be able to see some ideas of how to setup your tables and relationships to solve your problem.
Good luck and hope this helps some.
Related
I am working on a data warehouse solution, and I am trying to build a dimensional model from tables held in a SQL Server database. Some of the tables include but aren't limited to Customer, Customer Payments, Customer Address, etc.
All these tables in the DB have some fields that are repeated multiple times across each table i.e. Record update date, record creatuin date, active flag, closed flag and a few others. These tables all relate to the Customer in some way, but the tables can be updated independently.
I am in the process of building out a dimension(s) on the back of these tables, but I am struggling to see how best to deal with these repeated fields in an elegant way, as they are all used.
I'll appreciate any guidance from people who have experience with scenarios like this, as I ammjust starting out
If more details are needed, I am happy to provide
Thanks
Before you even consider how to include them, ask if those metadata fields even need to be in your dimensional model? If no one will use the Customer Payment Update Date (vs Created Date or Payment Date), don't bring it into your model. If the customer model includes the current address, you won't need the CustomerAddress.Active flag included as well. You don't need every OLTP field in your model.
Make notes about how you talk about the fields in conversation. How do you identify the current customer address? Check the CurrentAddress flag (CustomerAddress.IsActive). When was the Customer's payment? Check the Customer Payment Date (CustomerPayment.PaymentDate or possibly CustomerPayment.CreatedDate). Try to describe them in common language terms. This will provide the best success in making your model discoverable by your users and intuitive to use.
Naming the columns in the model and source as similar as possible will also help with maintenance and troubleshooting.
Also, make sure you delineate the entities properly. A customer payment would likely be in a separate dimension from the customer. The current address may be in customer, but if there is any value to historical address details, it may make sense to put it into its own dimension, with the Active flag as well.
I would be grateful if someone wrote how I should look for databases normalization errors in databases AND in entity classes in any language.
I just would like to know what is the most important and where should I look for possible errors in classes - in DAOs, BEANS or wherever. What should I take into account - any conventions, schemes etc?
For any answer, thanks in advance! :)
I guess you've read something about the normal forms, e.g. on wikipedia. Then I guess you know something, but you are not sure why should you do that or what is really important.
For example, if you have a table that contains relations between persons, it should not contain names, just IDs. If you have e.g. a table of patients where there are columns father_name and mother_name, it's an example of non-normalized table causing troubles.
Let's say the mother changes her name - from this moment on, your database is in inconsistent state. You decide to add some cascade/trigger on this change and you get into even worse problem: You realize several people can have the same name.
That is basically the main reason for using IDs as keys, not some column that is not a unique identifier. There is much more to learn, I hope someone provides you a link to some tutorial, as this is not really Q/A stuff.
Another good reason for normalizing a table are sparse tables - tables where some columns rarely contain anything else than null. E.g., there are four types of some device, each has different properties that are left null on the other types. In this case, creating a table that holds the specific properties of each device type (even though it's just {0,1}:1 relation) is advisable.
I am currently refactoring a web-app. Right now there is a 'Contact' table that has a one-to-one correspondence with the main 'Client' table, with a bool indicating if clients want to receive mail. The mail-list is accessed about once per month, and the clients' profile page is accessed many times a day. I am thinking if it would be 'cleaner' to make a new table with the client ids of everyone in the mail-list, as querying if the key is in the table should take about the same time as accessing the information. Should I do that, or should I leave it as it is?
Thanks,
Joyce
Leave it as is. Why complicate? Keep it as simple as possible.
An association table with (clientid, emailid) is too much normalized form. I think its better to keep like this. Also if you want to show contact emailid in any ui screen, you can avoid an inner join overhead due to this new association table.
However in future if you came across a requirement to have multiple emailids associated with a clientid, you could think about creating an association table then.
Full disclosure...Trying feverishly here to learn more about databases so I am putting in the time and also tried to get this answer from the source to no avail.
Barry Williams from databaseanswers has this schema posted.
Clients and Fees Schema
I am trying to understand the split of address tables in this schema. Its clear to me that the Addresses table contains the details of a given address. The Client_Addresses and Staff_Addresses tables are what gets me.
1) I understand the use of Primary Foreign Keys as shown but I was under the assumption that when these are used you don't have a resident Primary Key in that same table (date_address_from in this case). Can someone explain the reasoning for both and put it into words how this actually works out?
2) Why would you use date_address_from as the primary key instead of something like client_address_id as the PK? What if someone enters two addresses in one day would there be conflicts in his design? If so or if not, what?
3) Along the lines of normalization...Since both date_address_from and date_address_to are the same in the Client_Addresses and Staff_Addresses table should those fields just not be included in the main Address table?
Evaluation
First an Audit, then the specific answers.
This is not a Data Model. This is not a Database. It is a bucket of fish, with each fish drawn as a rectangle, and where the fins of one fish are caught in the the gills of another, there is a line. There are masses of duplication, as well as masses of missing elements. It is completely unworthy of using as an example to learn anything about database design from.
There is no Normalisation at all; the files are very incomplete (see Mike's answer, there are a hundred more problem like that). The other_details and eg.s crack me up. Each element needs to be identified and stored: StreetNo, ApartmentNo, StreetName, StreetType, etc. not line_1_number_street, which is a group.
Customer and Staff should be normalised into a Person table, with all the elements identified.
And yes, if Customer can be either a Person or an Organisation, then a supertype-subtype structure is required to support that correctly.
So what this really is, the technically accurate terms, is a bunch of flat files, with descriptions for groups of fields. Light years distant from a database or a relational one. Not ready for evaluation or inspection, let alone building something with. In a Relational Data Model, that would be approximately 35 normalised tables, with no duplicated columns.
Barry has (wait for it) over 500 "schemas" on the web. The moment you try to use a second "schema", you will find that (a) they are completely different in terms of use and purpose (b) there is no commonality between them (c) let's say there was a customer file in both; they would be different forms of customer files.
He needs to Normalise the entire single "schema" first,
then present the single normlaised data model in 500 sections or subject areas.
I have written to him about it. No response.
It is important to note also, that he has used some unrecognisable diagramming convention. The problem with these nice interesting pictures is that they convey some things but they do not convey the important things about a database or a design. It is no surprise that a learner is confused; it is not clear to experienced database professionals. There is a reason why there is a standard for modelling Relational databases, and for the notation in Data Models: they convey all the details and subtleties of the design.
There is a lot that Barry has not read about yet: naming conventions; relations; cardinality; etc, too many to list.
The web is full of rubbish, anyone can "publish". There are millions of good- and bad-looking "designs" out there, that are not worth looking at. Or worse, if you look, you will learn completely incorrect methods of "design". In terms of learning about databases and database design, you are best advised to find someone qualified, with demonstrated capability, and learn from them.
Answer
He is using composite keys without spelling it out. The PK for client_addresses is client_id, address_id, date_address_from). That is not a bad key, evidently he expects to record addresses forever.
The notion of keeping addresses in a separate file is a good one, but he has not provided any of the fields required to store normalised addresses, so the "schema" will end up with complete duplication of addresses; in which case, he could remove addresses, and put the lines back in the client and staff files, along with their other_details, and remove three files that serve absolutely no purpose other than occupying disk space.
You are thinking about Associative Tables, which resolve the many-to-many relations in Databases. Yes, there, the columns are only the PKs of the two parent tables. These are not Associative Tables or files; they contain data fields.
It is not the PK, it is the third element of the PK.
The notion of a person being registered at more than one address in a single day is not reasonable; just count the one address they slept the most at.
Others have answered that.
Do not expect to identify any evidence of databases or design or Normalisation in this diagram.
1) In each of those tables the primary key is a compound key consisting of three attributes: (staff_id, address_id, date_address_from) and (client_id, address_id, date_address_from). This presumably means that the mapping of clients/staff to addresses is expected to change over time and that the history of those changes is preserved.
2) There's no obvious reason to create a new "id" attribute in those tables. The compound key does the job adequately. Why would you want to create the same address twice for the same client on the same date? If you did then that might be a reason to modify the design but that seems like an unlikely requirement.
3) No. The apparent purpose is that they are the applicable dates for the mapping of address to client/staff - not dates applicable to the address alone.
3) Along the lines of
normalization...Since both
date_address_from and date_address_to
are the same in the Client_Addresses
and Staff_Addresses table should those
fields just not be included in the
main Address table?
No. But you did find a problem.
The designer has decided that clients and staff are two utterly different things. By "utterly different", I mean they have no attributes in common.
That's not true, is it? Both clients and staff have addresses. I'm sure most of them have telephones, too.
Imagine that someone on staff is also a client. How many places is that person's name stored? That person's address? Can you hear Mr. Rogers in the background saying, "Can you spell 'update anomaly'? . . . I knew you could."
The problem is that the designer was thinking of clients and staff as different kinds of people. They're not. "Client" describes a business relationship between a service provider (usually, that is, not a retailer) and a customer, which might be either a person or a company. "Staff" describes a employment relationship between a company and a person. Not different kinds of people--different kinds of relationships.
Can you see how to fix that?
This 2 extra tables enables you to have address history per one person.
You can have them both in one table, but since staff and client are separated, it is better to separate them as well (b/c client id =1 and staff id =1 can't be used on the same table of address).
there is no "single" solution to a design problem, you can use 1 person table and then add a column to different between staff and client. BUT The major Idea is that the DB should be clear, readable and efficient, and not to save tables.
about 2 - the pk is combined, both clientID, AddressID and from.
so if someone lives 6 month in the states, then 6 month in Israel, and then back to the states, to the same address - you need only 2 address in address table, and 3 in the client_address.
The idea of heaving the from_Date as part of the key is right, although it doesn't guaranty data integrity - as you also need manually to check that there isn't overlapping dates between records of the same person.
about 3 - no (look at 2).
Viewing the data model, i think:
1) PF means that the field is both part of the primary key of the table and foreign key with other table.
2) In the same way, the primary key of Staff_Addresses is {staff_id,address_id,date_adderess_from} not just date_adderess_from
3) The same that 2)
In reference to Staff_Addresses table, the Primary Key on date_address_from basically prevents a record with the same staff_id/address_id entered more than once. Now, i'm no DBA, but i like my PKs to be integers or guids for performance reasons/faster indexing. If i were to do this i would make a new column, say, Staff_Address_Id and make it the PK column and put a unique constraint on staff_id/address_id/date_address_from.
As for your last concern, Addresses table is really a generic address storage structure. It shouldn't care about date ranges during which someone resided there. It's better to be left to specific implementations of an address such as Client/Staff addresses.
Hope this helps a little.
I am currently in the process of looking at a restructure our contact management database and I wanted to hear peoples opinions on solving the problem of a number of contact types having shared attributes.
Basically we have 6 contact types which include Person, Company and Position # Company.
In the current structure all of these have an address however in the address table you must store their type in order to join to the contact.
This consistent requirement to join on contact type gets frustrating after a while.
Today I stumbled across a post discussing "Table Inheritance" (http://www.sqlteam.com/article/implementing-table-inheritance-in-sql-server).
Basically you have a parent table and a number of sub tables (in this case each contact type). From there you enforce integrity so that a sub table must have a master equivalent where it's type is defined.
The way I see it, by this method I would no longer need to store the type in tables like address, as the id is unique across all types.
I just wanted to know if anybody had any feelings on this method, whether it is a good way to go, or perhaps alternatives?
I'm using SQL Server 05 & 08 should that make any difference.
Thanks
Ed
I designed a database just like the link you provided suggests. The case was to store the data for many different technical reports. The number of report types is undefined and will probably grow to about 40 different types.
I created one master report table, that has an autoincrement primary key. That table contains all common information like customer, testsite, equipmentid, date etc.
Then I have one table for each report type that contains the spesific information relating to that report type. That table have the same primary key as the master and references the master as well.
My idea for splitting this into different tables with a 1:1 relation (which normally would be a no-no) was to avoid getting one single table with a huge number of columns, that gets very difficult to maintain as your constantly adding columns.
My design with table inheritance gave me segmented data and expandability without beeing difficult to maintain. The only thing I had to do was to write special a special save method to handle writing to two tables automatically. So far I'm very happy with the design and haven't really found any drawbacks, except for a little more complicated save method.
Google on "gen-spec relational modeling". You'll find a lot of articles discussing exactly this pattern. Some of them focus on table design, while others focus on an object oriented approach.
Table inheritance pops up in a few of them.
I know this won't help much now, but initially it may have been better to have an Entity table rather than 6 different contact types. Then each Entity could have as many addresses as necessary and there would be no need for type in the join.
You'll still have the problem that if you want the sub-type fields and you have only the master contact, you'll have to know what table to go looking at - or else join to all of them. But otherwise this is a workable solution to a common problem.
Another possibility (fairly similar in structure, but different in how you think of it) is to simply put all your contacts into one table. Then for the more specific fields (birthday say for people and department for position#company) create separate tables that are associated with that contact.
Contact Table
--------------
Name
Phone Number
Address Table
-------------
Street / state, etc
ContactId
ContactBirthday Table
--------------
Birthday
ContactId
Departments Table
-----------------
Department
ContactId
It requires a different way of thinking of things though - instead of thinking of people vs. companies, you think of the various functional requirements for the task at hand - if you want to send out birthday cards, get all the contacts that have birthdays associated with them, etc..
I'm going to go out on a limb here and suggest you should rethink your normalization strategy (as you seem to be lucky enough to be able to rethink your schema quite fundamentally). If you typically store an address for each contact, then your contact table should have the address fields in it. Alternatively if the address is stored per company then the address should be stored in the company table and your contacts linked to that company.
If your contacts only have one address, or one (or even 3, just not 'many') instance of the other fields, think about rationalizing them into a single table. In my experience having a few null fields is a far better alternative than needing left joins to data you aren't sure exists.
Fortunately for anyone who vehemently disagrees with me you did ask for opinions! :) IMHO you should only normalize when you really need to. Where you are rethinking schemas, denormalization should be considered at every opportunity.
When you have a 7th type, you'll have to create another table.
I'm going to try this approach. Yes, you have to create new tables when you have a new type, but since this table will probably have different columns, you'll end up doing this anyway if you don't use this scheme.
If the tables that inherit the master don't differentiate much from one another, I'd recommend you try another approach.
May I suggest that we just add a Type table. Ie a person has an address, name etc then the student, teacher as each use case presents its self we have a PersonType table that has an entry from the person table to n types and the subsequent new tables teacher, alien, singer as the system eveolves...