Why You Should Build Your Infrastructure To Support Data Analytics

09/27/2022 | Data Management, Technology Education

Too often, organizations relegate data analytics to a supporting role. This is a mistake. Data analytics should be at the core of an organization’s operations. By building your data infrastructure to support analytics, you ensure that your organization makes the most of its data.

When data is collected and prioritized, companies see many benefits. Product-driven companies can adjust their design, bundling, and recommendations — increasing profit margins and customer satisfaction. On the other hand, service-driven companies can optimize their services, removing unprofitable offerings and enhancing those that drive the bulk of their revenue.

A robust data analytics program doesn’t come about by chance; it must be built on a solid technology foundation. Let’s consider how data infrastructure benefits your analytics program.

Efficient Data Infrastructure Boosts Your Team’s Performance

Building your data infrastructure to support analytics boosts company performance. It helps you avoid costly downtime, prevents over-investment in unnecessary infrastructure, and helps you scale your resources with ease. To design a data infrastructure that aligns with your company’s needs, you should consider a few pillars of computing infrastructure:

  1. Make sure your infrastructure is scalable. Your data volume will likely grow over time, so you’ll need to ensure your infrastructure can accommodate this growth. Think about how storage, networking, and processing power combine to serve your computing needs. For example, many businesses use composable or disaggregated architectures to share computing resources. This approach allows them to treat all their hardware as a single pool, using resources more efficiently.
  2. Choose the right technology stack. Consider the volume and type of data and what you want to do with it. Your choices will determine how easy it is to integrate with public cloud platforms like AWS and Azure. Additionally, platforms like Weka.io can provide considerable improvements to your storage performance.
  3. Establish clear roles and permissions. Setting up your data architecture beforehand will ensure everyone in your organization has access to the data they need and that data stays organized as you scale. And don’t forget to create policies for deactivating applications to keep your system clean.
  4. Invest in training and education. One of the most important aspects of building a data infrastructure to support data analytics is ensuring that your team can use it effectively. Some organizations hold regular workshops to teach their team how to use the new infrastructure. You can also provide your team with resources like manuals and tutorials.

These pillars will set the foundation for your data infrastructure, providing your team with the hardware and expertise to use it effectively. One way to boost your infrastructure is to work with a partner that understands the challenges of deploying scalable infrastructure.

Prepare Yourself for the Continued Boon of Data Analytics

Data analytics is growing at an unprecedented rate. According to Gartner, “by 2025, 70% of organizations will shift their focus from big to small and wide data.” This means they will be taking in data from more sources than ever before — providing better context for business decision-making. You can stay ahead of the game by ensuring your data infrastructure is ready for these changes.

Equus has decades of experience helping businesses design hardware solutions that fit their current and future needs and deploying them at scale. The first step in designing your hardware infrastructure is understanding the options available. Our team can help you prioritize your requirements and strategize on the best hardware solutions for your company. Contact us to learn more.