Navigating through large data volumes: 3 considerations

A survey by Dell stated 43% of IT decision-makers fear their data infrastructure won’t be able to handle future data demands. And with the amount of data generated by machines and humans increasing daily, their worries are understandable.

Organizations rely on data collection and analysis to guide their decision-making processes. Data backs countless organizational functions, from AI-powered technologies like natural language processing to customer behavior tracking and fraud detection.

However, if you haven’t already, you’ll likely run into volume-based roadblocks that slow your productivity. This guide will explore three data considerations your organization should consider to manage its data use proactively. 

Volume and scalability

Although you may not be trudging through large data loads now, that doesn’t mean you won’t experience increased demand later. It’s essential to know the volume of data that flows through your organization and understand its expected growth rate. This way, you can anticipate challenges and course-correct. 

To get a handle on your organization’s current and future data volume, consider these questions:

What are your primary data sources? 

List your primary data sources, such as membership databases, event registration systems, CRM software data, or AMS software data. These sources are foundational for generating insights and making informed decisions. However, incompatible systems could cause duplicate or erroneous data. For example, gathering membership data to add to your CRM from two sources can falsely inflate your membership numbers. 

Are you integrating data from various systems and sources?

Data integration involves consolidating data from multiple sources. Successful integration ensures your datasets are comprehensive, consistent, accurate, and available for analysis. 

If you’re integrating data from multiple sources, you must ensure that an increasing data volume will not stall your processes. Point-to-point integration, or using custom code to connect two systems, may work well for simple use cases, but it’s not a scalable solution. That’s why you should consider an Integration Platform as a Service that can simplify your integration without additional costs or effort.

Your current and potential data volumes are a deciding factor for understanding which solutions will best support your workflows and meet your needs. For instance, a healthcare organization may adopt a specialized electronic health record integration platform to manage and organize large patient data volumes. 

Governance and security 

Governance policies such as HIPAA and GDPR should continue to guide your decision-making as your organization grows. The larger your organization’s data load, the more at-risk your sensitive data becomes. To stay on top of legal requirements and security best practices, ask these questions:

How will you protect data from unauthorized access?

Depending on your platform, you must be confident that it is legally compliant and scalable. It should have reliable encryption, access controls, and regular system updates to protect you from cyber security threats and ransomware attacks on your data. 

How will you communicate security expectations to your stakeholders?

Ensure that everyone with access to your data is on the same page about how to protect it. Use data governance and documentation to outline best data ownership and stewardship practices. 

Update your internal security policy regularly. For example, if you’re migrating data between platforms, this will include several departments. In this case, you need to keep all relevant parties informed. If you partner with a technology consultant, you’ll want to double-check their security training and expertise. 

Keeping your software and internal systems in check with data governance best practices will ensure proper data handling and save your organization from legal fees. 

Software usability

Arcadia’s analytics guide states, “High-quality and comprehensive data is vital for accurate analysis and meaningful results.” In other words, organized data is great, but it’s just the first step in meaningful analysis. 

Reliable software and digital tools are necessary to get the most out of your collected data. Without them, you won’t realize your data’s potential to make strategic decisions. Ask yourself these questions to evaluate your tech stack’s usability:

Is our software user-friendly?

Assess how intuitive your software interface is for all users, including those with varying technical expertise. When deciding between software solutions, invite the relevant employees to give feedback on platform demonstrations and research.

When vetting software vendors, ask which tools they’ve incorporated to enhance user experience and productivity. Ensure your chosen solution provides knowledgeable, reliable support to implement and maintain your software. 

Can we customize it to align with our preferences and workflows?

Choose a platform that caters to your organization’s preferred workflows, including personalization options such as role-based reports, views, and access controls. For example, you may find that customizable dashboard visualizations are a must-have functionality for your organization.

Does it scale with increasing data loads?

You shouldn’t have to worry about your software’s performance when you increase your data volume. Onboarding new members or changing business needs should not affect software response times and capacity. 

That’s why it’s essential to research a software vendor with testimonials of clients that reflect your organization’s needs and goals. Additionally, look for a platform that provides third-party integration capabilities and regular updates to stay on top of data volume. 

By addressing these considerations, organizations can confidently navigate large data volumes and leverage data insights that drive strategic decision-making to help them achieve their goals.