When creating content for your website, it's best to be careful about where you get your content from, whether it's from a freelancer or from another website. You do not want to get on the wrong side of the law or get on someone's bad books when it comes to their copyrighted work.

Unless you take articles from article directories, you must contact the author and ask for their permission. There is no way around that. Sure, the author would like to receive the free publicity, but it's best to let him or her know before you use their work. It's common courtesy.

I'm a heavy article author and marketer, so I know the tricks people pull to get articles on their websites. Some will include links which don't work, don't include the resource box, or just plain spin my articles into their own by changing the title and leaving everything else the same. I usually don' take much action unless it's a major case, because I've got better things to do with my time, like marketing my business and serving my customers, but others might do things differently. They'll certainly take action if they feel it warrants it.

I can tell you from personal experience; trust is low on the Internet and people are willing to take legal action (my freelancer is doing that just now to someone else who copied her work). So it's best to stay on the safe side and play by the rules. Don't ever plagiarize someone else's work and you'll avoid any copyright issues!

A part of web development is copywriting. Excellent copy means it has to be appealing to both readers and to search engines. This combination will help websites to rank highly. A problem occurs when there are space constraints to a site, page layout requirements or other issues.

Because appealing to both readers and search engines is so important, you don't want to sacrifice one for the other. Adding a big block of copy to the middle of a page may not be the best answer, however, if a page needs content, adding a couple of sentences to the bottom of each section is a good option. Your copy will still be readable and the additional content will appeal to the search engines.

There are some things to remember when writing content for a website.

• Web users are active. One click and they have left your site. If they don't see a reason to stay, they won't. There is a 10 - 15 second window available to capture a visitor's attention.
• The longer the text is, the less likely they are to read it. With long text, they will skim it, if they bother to read it at all.
• Web users don't believe in hype. If you want a web user to believe you and to believe in you, you must back up your claims.

Four questions must be answered on each page:

• What am I doing here?
• How do I do it?
• What's in it for me?
• Where can I go, next?

If your design and navigation isn't obvious, then you need to explain it in the copy. Most visitors will not take the time to figure this information out. If a first time visitor cannot find their way around your site, they will likely never come back.

Unless your visitors are expecting to read something on your page, don't expect that they will read more than one or two lines of copy.

Understanding your copy is as important as length. Don't make the copy so complicated that it is difficult to comprehend or make it so the customer will have to think about it because they won't.

What this means is you want to convey one key idea in just one or two lines. Don't try to add a third line because if you say too much, then even the first idea won't penetrate. If your site needs more content, break it down into sections that are one or two paragraphs each. Say what you want to say in the first sentence and then expand the thought into the paragraph. Use meaningful headers. Most people will only scan the headers to the paragraphs and not even bother with the copy on the page, unless it is something that appeal to them. It is better to write only one or two lines with links to another page with the longer copy.

Even when users are expecting to find text heavy content, don't expect they will take the time to read all of it. Longer copy doesn't have to be as abrupt as shorter text, but it needs to be as easy to read.

Make your copy clear, but not boring. Lively writing with an unassuming voice is best. Boring writing will turn your reader off and nothing you say at that point will make it through.

Don't be fooled by seeming simplicity. A lot of developers get comfortable with a certain way of designing a database for their web applications that they miss out on techniques they should rather employ to make things run faster and more efficiently. A lot of developers don't bear in mnd that the small site they are creating now might grow into something incredibly large and complex, and the database they designed has become bloated and doesn't scale well to meet the demands of the increased traffic.

This article hopes to provide web developers with a few techniques to help make their database and queries faster and more efficient.

1. Avoid Character Types

When you are designing a database, it is so easy to set all data types to the VARCHAR type as it can then contain any data you want; numbers or text. But character data is amongst the most inefficient data type you can get. If a field is only going to contain numbers, then make it one of the appropriate types (INT, DOUBLE, etc).

Also, wherever possible in your web development code, try to use numeric data types as opposed to characters. One of the most common things a script has to store are flags like whether someone answered yes or no to a question, etc. You could of course store it as 'Y' or 'N' but why not store it as 0 and 1?

The reason this makes a difference is when you have a database, for example, with over 500 000 entries, and are running a SELECT on that field, comparisons are processed a lot faster for numeric data types than character types. Also, if you need to return data to the calling script, numeric data is less memory intensive than character data. In addition, your web development language (PHP, ASP, etc) would also be able to process and perform functions on numeric data better than character data.

I am not trying to convince you never to use character data types. Sometimes it is a necessity, but if you can find ways to reduce the amount of character data processed by your SQL database, the better your server will cope.

2. Normalization

Normalizing a database is really quite a complex process. It is a process that describes a way to design a database structure to avoid repetition of data in your database and can lead to significant performance benefits if employed correctly. However, the entire process of normalisation is a bit beyond the scope of this article as it can fill books on its own, but any developer designing a database should seriously consider becoming knowledgable about normalisation and employing it in their own designs.

For a good tutorial on this process: http://www.keithjbrown.co.uk/vworks/mysql/mysql_p7.php

3. DateTime vs Timestamp fields

This actually relates to 1. a bit. The big difference to bear in mind here is that a field of type DATETIME is actually stored as a series of characters. A field of type TIMESTAMP is actually stored as an integer. So therefore, a more efficient way of storing dates is using the timestamp method. The timestamp has its drawbacks however. For one, you cannot store a date early than 1 January, 1970. Also, timestamps in your script will need recalculating to get to the character format. Because of this recalculation, it may not be better to store as timestamp. It really is a case of testing which format works better for your needs.

4. Use LIMIT where possible

In your queries, if you are doing a SELECT to a database and you only expect a certain number of results, using the LIMIT statement can speed your query up incredibly.

For example, if you have a table of users and you need to run a query to search for one users record, you can use a query like:

SELECT user_name FROM users WHERE user_id = 453;

This query is perfectly valid and will return the right result. But you also know there will only be ONE result. The query above will search the database, find what you want, but then still continue searching after that. It would run a lot faster if you could tell the query that once it has found what you are looking for to stop searching. LIMIT can do this, as this query shows:

SELECT user_name FROM users WHERE user_id = 453 LIMIT 1;

Imagine this scenario. You have a table called logins, that records every login from a user. It currently contains over 2 000 000 records, and you want to find the first time a user logged in. Now bear in mind that because this table inserts data over time, it is already sorted for by date. You could do the following query:

SELECT MIN(login_date) FROM logins WHERE user_id = 4876;

This will return the record you want, but SQL will now have to get all dates for that user, sort them and then return the lowest value to you. Our table is already date sorted simply because of the way it records data for us. So using LIMIT can be more effective:

SELECT login_date FROM logins WHERE user_id = 4876 LIMIT 1;

Because it is sorted, the first one will always be a users first login.

5. Avoid using LIKE

If you have tried to employ 1. above, then hopefully you will be in a scenario where you do not need to use LIKE all that much. LIKE is one of the most inefficient ways of searching a table. LIKE performs a text comparison search in a field and with no wildcards is as efficient as a direct comparison; i.e. WHERE name = 'Jane' is equivalent to WHERE name LIKE 'Jane'. It is when you start introducing the wildcard characters like '%' that things get really hairy.

If you do have to use LIKE, then at least try and make efficient use of the wildcards. These are '_' (underscore) and '%'. Let me explain all this with a real world example.

In a project I was involved in, we had a SQL database storing logs generated automatically from a mail server. Unfortunately, the mail server pretty much just dumped a very long string of text data into a field that contained the data we wanted. A script had to be written to find all logs that referred to a login by a user into the POP server. The only way we could do this was to search every record for a string in the msg field that had the text "User logged in" in it. The first query developed was something like this:

SELECT msg FROM logs WHERE msg LIKE '%User logged in%';

This query took on average of about 35 minutes to process. Obviously not an ideal situation. The way the LIKE worked here was that it had to parse through every single portion of each and every record in the msg field looking for text that matched "User logged in" anywhere in the text. We were able to determine eventually that the text "User logged in" occured at the end of that text in the msg field and so we altered the query:

SELECT msg FROM logs WHERE msg LIKE '%User logged in';

The '%' at the end was removed as we do not want to worry about text after because there is none. The query now only compares text to our string in the msg field at the end of the field and no longer parses through the entire piece of text stored in msg. The query now ran in under 2 minutes. (This was actually still too long, but how we optimised from there is a little beyond the scope of this article.)

Hopefully with all these elements put into practice on your next web development project, you can have a database that runs quickly, efficiently, uses as little resources as possible and wont grind to a halt when the load suddenly increases.