Combine the 3 Vs of Big Data with the 3 Ss of Bare Metal Servers

The big data infrastructure needs to be adapted to the size of the company, and the particular use case, but it also needs to be scalable so it can fit your growth path. Generally, a big data infrastructure requires a fast network, as well as servers that provide extensive computing power.

The 3 Vs in Big Data

When people talk about big data they typically refer not just to data volume but also to data velocity and data variety. In a nutshell:

• Volume describes how much data you have.
• Velocity describes how fast new data comes in.
• Variety refers to how different the data you have is: video, text, images, and more.

The 3 Ss in Bare Metal Servers

The infrastructure you run your big data projects on is key to gaining rapid insights. Stability of the infrastructure, security of data, and scalability are key to the success of your big data projects.

• Stability in bare metal servers refers to high availability, which is achieved through the redundancy of the systems you use in your big data projects.
• Security in bare metal servers refers to single-tenancy – only you have access to the hardware.
• Scalability in bare metal servers refers to being able to switch your existing infrastructure that reached its resource limit to a different infrastructure quickly, with minimal downtime or no downtime at all.

Big Data Industry Use Cases

There are a few common big data use cases that can benefit many industries, for instance:

• Customer Segmentation
• Product Development
• Churn Prevention
• Fraud Detection
• Real-time Analytics

To go further into details, there are also big data use cases particular to each industry:

• Healthcare – i.e. biometric data analysis
• Telecom – i.e. network management and optimization
• Gaming – i.e. real-time rendering techniques, photogrammetry
• E-commerce – i.e. recommendation systems
• Traditional Retail – i.e. optimizing in-store replenish of products
• Media/Streaming – i.e. real-time viewership data analysis, improve advertising strategies
• Banking/Fintech – i.e. risk management analysis
• Insurance – i.e. fraud detection

You will need to create a roadmap taking into consideration your business objectives for your big data projects:

Infrastructure Challenges in Running Big Data Projects

• Slow Storage

Disk input/output bottlenecks can cause delay in data processing. An I/O bottleneck means that the big data infrastructure will not be able to ingest and process the data fast enough.

• Lack of Scalability

Not being able to grow your infrastructure along with your data volume will cause bottlenecks. A non-scalable system means that the infrastructure will eventually reach its resource limit. Migrating to a different infrastructure is a complex and time-consuming process that will generate significant downtime and costs.

• Slow Network Connectivity

A slow network can cause your large data analysis to take forever. Network speed can mean the difference between processing the same data in 2 hours instead of 2 days.

How to Improve Your Big Data Projects for Your Business

While most of these features are offered by public cloud providers, they do not offer the same performance as a bare metal server. Big data projects need a lot of processing power and storage, so they are unlikely to work well on virtualized solutions. Bare metal servers provide the processing power and the high availability that big data projects require. A few bare metal providers (yes, us included!) also offer some of the scalability and flexibility associated with the cloud.

Given the above challenges, you should:

• Choose a provider that offers scalable storage

Quickly scalable drives eliminate all the guess-work and allow you to use precisely as much storage space as needed.

• Choose a provider that offers scalability

You can quickly scale up resources when needed, and easily scale back. This allows you to control your costs, and not pay monthly for a server that you only use a few days.

• Choose a provider that offers a fast network

A Layer 2 Network provides several important advantages: the speed required for running big data projects, a reduction in cost (since LAN traffic is not billed), and improved security (since private networks can’t be accessed from the outside).

Want to discuss big data infrastructure requirements specific to your business? Contact us anytime.