5G and big data:

Seven tips for


Author: Mike Elgan

It's widely understood that 5G is set to transform business. But you can't talk about the coming 5G transformation without talking about 5G and big data. And you can't talk about 5G and big data without talking about artificial intelligence (AI) and multi-access edge computing (MEC). There's a ton of change coming. But don't be overwhelmed. Be prepared.

To oversimplify, 5G is needed to distribute AI to the edge and to devices. And AI is needed to bring intelligence to complex 5G networks. Widely distributed AI, edge computing and 5G all should drive very fast, very low-latency interactions throughout an organization. 5G and big data complement each other.

How 5G and big data work together

5G and big data are a key part of the Internet of Things (IoT) revolution. And for the simple reason that most IoT devices exist to produce actionable data.

What makes big data so "big" is that it tends to have the attributes of volume (or amount of data), speed (how fast it needs to be gathered, transmitted and processed), value (business-critical content) and variety (lots of different data types). Big data sets are so complex and enormous that yesterday's database systems can't deal with them.

None of this is static—especially the data processing part, which will increase in importance and magnitude at astronomical rates going forward. 5G networks can be key to providing the bandwidth and remote AI computing that can fuel the business intelligence revolution.

AI uses deep learning to extract business insights from large quantities of data, which can be used to improve operations, logistics, marketing and many other business endeavors.

Let's talk about data processing

The use of 5G and big data with AI-based machine vision is expected to turbocharge factories, helping to optimize assembly lines, reduce downtime and enable preventive maintenance. Using IoT sensors, AI-based predictive analytics can optimize inventory management, cutting costs and minimizing delays. This can be especially powerful in complex manufacturing environments.

All this data processing should not only enhance and optimize business processes, but provide feedback into the intelligent networks for continuous, self-healing optimization.

The data-driven organization of the future features data processing close to its source, either through on-device AI or on-the-edge cloud, all connected via 5G. The performance needed for this intelligent organization comes from low latency enabled by 5G and the edge network. 

How to prepare for the new world of 5G and big data

The technology behind 5G and big data are coming into place. But onboarding these technologies without fundamentally changing how you understand and access your networks will only build obstacles into your digital transformation. Here are some essential steps to preparing for the next industrial revolution:

1. Create a transition team

Assemble an internal team representing all parts of the company to take the lead in creating a delivery plan, budget plan, resource analysis and strategy and to spearhead the communication internally. Include executive leadership and business leaders, as well as technology specialists to secure buy-in from the top down. Appoint a solid and experienced leader and, if necessary, add a new position. The delivery plan should include resource requirements and the criteria against which success will be determined.

2. Determine a budget

While a well-strategized 5G and big data investment will yield cost savings in the long run, you'll need investment in the shorter term to realize those savings. Explore the expected costs of 5G equipment (both networking and devices), as well as other infrastructure based on your organization's specific situation and requirements. Develop the most detailed plan you can, considering increased cloud service fees and other services, sensors and tags, IoT devices, training costs, and more.

3. Be a student of 5G

Stay on top of new technical developments on 5G and big data and related technologies as they emerge. Consider all possible solutions, then narrow down the options based on your own circumstantial criteria, including industry, budget, scalability and specific goals. Explore specific use cases for 5G, big data, AI and MEC in your industry and among your competitors. Communicate and evangelize what you have learnedacross the company to generate excitement about what's possible with advanced networks.

4. Strategize

Start with a vision that's based on big-picture goals for the business. Focus on best-case scenarios, such as: What does the best possible customer experience look like? What new markets could we enter? Where do we want the organization to be in 10 years?

Perform a comprehensive review of your current business and larger business strategy, and estimate what's possible in the new world of advanced networks. Establish key performance indicators (KPIs) and potential growth opportunities. Focus on the "why" and review each area of the business and what's possible with 5G-enabled AI.

5. Upskill your team

A successful 5G and big data plan starts with bringing in the right skills through training, hiring, partnering or some combination of the three. You'll need serious skills in network architecture design, big data processing and probably more programming skills.

6. Review your network design

Think about redesigning your network to support massive quantities of unstructured data with intelligence and data processing as close to the edge as possible. Think through issues with legacy systems. Fully embrace the MEC network architecture to radically drive down latency across the fullest-possible spectrum of network activity. Plan to take advantage of the ability to connect tens of thousands of IoT, mobile and other devices within a single area with 5G and big data. 

7. Onboard key partners

A managed services partner can play a major role in developing the architecture for and implementing your next gen infrastructure, bringing expertise and experience to the incredible transformation ahead. Bringing the right partner in early can also add the expertise you need through all stages of the process—helping you choose the best technologies, follow best practices, and assess costs, risks and quality-of-service issues for the solutions under consideration.

Learn more about how AI-enabled analytics can streamline operations and improve the customer experience.