Why big data depends on big clouds

These days, the majority of enterprises hold huge quantities of data. Find out how big clouds can help.

These days, most enterprises are sitting on a huge pile of data.

This pile could be a goldmine – or it could be a dungheap. It all depends on how it's handled. Data alone isn't good for much. But sorted and put to work, it can unlock new levels of velocity and versatility in your business.

Data resides in clouds – so the more data you have, the bigger the cloud environment needs to be. Once upon a time, a company could run everything on-premises with private hardware. Today, they mostly rent resources from public providers.

These public cloud resources are built for big data. They allow you to scale up with ease, giving you the space you need to store and run your workloads. And above all, they let you leverage these capabilities without squandering money on maintaining and upgrading private servers.

Everybody in the business world knows about the recent explosion of data. But too often, their response is to dabble in data analytics and leave it at that.

The truth is that most businesses aren't getting the most out of their big data – and this is partly because they're not getting the most out of big clouds. In this article, we look at how the two interact and help businesses to grow.

What do big clouds do?


Cloud adoption has skyrocketed over the last decade. We're now well and truly living in the Age of Cloud.

But think back, if you will, to the olden days. Chances are, your workloads ran on a server in your office – a big machine with blinking lights and spooling wires.

As data grows, these on-premises servers become increasingly insufficient. Why? Because they're extremely hard to scale up. Upgrading servers, or ripping them out and replacing them entirely, costs money and takes time (another way of saying it costs money).
That's where big clouds come in – feature-rich, scalable public cloud environments managed by tech giants like Amazon (AWS), Microsoft (Azure) and Oracle (OCI).

The key selling point of big cloud environments is that they're built for size and velocity.

First, they provide data ingestion and processing tools. Even the most hard-working IT team is unlikely to be able to sort through and categorise your data hoard. Instead, a big cloud can do the job for you – fast.

Secondly, big clouds are, well, big. These cloud platforms offer huge silos for your data using distributed file systems. And when you need more space, you simply scale up. The only consideration is how to keep your storage in line with your budget.

Then there's the question of data analytics. What's the use of all that data, anyway? Sure, it helps you stay on top of sales histories, customer profiles and the like. But if that's all you're using it for, surely a spreadsheet will do?

Big clouds often come with built-in data analytics tools like machine learning (ML) and artificial intelligence (AI). These put your data to work. They can help you forecast demand and downturns and provide a granular analysis of who's buying what and who's coming back for more.

Next up is the integrative power of big clouds. These cloud solutions come with APIs that interface between different sources of data. This creates a seamless experience for data travelling within, towards and away from your organisation.

Finally, big clouds provide big security – high levels of encryption, access control and security audits. And unlike some businesses, they also have the resources to stay on top of the ever-changing security threat landscape and adapt accordingly.

What are the challenges of big data in the cloud?

Some of the challenges of big data are the same as the challenges of data in general. Mostly, it's a matter of scale.

Big data comes from a variety of sources. Payment processing. Warehouse systems. CRM systems. Even IoT sensors. Without big clouds, the sheer scale of data can be a problem.


Secondly, there's scalability. Data can fluctuate and your cloud system needs to be able to adapt. Luckily, most big clouds from public providers are easy to scale.

Thirdly, there's the need for data to turn into insights. Without this capacity, you can easily lag behind your competitors. Big clouds work best when supplemented with ML and AI tools to help you process and instrumentalise your data.

Finally, there's the rise of remote work and the security challenges it introduces. More and more devices join and leave your networks from more and more locations. You need a big cloud with the functionality to deal with this level of complexity.

What are the benefits of big clouds for big data?

If you've got a lot of data, you need a lot of capacity to handle it, store it and put it to work. Big clouds let you do this with scalable resources and easy-access analytics.

It also removes the need for upfront hardware costs. Resources can be provisioned and adjusted at the click of a button – no disruption, no delay.

Finally, big clouds let you make better decisions driven by data. In a saturated marketplace, this can be the difference between treading water and accelerating your ambitions.

How to effectively deploy cloud-based big data solutions

So, that's what big clouds are for. But how can you be sure they're deployed effectively?

You need a vision – and you need to map that vision onto clear, actionable, measurable goals. If you can't answer the question, "What is this cloud solution for?", you're probably on a hiding to nothing.

You then need to assess your existing data infrastructure and choose the right provider or providers for the job. All the while, you need to align these technological goals with your bottom line.

It's a tricky business that requires a lot of strategic thinking and cloud expertise. You may find that a cloud consultant can help you unlock the benefits of big cloud environments.


If that sounds like you, why not get in touch with Ascend Cloud Solutions? As a trusted cloud consulting firm, we'd love to help you deploy a big cloud environment and make your data work for you.