游戏邦在:
杂志专栏:
gamerboom.com订阅到鲜果订阅到抓虾google reader订阅到有道订阅到QQ邮箱订阅到帮看

创造还是购买一个游戏分析系统?

发布时间:2016-07-11 11:35:23 Tags:,,,,

作者:Chris Wright

关于是创造还是购买分析系统的确是一个艰难的决定。而在你做出这个决定前你需要考虑许多情况。

所以在尝试前你应该考虑哪些事?

make or buy(from gamasutra)

make or buy(from gamasutra)

1.创造你自己的分析系统—-关于你为什么要自己创建一个平台主要存在3个原因。首先这能降低成本,其次这能够确保你可以完全控制所有数据,而最重要的原因还是你想要真正面向自己所开发的游戏并基于特定规格去定制相关分析系统。关于成本,你需要着眼于你们将使用怎样的数据库技术去创建这一系统,如此的基础设施成本是多少;你们还需要去寻找能够创建该系统的软件工程师和相关人才。这里还要考虑到运行成本并确保该系统始终是可行的,而这的确是个昂贵的过程。一旦你决定开始,你就很难再回头了,你需要确保它能够始终运行下去。

2.妥协—-在你做出的任何决定中总是存在妥协的情况。如果你打算创造你自己的分析系统,你便需要着眼于总成本,创造与运行成本以及投资回报率。之后明确你想要创造怎样的内容以及为什么要创造这样的内容便非常重要。你是针对于一款特定游戏进行创造还是打算将其用于一系列游戏中?如果是这样的话会出现怎样的效果?你必须拥有长远的视角。同时你还要考虑除了分析你是否还会将其用于市场营销中?是否会用其去改变游戏行为?是否会在游戏中添加广告?是否会改变游戏所提供的内容?在创建你自己的系统时你需要考虑的内容真的有许多。

3.核心数据库技术—-基于你所创造的内容你需要着眼于两种不同的数据库技术。从分析角度来看,你需要着眼于数据仓库,即数据是怎样流入的以及你可以使用它做些什么。你是否只需要去收集数据,储存数据并基于数据去运行?你是否需要一些图表去明确自己的收益以及每日活跃用户指数?或者你是否想要获得一些更详细的数据内容。如果是这样的话你便需要列式数据库,即能够帮助你获得收据并进行详细的分析等等,就像惠普的Vertica或亚马逊的Redshift那样。

如果你想要进行实时市场营销,你便需要一些能够帮助你快速做出决定的工具,如内存数据库。即像VoltDB之类的工具,除此之外也有一些不同的工具。你需要决定自己想要创造什么样的内容以及你计划使用数据去做些什么,这些都将帮助你做出正确的决定。

4.数据储存—-你需要某种数据湖泊,即能够用于后续数据库中的内容。如果你将基于它进行分析,你便需要像Vertica或Redshift这种列式数据库的帮助。而这一切都是取决于你想要使用数据库去做些什么。如果你并不打算恢复它或经常使用它,你便可以将其储存在像S3这样廉价又简单的仓库中。而如果你想要不断分析数据,你便需要将其置于活跃的数据库中从而让自己可以随时分析数据。

5.验证数据—-关于数据收集,你最好确保这一过程足够简单,因为你将需要收集大量的数据。大多数公司都是从简单的核心数值开始。如果你需要一些更复杂的内容,你便可以创造Json结构去获取一些更复杂的内容。你需要将其快速且有效地整合到自己的系统中。关于数据的流动我们经历了较漫长的处理过程并对其进行了验证。我们相信验证是非常必要的。这能够帮助你确保该数据是你们的数据仓库中最主要的内容之一。所以你最好能够事先进行规划并去验证所获得数据,这对于数据输入和输出都很重要。

6.安全考虑—-你需要确保所有数据都是安全的,为此你必须真正了解数据保护。你还必须清楚美国和欧洲的数据保护法规是不同的。你需要了解人们会如何访问这些数据并且当你的系统出现漏洞时该怎么办。如果你正在收集数据,你也可能遇到黑客的问题。为了解决这种情况,你最好求助于外部保安公司去验证你的数据并基于你的系统进行渗透测试以确保外部非法组织没办法去访问它,同时对其设置密码。你应该确保将数据储存在一个真正安全的地方并对其进行加密保护。

7.扩展和第三方工具—-当你在购买分析系统时需要能够确保它足够灵活,即让你能够插入第三方工具并使用任何你想使用的工具。你可以使用平台作为数据仓库,也可以使用它作为分析工具。例如deltaDNA的Direct Access不仅能够提供给你所需要的性能,也能够让你进行扩展。即用户不仅可以使用基本平台及其核心功能,也可以使用第三方工具对其进行扩展从而去满足自己的需求。

8.独立开发者—-独立开发者也能够找到一些免费系统。而如果你像我们这样只想花较少的钱,你便可以选择独立授权。现在对于独立开发者来说最好的事便是他们可以使用更多技术了。他们可以访问许多之前需要花费高额成本才能获得的引擎和分析平台,这便意味着他们可以使用那些真正重要的工具去创造出最棒的创意游戏。

本文为游戏邦/gamerboom.com编译,拒绝任何不保留版权的转发,如需转载请联系:游戏邦

Build or buy a game analytics system?

by Chris Wright

It’s a tough decision, whether to make or buy a game analytics system. There are lots of things to contemplate before you make the big decision. I’ve been through the process; firstly, when building the deltaDNA platform to support the company’s consultancy activities, and then continuing to extend the platforms capabilities.

So what should you consider before taking the plunge?

1. Building your own – There are three main reasons why you would want to build a platform yourself. The first is price and keeping costs down, the second is security and ensuring the data is under your control, and the most important reason is if you are looking to be very specific to the game you have developed and are looking to tailor it to exact specifications. Regarding cost, you need to look at the database technology you are going to use to build this, infrastructure costs and hosting; the software engineers and the people you need to build it and add to it. And there is also the cost of running it and making sure it is always available, which is expensive to do. Once you start, it is very hard to back out, as you have to keep it running.

2. Compromises – There are really always compromises in any decision you take. If you are going to build your own then you have to look at the total cost of ownership, the cost of building and running it, and the return on investment. Understanding that, and knowing exactly what you are trying to build, and why you are trying to build it is crucial. Are you building it for one specific game, or are you going to use it across a whole set of games? If so what are the effects of that going to be? You have to really take the long view and factor in what you are going to use it for. Are you going to use it for marketing purposes as well as analytics? For changing game behaviours? Putting adverts into the game? Changing in-game offers? So there are a whole set of objectives to consider when building your own system.

3. Core database technologies – There are two different kinds of database technologies you need to look at depending on what you are building. From an analytics point of view you really need to look at the data warehouse, so how data flows in and what you can do with it. Are you simply going to collect the data, store it and run aggregates against it? Do you want to have charts to look at your revenue and your daily active users? Or do you want to put it into something that can do detailed data mining. If so, you will need some kind of column store, something that allows you to pull that data in, so you can undertake detailed analysis, such as HP Vertica or Amazon’s Redshift.

If you are looking to do real-time marketing, then you will need something that allows you to make decisions rapidly such as a memory database. Something like VoltDB, but there are different kinds available. You need to decide exactly what you are trying to build, and what purpose you are planning to use your data for, to inform your database decision.

4. Data storage – You will need a type of data lake, which could simply be S3 or you could put it into some kind of sequel database. If you are going to do analysis on it then you will need to have something quicker – a column store like Vertica or Redshift. It really depends on what you want to do with that data. If you are not going to recover it or look at it often, then storing it in a nice cheap simple storage like S3 may well be perfectly practical. If you want to analyze data continuously, then you will need to keep it in an active database that allows you to do real time analysis against that data and data mine it.

5. Validated data – For data capture, keep it as simple as possible, as you will be collecting large amounts of data. Most companies start with a simple key values style. If you need something more complex, you can start to build Json structures that allows you to have more complicated events. You need to get it into your system as quickly and efficiently as possible. We do quite a lot of processing as the data flows through and we validate it. We believe that validation is imperative. Making sure that the data is clean is probably one of the most crucial things in your data warehouse. So putting that up front, controlling the schemas and making sure that you validate the data coming through, are important things to consider as garbage in = garbage out.

6. Security considerations – You need to make sure all the data is secure and that you have a cohesive understanding of data protection. Bear in mind data protection legislation also differs between the US and Europe. You need to understand how people can access it and if there are any loopholes in your system. If you are collecting data, there is always the danger of hacking. To counter this, have an external security company validate your data and do penetration tests against your system to make sure there is no way an unauthorized external party can access it, attain passwords and get at the encrypted data. Making sure you have the data in a secure place and that it is encrypted when at rest is important.

7. Extension and third party tools – Make sure when buying an analytics system, that you can extend the platform, that you can plug third party tools into it and use whatever tools you want, to give flexibility. You can use the platform as a data warehouse, as well as an analytics tool. For instance, deltaDNA’s Direct Access, gives you that capability, and allows you to extend. Clients use the base platform, the core functionality, but then they extend it with third party tools that allow them to do exactly what they want.

8. Indies – There are free systems out there for Indies so every budget can be catered for. However, if you want to spend a small amount of money, then a lot of companies, including ourselves, will do Indie licences to make it cheap and affordable. The great thing about Indies is that they now have access to an incredible set of technologies. They have access to engines and analytics platforms that used to cost hundreds of thousands of dollars, which are now easily accessible (either free or very low cost), which means they can get on with what’s really important and exciting, which is creating original games.(source:Gamasutra

 


上一篇:

下一篇: