Big data architecture is a big investment for an organization. There are plenty of things to be considered before deciding to go big; and then, once that decision is reached, you still have a plenty of things to considered. Here, we discuss the absolutely crucial aspects of big data architecture that every business owner should look into before investing in the big data architecture.
The aspects range from deciding to customize or pick a standard solution to opting for a storage medium that will fit your company’s security policy and your pockets. Let’s look at the consideration points.
Big organizations often like to hire big data developers who can custom build its big data architecture; while small organizations opt for standard available architecture. But, the kind of services and features that standard operators offer are beyond comparison and you should build architecture only when you absolutely have to.
The other important consideration is to decide the type of architecture. Now, if you are not an expert, you would know the distinction between Kappa and Lambda. For beginners, these are the two types of architectures with distinction of batch with stream and only streaming of data. Read on for more information on batch and stream or talk to your big data developers.
You would also be required to decide your storage and hosting medium. That is a decision between public or private cloud. It is a whole another ball game if you are not opting for cloud. Organization that will be dealing with extremely crucial data prefer using private clouds over public clouds.
With respect to batch and stream, these are two ways to handle data. Both have their advantages and disadvantages. While batch is popular because of big data technologies like Hadoop using it, streaming is more scalable. But, there are modern tools that can combine both the features to provide impeccable results.
You might be thinking that you have everything sorted once you have made your choices; but, there is more to it. The fact that you will not be working on the tools makes you less credible as a decision-maker. The final call should be made only after consulting with your team of big data analytics solutions. They are the ones who will be working on it, so they deserve to have a say in the decision making because if they fail to use it effectively, your investment is going down the drain.
It is important for organizations to make decisions regarding big data architecture by carefully considering the end use and expectation. This clear vision would empower them to make better choice which would ultimately result in an architecture that would bring performance efficiency, enhance processes, increase revenues, and what not.
Understanding different terminologies like Kappa and Lambda, batch and stream, public and private cloud, etc. is bound to give you an edge as a decision maker who is striving for the better results by providing better infrastructure. If you feel there are any other points that need to be considered, please share with us in the comments section below.
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