After a watching a few videos regarding DynamoDB and its best practices, I decided to give it a try; however, I cannot help but feel what I'm doing may be an anti-pattern. As I understand it, the best practice is to leverage as few tables as possible while also taking advantage of GSIs to do some 'heavy' lifting. Unfortunately, I'm working with a use case that doesn't actually have strictly defined access patterns yet since we're still in early development.
Some early access patterns that we may see are:
Retrieve the number of wins for a particular game: rock paper scissors, boxing, etc. [1 quick lookup]
Retrieve the amount of coins a user has. [1 quick lookup]
Retrieve all the items that someone has purchased (don't care about date). [Not sure?]
Possibly retrieve all the attributes associated with a user (rps wins, box wins, coins, etc). [I genuinely don't know.]
Additionally, there may be 2 operations we will need to complete. For example, if the user wins a particular game they may receive "coins". Effectively, we'll need to add coins to the user "coins" attribute & update their number of wins for the game.
Do you think I should revisit this strategy? Additionally, we'll probably start creating 'logs' associated with various games and each individual play.
Designing a DynamoDB data model without fully understanding your applications access patterns is the anti-pattern.
Take the time to define your entities (Users, Games, Orders, etc), their relationship to one another and your applications key access patterns. This can be hard work when you are just getting started, but it's absolutely critical to do this when working with DynamoDB. How else can we (or you, or anybody) evaluate whether or not you're using DDB correctly?
When I first worked with DDB, I approached the process in a similar way you are describing. I was used to working with SQL databases, where I could define a few tables and rely on the magic of SQL to support my access patterns as my understanding of the application access patterns evolved. I quickly realized this was not going to work if I wanted to use DynamoDB!
Instead, I started from the front-end of my application. I sketched out the different pages in my app and nailed down the most important concepts in my application. Granted, I may not have covered all the access patterns in my application, but the exercise certainly nailed down the minimal access patterns I'd need to have a usable app.
If you need to rapidly prototype your application to get a better understanding of your acecss patterns, consider using the skills you and your team already have. If you already understand data modeling with SQL databses, go with that for now. You can always revisit DynamoDB once you have a better understanding of your access patterns and determine that your application can benefit from using a NoSQL databse.
Related
I am looking for some light in the complexity of architectural selection, before starting the development of a CMS or CRM or ERP.
I was able to find this similar question: A CRM architecture (open source app)
But it seems old enough.
I watch and read recently several conferences, discussions about monolith vs distrubuted, DDD philosophy, CQRS and event driven design, etc.
And I panic even more than before on the architectural choice, having taken into account the flaws of each (I think).
What I find unfortunate with all the examples of microservices and distributed systems that can be found easily on the net is that they always take e-commerce as an example (Customers, Orders, Products ...). And for this kind of example, several databases (in general, a NoSQL DB by microservice) exist.
I see the advantage (more or less) ==> to keep a minimalist representation of the necessary data for each context.
But how to go for a unique and relational database? I really think I need a single relational database, having worked in a company producing a CRM (without access to the source code of the machine, but the structure of the database), I could see the importance of relational: necessary for listings, reports, and consult the links between entities within the CRM (a contact can have several companies and conversely, each user has several actions, tasks, but each of his tasks can also be assigned to other users, or even be linked to other items such as: "contact", "company", "publication", "calendarDate", etc. And there can be a lot of records in each table (+ 100,000 rows), so the choice of indexes will be quite important, and transactions are omni-present because there will be a lot of concurrent access to data records).
What I'm saying to myself is that if I choose to use a microservice system, there will be a lot of microservices to do because there would really be a lot of different contexts, and a high probability of having a bunch of different domain models. And then I will end up having the impression of having to light each small bulb of a garland, with perhaps too much process running simultaneously.
To try to be precise and not go in all directions, I have 2 questions to ask:
Can we easily mix the DDD philosophy with a monolith system, while uncoupling very small quantity (for the eventual services that should absolutely be set apart, for various reasons)?
If so, could I ask for resources where I can learn a lot more about this?
Do we necessarily have to work with a multitude of databases, and should it necessarily be of the kind mongoDb, nosql?
I can imagine that the answer is no, but could I ask to elaborate a little more? Or redirect me to articles that will give me clear enough answers?
Thank you in advance !
(It would be .NET Core, draft is here: https://github.com/Jin-K/simple-cms)
DDD works perfectly as an approach in designing your CRM. I used it in my last project (a web-based CRM) and it was exactly what I needed. As a matter of fact, if I wouldn't have used DDD then it would have been impossible to manage. The CRM that I created (the only architect and developer) was very complex and very custom. It integrates with many external systems (i.e. with email server and phone calls system).
The first thing you should do is to discover the main parts of your system. This is the hardest part and you probably get them wrong the first time. The good thing is that this is an iterative process that should stabilize before it gets to production because then it is harder to refactor (i.e. you need to migrate data and this is painful). These main parts are called Bounded contexts (BC) in DDD.
For each BC I created a module. I didn't need microservices, a modular monolith was just perfect. I used the Conway's Law to discover the BCs. I noticed that every department had common but also different needs from the CRM.
There were some generic BCs that were common to each department, like email receiving/sending, customer activity recording, task scheduling, notifications. The behavior was almost the same for all departments.
The department specific BCs had very different behaviour for similar concepts. For example, the Sales department and Data processing department had different requirements for a Contract so I created two Aggregates named Contract that shared the same ID but they had other data+behavior. To keep them "synchronized" I used a Saga/Process manager. For example, when a Contract was activated (manually or after the first payment) then a DataProcessingDocument was created, containing data based on the contract's content.
Another important point of view is to discover and respect the sources of truth. For example, the source of truth for the received emails is the Email Server. The CRM should reflect this in its UI, it should be very clear that it is only a delayed reflection of what is happening on the Email Server; there may be received emails that are not shown in the CRM for technical reasons.
The source of truth for the draft emails is the CRM, with it's Email composer module. If a Draft is not shown anymore then it means that it has been deleted by a CRM user.
When the CRM is not the source of truth then the code should have little or no behavior and the data should be mostly immutable. Here you could have CRUD, unless you have performance problems (i.e. millions of entries) in which case you could use CQRS.
And there can be a lot of records in each table (+ 100,000 rows), so the choice of indexes will be quite important, and transactions are omni-present because there will be a lot of concurrent access to data records).
CQRS helped my a lot to have a performant+responsive system. You don't have to use it for each module, just where you have a lot of data and/or different behavior for write and read. For example, for the recording of the activity with the customers, I used CQRS to have performant listings (so I used CQRS for performance reasons).
I also used CQRS where I had a lot of different views/projections/interpretations of the same events.
Do we necessarily have to work with a multitude of databases, and should it necessarily be of the kind mongoDb, nosql? I can imagine that the answer is no, but could I ask to elaborate a little more? Or redirect me to articles that will give me clear enough answer
Of course not. Use whatever works. I used MongoDB in 95% of cases and Mysql only for the Search module. It was easier to manage only a database system and the performance/scalability/availability was good enough.
I hope these thoughts help you. Good luck!
Hi I am building a small app to get used to Meteor (and Mongo). Something that is bothering me is the data modelling aspect. Specifically what is the best way to model a many to many relationship. I have read in the Mongo docs that a doc should not be embedded in another doc if you expect it to grow while the original doc remains fairly static.
In my test app students can register for courses. So from the Mongo perspective it makes sense to include the students as an embedded doc in the course as each course will have a limited number of students as opposed to the other way round where, over time, a student could theoretically join unlimited courses.
Then there is the Meteor aspect, I read that a lot of Meteor's features are aimed at separate collections, such as DDP working at the document level so any change in the student array would cause the entire course doc to be resent to every browser, and things like the each spacebars helper works with Mongo cursors but not with arrays etc, etc.
Has anyone dealt with a similar situation and could they explain what approach they took and any drawbacks they had to deal with etc? Thanks.
See this article: https://www.discovermeteor.com/blog/reactive-joins-in-meteor/
And test how good your possible solutions are with this https://kadira.io/
Better use the guide:
http://guide.meteor.com/data-loading.html#publishing-relations
The Meteor team tames (or hides!) the javascript monster to an amazing extent. By using their conventions, you get "free" a ton of much-used functionality "out of the box". Things that are usually re-invented over and over again, accounts, OAuth, live data across clients, standard live-data protocol etc.
But very soon... you need features not in the box. Wow... look at all the choices. Wait a minute, this is the same monster you were fighting before Meteor!
So use the official Meteor Guide. They recommend the wisest ways to extend functionality of your app when you make these choices.
Since they know how they have "hidden the monster", they know how to keep avoiding the monster when you extend.
I have what I consider to be a fairly simple application. A service returns some data based on another piece of data. A simple example, given a state name, the service returns the capital city.
All the data resides in a SQL Server 2008 database. The majority of this "static" data will rarely change. It will occassionally need to be updated and, when it does, I have no problem restarting the application to refresh the cache, if implemented.
Some data, which is more "dynamic", will be kept in the same database. This data includes contacts, statistics, etc. and will change more frequently (anywhere from hourly to daily to weekly). This data will be linked to the static data above via foreign keys (just like a SQL JOIN).
My question is, what exactly am I trying to implement here ? and how do I get started doing it ? I know the static data will be cached but I don't know where to start with that. I tried searching but came up with so much stuff and I'm not sure where to start. Recommendations for tutorials would also be appreciated.
You don't need to cache anything until you have a performance problem. Until you have a noticeable problem and have measured your application tiers to determine your database is in fact a bottleneck, which it rarely is, then start looking into caching data. It is always a tradeoff, memory vs CPU vs real time data availability. There is no reason to make your application more complicated than it needs to be just because.
An extremely simple 'win' here (I assume you're using WCF here) would be to use the declarative attribute-based caching mechanism built into the framework. It's easy to set up and manage, but you need to analyze your usage scenarios to make sure it's applied at the right locations to really benefit from it. This article is a good starting point.
Beyond that, I'd recommend looking into one of the many WCF books that deal with higher-level concepts like caching and try to figure out if their implementation patterns are applicable to your design.
This is more of a business-oriented programming question that I can't seem to figure out how to resolve. I work with a team of programmers who have been working with BASIC for over 20 years. I was brought in to help write the same software in .NET, only with updates and modern practices. The problem is that I can't seem to get any of the other 3 team members(all BASIC programmers, though one does .NET now as well) to understand how to correctly do a relational database. Here's the thing they won't understand:
We basically have a transaction that keeps track of a customer's tag information. We need to be able to track current transactions and past transactions. In the old system, a flat-file database was used that had one table that contained records with the basic current transaction of the customer, and another transaction that contained all the previous transactions of the customer along with important money information. To prevent redundancy, they would overwrite the current transaction with the history transactions-(the history file was updated first, then the current one.) It's totally unneccessary since you only need one transaction table, but my supervisor or any of my other two co-workers can't seem to understand this. How exactly can I convince them to see the light so that we won't have to do ridiculous amounts of work and end up hitting the datatabse too many times? Thanks for the input!
Firstly I must admit it's not absolutely clear to me from your description what the data structures and logic flows in the existing structures actually are. This does imply to me that perhaps you are not making yourself clear to your co-workers either, so one of your priorities must be to be able explain, either verbally or preferably in writing and diagrams, the current situation and the proposed replacement. Please take this as an observation rather than any criticism of your question.
Secondly I do find it quite remarkable that programmers of 20 years experience do not understand relational databases and transactions. Flat file coding went out of the mainstream a very long time ago - I first handled relational databases in a commercial setting back in 1988 and they were pretty commonplace by the mid-90s. What sector and product type are you working on? It sounds possible to me that you might be dealing with some sort of embedded or otherwise 'unusual' system, in which case you do need to make sure that you don't have some sort of communication issue and you're overlooking a large elephant that hasn't been pointed out to you - you wouldn't be the first 'consultant' brought into a team who has been set up in some manner by not being fed the appropriate information. That said such archaic shops do still exist - one of my current clients systems interfaces to a flat-file based system coded in COBOL, and yes, it is hell to manage ;-)
Finally, if you are completely sure of your ground and you are faced with a team who won't take on board your recommendations - and demonstration code is a good idea if you can spare the time -then you'll probably have to accept the decision gracefully and move one. Myself in this position I would attempt to abstract out the issue - can the database updates be moved into stored procedures for example so the code to update both tables is in the SP and can be modified at a later date to move to your schema without a corresponding application change? Make sure your arguments are well documented and recorded so you can revisit them later should the opportunity arise.
You will not be the first coder who's had to implement a sub-optimal solution because of office politics - use it as a learning experience for your own personal development about handling such situations and commiserate yourself with the thought you'll get paid for the additional work. Often the deciding factor in such arguments is not the logic, but the 'weight of reputation' you yourself bring to the table - it sounds like having been brought in you don't have much of that sort of leverage with your team, so you may have to work on gaining a reputation by exceling at implementing what they do agree to do before you have sufficient reputation in subsequent cases - you need to be modded up first!
Sometimes you can't.
If you read some XP books, they often say that one of your biggest hurdles will be convincing your team to abandon what they have always done.
Generally they will recommend letting people who can't adapt go to other projects (Or just letting them go).
Code reviews might help in your case. Mandatory code reviews of every line of code is not unheard of.
Sometime the best argument is an example. I'd write a prototype (or a replacement if not too much work). With an example to examine it will be easier to see the pros and cons of a relational database.
As an aside, flat-file databases have their places since they are so much easier to "administer" than a true relational database. Keep an open mind. ;-)
I think you may have to lead by example - when people see that the "new" way is less work they will adopt it (as long as you don't rub their noses in it).
I would also ask yourself whether the old design is actually causing a problem or whether it is just aesthetically annoying. It's important to pick your battles - if the old design isn't causing a performance problem or making the system hard to maintain you may want to leave the old design alone.
Finally, if you do leave the old design in place, try and abstract the interface between your new code and the old database so if you do persuade your co-workers to improve the design later you can drop the new schema in without having to change anything else.
It is difficult to extract a whole lot except general frustration from the original question.
Yes, there are a lot of techniques and habits long-timers pick up over time that can be useless and even costly in light of technology changes. Some things that made sense when processing power, memory, and even disk was expensive can be foolish attempts at optimization now. It is also very much the case that people accumulate bad habits and bad programming patterns over time.
You have to be careful though.
Sometimes there are good reasons for the things those old timers do. Sadly, they may not even be able to verbalize the "why" - if they even know why anymore.
I see a lot of this sort of frustration when newbies come into an enterprise software development shop. It can be bad even when the environment is all fairly modern technology and tools. If most of your experience is in writing small-community desktop and Web applications a lot of what you "know" may be wrong.
Often there are requirements for transaction journaling at a level above what your DBMS may do. Quite often it can be necessary to go beyond DB transaction semantics in order to ensure time-sequence correctness, once and only once updating, resiliancy, and non-repudiation.
And this doesn't even begin to address the issues involved in enterprise or inter-enterprise scalability. When you begin to approach half a million complex transactions a day you will find that RDBMS technology fails you. Because relational databases are not designed to handle high transaction volumes you must often break with standard paradigms for normalization and updating. Conventional RDBMS locking techniques can destroy scalability no matter how much hardware you throw at the problem.
It is easy to dismiss all of it as stodginess or general wrong-headedness - even incompetence. But be careful because this isn't always the case.
And by the way: There are other models besides the RDBMS, and the alternative to an RDBMS is not necessarily "flat files" - contrary to the experience of of most coders today. There are transactional hierarchical DBMSs that can handle much higher throughput than an RDBMS. IMS is still very much alive in large IBM shops, for example. Other vendors offer similar software for different platforms.
Of course in a 4-man shop maybe none of this applies.
Sign them up for some decent trainings and then it's up to you to convince them that with new technologies a lot more is possible (or at least easier!).
But I think the most important thing here is that professional, certified trainers teach them the basics first. They will be more impressed by that instead of just one of their colleagues telling them: "hey, why not use this?"
Related post here.
The following may not apply in yr situation, but you make very little mention of technical details, so I thought I'd mention it...
Sometimes, if the access patterns are very different for current data than for historical data (I'm making this example up, but say that Current data is accessed 1000s of times per second, and accesses a small subset of columns, and all current data fits in less than 1 GB, whereas, say, historical data uses 1000s of GBs, is accessed only 100s of times per day, and access is to all columns),
then, what your co-workers are doing would make perfect sense, for performance optimization. By separating the current data (albiet redundantly) you can optimize the indices and data structures in that table, for the higher frequency access paterns that you could not do in the historical table.
Not everything that is "academically", or "technically" correct from a purely relational perspective makes sense when applied in an actual practical situation.
Locked. This question and its answers are locked because the question is off-topic but has historical significance. It is not currently accepting new answers or interactions.
How do you go about the requirements gathering phase? Does anyone have a good set of guidelines or tips to follow? What are some good questions to ask the stakeholders?
I am currently working on a new project and there are a lot of unknowns. I am in the process of coming up with a list of questions to ask the stakeholders. However I cant help but to feel that I am missing something or forgetting to ask a critical question.
You're almost certainly missing something. A lot of things, probably. Don't worry, it's ok. Even if you remembered everything and covered all the bases stakeholders aren't going to be able to give you very good, clear requirements without any point of reference. The best way to do this sort of thing is to get what you can from them now, then take that and give them something to react to. It can be a paper prototype, a mockup, version 0.1 of the software, whatever. Then they can start telling you what they really want.
See obligatory comic below...
In general, I try and get a feel for the business model my customer/client is trying to emulate with the application they want built. Are we building a glorified forms processor? Are we retrieving data from multiple sources in a single application to save time? Are we performing some kind of integration?
Once the general businesss model is established, I then move to the "must" and "must nots" for the application to dictate what data I can retrieve, who can perform what functions, etc.
Usually if you can get the customer to explain their model or workflow, you can move from there and find additional key questions.
The one question I always make sure to ask in some form or another is "What is the trickiest/most annoying thing you have to do when doing X. Typically the answer to that reveals the craziest business/data rule you'll have to implement.
Hope this helps!
Steve Yegge talks fun but there is money to be made in working out what other people's requirements are so i'd take his article with a pinch of salt.
Requirements gathering is incredibly tough because of the manner in which communication works. Its a four step process that is lossy in each step.
I have an idea in my head
I transform this into words and pictures
You interpret the pictures and words
You paint an image in your own mind of what my original idea was like
And humans fail miserably at this with worrying frequency through their adorable imperfections.
Agile does right in promoting iterative development. Getting early versions out to the client is important in identifying what features are most important (what ships in 0.1 - 0.5 ish), helps to keep you both on the right track in terms of how the application will work and quickly identifies the hidden features that you will miss.
The two main problem scenarios are the two ends of the scales:
Not having a freaking clue about what you are doing - get some domain experts
Having too many requirements - feature pit. - Question, cull (prioritise ;) ) features and use iterative development
Yegge does well in pointing out that domain experts are essential to produce good requirements because they know the business and have worked in it. They can help identify the core desire of the client and will help explain how their staff will use the system and what is important to the staff.
Alternatives and additions include trying to do the job yourself to get into the mindset or having a client staff member occasionally on-site, although the latter is unlikely to happen.
The feature pit is the other side, mostly full of failed government IT projects. Too much, too soon, not enough thought or application of realism (but what do you expect they have only about four years to make themselves feel important?). The aim here is to work out what the customer really wants.
As long as you work on getting the core components correct, efficient and bug-free clients usually remain tolerant of missing features that arrive in later shipments, as long as they eventually arrive. This is where iterative development really helps.
Remember to separate the client's ideas of what the program will be like and what they want the program to achieve.
Some clients can create confusion by communicating their requirements in the form of application features which may be poorly thought out or made redundant by much simpler functionality then they think they require. While I'm not advocating calling the client an idiot or not listening to them I feel that it is worth forever asking why they want a particular feature to get to its underlying purpose.
Remember that in either scenario it is of imperative importantance to root out the quickest path to fulfilling the customers core need and put you in a scenario where you are both profiting from the relationship.
Wow, where to start?
First, there is a set of knowledge someone should have to do analysis on some projects, but it really depends on what you are building for who. In other words, it makes a big difference if you are modifying an enterprise application for a Fortune 100 corporation, building an iPhone app, or adding functionality to a personal webpage.
Second, there are different kinds of requirements.
Objectives: What does the user want to accomplish?
Functional: What does the user need to do in order to reach their objective? (think steps to reach the objective/s)
Non-functional: What are the constraints your program needs to perform within? (think 10 vs 10k simultaneous users, growth, back-up, etc.)
Business rules: What dynamic constraints do you have to meet? (think calculations, definitions, legal concerns, etc.)
Third, the way to gather requirements most effectively, and then get feedback on them (which you will do, right?) is to use models. User cases and user stories are a model of what the user needs to do. Process models are another version of what needs to happen. System diagrams are just another model of how different parts of the program(s) interact. Good data modeling will define business concepts and show you the inputs, outputs, and changes that happen within your program. Models (and there are more than I listed) are really the key to the concern you list. A few good models will capture the needs and from models you can determine your requirements.
Fourth, get feedback. I know I mentioned this already, but you will not get everything right the first time, so get responses to what your customer wants.
As much as I appreciate requirements, and the models that drive them, users typically do not understand the ramifications of of all their requests. Constant communication with chances for review and feedback will give users a better understanding of what you are delivering. Further, they will refine their understanding based on what they see. Unless you're working for the government, iterations and / or prototypes are helpful.
First of all gather the requirements before you start coding. You can begin the design while you are gathering them depending on your project life cicle but you shouldn't ever start coding without them.
Requirements are a set of well written documents that protect both the client and yourself. Never forget that. If no requirement is present then it was not paid for (and thus it requires a formal change request), if it's present then it must be implemented and must work correctly.
Requirements must be testable. If a requirement cannot be tested then it isn't a requirement. That means something like, "The system "
Requirements must be concrete. That means stating "The system user interface shall be easy to use" is not a correct requirment.
In order to actually "gather" the requirements you need to first make sure you understand the businness model. The client will tell you what they want with its own words, it is your job to understand it and interpret it in the right context.
Make meetings with the client while you're developing the requirements. Describe them to the client with your own words and make sure you and the client have the same concept in the requirements.
Requirements require concise, testable example, but keep track of every other thing that comes up in the meetings, diagrams, doubts and try to mantain a record of every meeting.
If you can use an incremental life cycle, that will give you the ability to improve some bad gathered requirements.
You can never ask too many or "stupid" questions. The more questions you ask, the more answers you receive.
According to Steve Yegge that's the wrong question to ask. If you're gathering requirement it's already too late, your project is doomed.
High-level discussions about purpose, scope, limitations of operating environment, size, etc
Audition a single paragraph description of the system, hammer it out
Mock up UI
Formalize known requirements
Now iterate between 3 and 4 with more and more functional prototypes and more specs with more details. Write tests as you go. Do this until you have functional software and a complete, objective, testable requirements spec.
That's the dream. The reality is usually after a couple iterations everybody goes head-down and codes until there's a month left to test.
Gathering Business Requirements Are Bullshit - Steve Yegge
read the agile manifesto - working software is the only measurement for the success of a software project
get familiar with agile software practices - study Scrum , lean programming , xp etc - this will save you tremendous amount of time not only for the requirements gathering but also for the entire software development lifecycle
keep regular discussions with Customers and especially the future users and key-users
make sure you talk to the Persons understanding the problem domain - e.g. specialists in the field
Take small notes during the talks
After each CONVERSATION write an official requirement list and present it for approving. Later on it would be difficult to argue against all agreed documentation
make sure your Customers know approximately what are the approximate expenses in time and money for implementing "nice to have" requirements
make sure you label the requirements as "must have" , "should have" and "nice to have" from the very beginning, ensure Customers understand the differences between those types also
integrate all documents into the latest and final requirements analysis (or the current one for the iteration or whatever agile programming cycle you are using ... )
remember that requirements do change over the software life cycle , so gathering is one thing but managing and implementing another
KISS - keep it as simple as possible
study also the environment where the future system will reside - there are more and more technological restraints from legacy or surrounding systems , since the companies do not prefer to throw to the garbage the money they have invested for decades even if in our modern minds 20 years old code is garbage ...
Like most stages of the software development process its iteration works best.
First find out who your users are -- the XYZ dept,
Then find out where they fit into the organisation -- part of Z division,
Then find out what they do in general terms -- manage cash
Then in specific terms -- collect cash from tills, and check for till fraud.
Then you can start talking to them.
Ask what problem they want you want to solve -- you will get an answer like write a bamboozling system using OCR with shark technoligies.
Ignore that answer and ask some more questions to find out what the real problem is -- they cant read the till slips to reconcile the cash.
Agree a real solution with the users -- get a better ink ribbon supplier - or connect the electronic tills to the network and upload the logs to a central server.
Then agree in detail how they will measure the success of the project.
Then and only then propose and agree a detailed set of requirements.
I would suggest you to read Roger-Pressman's Software Engineering: A Practitioner's Approach
Before you go talking to the stakeholders/users/anyone be sure you will be able to put down the gathered information in a usefull and days-lasting way.
Use a sound-recorder if it is OK with the other person and the information is bulky.
If you heard something important and you need some reasonable time to write it down, you have two choices: ask the other person to wait a second, or say goodbye to that precious information. You wont remember it right, ask any neuro-scientist.
If you detect that a point need deeper review or that you need some document you just heard of, make sure you make a commitment with the other person to send that document or schedule another meeting with a more specific purpose. Never say "I'll remember to ask for that xls file" because in most cases you wont.
Not to long after the meeting, summarize all your notes, recordings and fresh thoughts. Just summarize it rigth. Create effective reminders for the commitments.
Again, just after the meeting, is the perfect time to understand why the gathering you just did was not as right as you thought at the end of the meeting. That's when you will be able to put down a lot of meaningful questions for another meeting.
I know the question was in the perspective of the pre-meeting, but please be aware that you can work on this matters before the meeting and end up with a much usefull, complete and quality gathering.
I've been using mind mapping (like a work breakdown structure) to help gather requirements and define the unknowns (the #1 project killer). Start at a high level and work your way down. You need to work with the sponsors, users and development team to ensure you get all the angles and don't miss anything. You can't be expected to know the entire scope of what they want without their involvement...you - as a project manager/BA - need to get them involved (most important part of the job).
There are some great ideas here already. Here are some requirements gathering principles that I always like to keep in mind:
Know the difference between the user and the customer.
The business owners that approve the shiny project are usually the customers. However, a devastating mistake is the tendency to confuse them as the user. The customer is usually the person that recognizes the need for your product, but the user is the person that will actually be using the solution (and will most likely complain later about a requirement your product did not meet).
Go to more than one person
Because we’re all human, and we tend to not remember every excruciating detail. You increase your likelihood of finding missed requirements as you talk to more people and cross-check.
Avoid specials
When a user asks for something very specific, be wary. Always question the biases and see if this will really make your product better.
Prototype
Don’t wait till launch to show what you have to the user. Do frequent prototypes (you can even call them beta versions) and get constant feedback throughout the development process. You’ll probably find more requirements as you do this.
I recently started using the concepts, standards and templates defined by the International Institute of Business Analysts organization (IIBA).
They have a pretty good BOK (Book of Knowledge) that can be downloaded from their website. They do also have a certificate.
Requirements Engineering is a bit of an art, there are lots of different ways to go about it, you really have to tailor it to your project and the stakeholders involved. A good place to start is with Requirements Engineering by Karl Wiegers:
http://www.amazon.com/Software-Requirements-Second-Pro-Best-Practices/dp/0735618798/ref=pd_bbs_sr_2?ie=UTF8&s=books&qid=1234910330&sr=8-2
and a requirements engineering process which may consist of a number of steps e.g.:
Elicitation - for the basis for discussion with the business
Analysis and Description - a technical description for the purpose of the developers
Elaboration, Clarification, Verification and Negotiation - further refinement of the requirements
Also, there are a number of ways of documenting the requirements (Use Cases, Prototypes, Specifications, Modelling Languages). Each have their advantages and disadvantages. For example prototypes are very good for elicitation of ideas from the business and discussion of ideas.
I generally find that writing a set of use cases and including wireframe prototypes works well to identify an initial set of requirements. From that point it's a continual process of working with technical people and business people to further clarify and elaborate on the requirements. Keeping track of what was initially agreed and tracking additional requirements are essential to avoid scope creep. Negotiation plays a bit part here also between the various parties as per the Broken Iron Triangle (http://www.ambysoft.com/essays/brokenTriangle.html).
IMO the most important first step is to set up a dictornary of domain-specific words. When your client says "order", what does he mean? Something he receives from his customers or something he sends to his suppliers? Or maybe both?
Find the keywords in the stakeholders' business, and let them explain those words until you comprehend their meaning in the process. Without that, you will have a hard time trying to understand the requirements.
i wrote a blog article about the approach i use:
http://pm4web.blogspot.com/2008/10/needs-analysis-for-business-websites.html
basically: questions to ask your client before building their website.
i should add this questionnaire sheet is only geared towards basic website builds - like a business web presence. totally different story if you are talking about web-based software. although some of it is still relavant (e.g. questions relating to look and feel).
LM
I prefer to keep my requirements gathering process as simple, direct and thorough as possible. You can download a sample document that I use as a template for my projects at this blog posting: http://allthingscs.blogspot.com/2011/03/documenting-software-architectural.html