The world is generating more data than ever before. It’s also capturing more of that data than it has in the past. From digital packets running through global networks to information that’s processed by smart devices on the edge of IoT setups, there’s plenty of material being churned out daily.

A report from the year 2019 estimates that about 2.5 quintillion bytes of data are created every day. This number will continue to grow, as IoT becomes commonplace and we increase our dependence on digital technology.

For most people, these figures are mere statistics. But for many organizations, they represent a vast treasure throve that they can leverage to gain unusual insights into their customers, target markets, and industries.

That’s why big data has become a thing.

What is Big Data?

The term big data refers to large amounts of data that companies receive from their various interaction points—client information, customer service, transactions, market prices, engagement on the web and social media platforms, etc.

‘Big data’ could also apply to the large amount of data that is generated by sensors on an oil rig or by smart machines at a factory site.

Companies can gather these sorts of data, analyze them, and see the trends in the crucial variables. This gives them a picture of what’s going on in various aspects of their operations and lets them make intelligent decisions based on that picture.

For instance, let’s say you have access to data on the thousands of sales made by an ecommerce store within a year. You also have information like the days, time of the day, and months in which these sales have been made.

You could analyze this data and find out things like the times of the day, days of the week, and months of the year in which sales were highest and lowest. It may also be possible to tell how these trends change over time.

These details let you know the peak purchase times. Based on this insight, you can allocate resources away from the less active periods and towards the times with higher traffic. Ultimately, you’ll be able to maximize your sales and returns from those periods.

The more dense and complex the data sets are, the more sophisticated the tools you will need to analyze the data. Besides this, you should also possess certain skills if you’re going to work on large volumes of data.

How Cloud Computing Can Help

In the old days, you could store all your data on your premises—because you weren’t generating a whole lot of it anyway. But today, you’re creating and storing more data, and you can’t hold everything at your site anymore.

This is where the cloud comes in. Instead of trying to expand your physical data centers or procure more storage devices, why not just host all that data on a cloud platform?

Any solution that enables big data computing and analysis must cater to the 5Vs of big data:

• Volume: The large amounts of data you’re dealing with
• Variety: The assorted types of data available
• Velocity: Rate at which data is collected and analyzed in your system
• Value: The importance you attach to the data based on the information that it conveys
• Veracity: Establishing the quality and credibility of data

A solid, robust cloud platform takes care of all these needs.

Here’s how.

1. Scalability

We dropped a hint on this earlier in the article.

The cloud is scalable; you can get your capacity jacked up at short notice. All that’s required is that you pay for the extra compute space. And there’s an almost infinite room you can expand into. You can also scale down if you’re past peak usage, and don’t need a lot of capacity anymore.

It’s something you want to have when you’re dealing with vast amounts of data. It lets you maintain a high level of efficiency over time, regardless of the varying volumes of data you have to deal with at  every moment.

2. Lower Costs

Many companies are wary of the large costs associated with big data analytics. But thanks to cloud computing, they have more leeway as far as costs are concerned.

The scalability of the cloud—and the subscription model that cloud service providers use –means that organizations only need to spend on what they’ll use. They can raise compute powers to take care of a spike in the volume of data they analyze and pay just the commensurate fees.

That’s better for your budget than purchasing storage capacity upfront, only to find that it’s either too small or too much.

3. Infrastructure that’s Easy to Manage

Instead of devoting large sums to CAPEX for big data storage, you can house your data on third party infrastructure owned by cloud service providers (Infrastructure as a Service, or IaaS).

You don’t have to worry about maintaining infrastructure either; the managed service provider will handle this. If it’s a competent firm, they will have experts who can fix any problems that may arise.

What you do have to watch over is the cloud environment within which you work. Thankfully, some tools can help you strengthen the visibility of your cloud and simplify the management process for you.

4. Virtualization

Virtualization is something that the cloud allows you to achieve. It involves creating virtual machines, operating systems, and servers, which can run on existing hardware. This lets you increase your data processing capacity without expanding your physical infrastructure. And that’s a boon for your big data aspirations.

Another benefit of virtualization is disaster recovery. You could lose a lot of data in the event of a major disruption to your networks. Virtualization allows you to retain virtual copies of that data, so you can carry on with them even if the original forms are lost.

5. Frees Up Resources for Innovation

Imagine working on large amounts of valuable data for just a fraction of the cost. Also, imagine having more time to do this because you don’t have to worry about cloud infrastructure. These are gains you’ll derive from cloud computing.

These gains open up even more opportunities when they combine. For instance, your team will have more time and resources to be creative with their data analytics. They can find more patterns, design more solutions, and make better decisions based on their analysis.

Find a Cloud Solutions Provider that Supports Your Big Data Aspirations 

Big data analytics is becoming a firm part of the decision making process for organizations. As your company moves in this direction, you’ll want a solution that takes the burden of managing extra infrastructure off your back.

Layer3 gives you this and more. For many years, we have provided businesses and government agencies in Nigeria with services that help them make the most of their data. From virtual data centers to disaster recovery, our products are tailored to scale up your computing capacity and keep you operating at the highest levels of efficiency.

If you would like to discuss your big data plans with experts who can support them, reach out to us here and we’ll take on your concerns.