The five Vs of big data

No matter how big or small your business is, you probably use just a fraction of the data you accumulate.

A massive 2.5 petabytes of data are generated globally each day, adding to the ever-growing magnitude of 2.7 zettabytes currently sitting in data warehouses and silos all over the world.

To put that into context, if every gigabyte in a zettabyte were a kilometer, it would be the equivalent of 3,510 trips to the moon and back.

As you continue to amass data, the prospect of actually organizing and tapping into that resource can be daunting, almost as though you’re experiencing information overload.

But fear not—with the right cloud providers and tech talent on your side, big data is a beast you can not only tame, but use to your advantage.

Big data and AWS

AWS offers its customers a wide range of fully integrated cloud tools and services that allow you to create, secure, and deploy big data apps.

Using AWS means you don’t need to get your hands on expensive hardware, and you can leave all the infrastructure upkeep and scaling to your provider, allowing you to use your company resources more efficiently.

AWS continuously updates its big data offerings and rolls out new products, so customers are always able to tap into the latest tech without the burden of long-term investment commitments.

Getting the most from big data is all about having the right tools to handle storage, analysis, and visualization. Once you have the first building blocks cemented in place, you’ll have the capacity to begin extracting insights from all your incoming datasets.

However, if you feel that your business hasn’t yet been able to harness the power of this technology, then understanding the five Vs of big data could be the first step towards your business becoming a big data aficionado.

The 5 Vs of big data

Big data: Volume

Volume

If you’re in the first stages of big data implementation, you’ll quickly learn that your business is going to need more storage.

As you begin to unleash the power of big data, you’ll discover the data streams connected to your business will grow exponentially—this constant influx of new information is great for feeding and improving your analytical processes, but you’ll need somewhere to put it all.

Previously, database management systems were sufficient to handle and organize all of your datasets.

However, the introduction of big data has slowly seen these methods become defunct; to cope with increased data streams, businesses today have started to invest in off-premise storage facilities and new network infrastructure.

The need for additional storage is one of the major issues your business will encounter when introducing big data practices and principles.

Not all data will need to undergo strategic analysis or provide you with actionable information, but data can surprise you.

You won’t really know what’s truly useful until you start putting analytical processes in place, so make sure you allow yourself enough space to harvest it.

If you decide to start collecting voluminous amounts of business data, you’ll have more data to analyze and derive insight from in the future.

Plus, today’s cloud storage solutions are cheap and massively flexible, so you can scale your storage capacity up and down as needed without worrying about wasting resources.

Our advice? When it comes to data of this scale, invest in new storage solutions to suit your business.

Big Data: Velocity

Velocity

Since big data is collected in such massive quantities, you don’t just need space to process it properly—you also need speed. It’s no longer just about how much information you collect, but how fast you can use the data to make business decisions.

Traditionally, an organization would have to wait for data to be analyzed and interpreted.

But now, with the continuous stream of incoming data, it needs to be processed and digested quickly.

If you don’t work fast enough, you’re going to end up with an enormous backlog of information; given how fast the business world moves, that hard-earned information might be useless by the time you get it.

Your business will receive data feeds from tons of sources, many of which will be generated by real-time processes.

Once this data has been collected, you’ll get a sneak peek into customer behavior, operational needs, and cybersecurity threat, empowering you to make data-based predictions and take the action necessary to drive your business forward.

One sector that’s truly embraced data processing at speed is the financial sector. By analyzing data quickly and efficiently, the industry has seen major advancements in cybersecurity protections.

By processing customer transactions in real-time, big data security algorithms can instantly detect fraudulent activity, saving huge amounts of time and money in the long run while protecting sensitive information.

Big Data: Volume

Variety

From social media platforms to CRMs and IoT devices, you’ll certainly be spoiled for choice in terms of the data your business can utilize.

Your business already sources data in a number of ways, but with the addition of new devices and new points of contact with your customers, you’ll be in a position to extract more-profound meaning from the information you collect, which will give you a fuller picture of both your own operations, and the activities of your clients and customers.

This unstructured data is extremely valuable, but it will take work to extract useful insights from it.

The business data that’s easy to understand at a glance is just the tip of the iceberg; the other 90% of that data will need a team of data engineers (or at the very least some top-notch analytical software) to organize it before it can be properly analyzed by data experts.

In the world of big data, this lack of structure is fast becoming the norm, so if you’re looking to expand your use of big data, it’s something you’ll need to account for.

Luckily, there are ways and means to process these oceans of unstructured information, either through investing in big data analytical platforms or hiring data professionals.

But, with the right analytical set up in place, these new types of data can supercharge your business growth, allowing for the movement into previously uncharted territory.

Big Data: Veracity

Veracity

Using big data and the insight it provides to improve company performance should be a crucial part of your business strategy.

But to really benefit from this practice, your data needs to be truthful.

As the saying goes; garbage in, garbage out. Only if you have complete faith in every data source your business collects from can you rely on the reports that come out on the other side.

Volume, velocity, and variety of data provide a crucial foundation on which to build your data lake, but the amount of data you have and the speed at which you generate it mean nothing if that data isn’t accurate.

> Why do I need a data governance strategy?

To make sure your data is accurate (and therefore useable) you need a data governance plan.

If you’re delving into big data, you’re going to have a lot of information to process.

A data governance plan will help you verify the accuracy of your data streams, and introduce accountability and actionable steps to take if your data quality isn’t up to scratch.

You need to be able to trust your data to provide a foundation you can base quick, confident decisions on, but that’s easier said than done.

Why? Well, when you open the door to additional data sources, data quality can take a hit without proper attention, which can damage your decision-making process.

To be truly effective, your data governance strategy needs to be baked into your company culture, with every corner of your business working closely with your data team as a united front in a singular, cohesive effort to keep your data clean.

For these practices to roll along smoothly, your business may need to bring a data steward on board who’ll see that all guidelines are followed during collection.

They’ll also educate the wider business on best practices, resolve data issues, and make sure your strategy stays up to date with changes in data regulation and new security practices.

Big Data: Value

Value

Every business decision you make should be data-driven, but these decisions won’t be based on the raw data itself.

Adapting data to suit your business needs will clear the way for you to unlock the hidden potential in the information you’ve collected, which means you’ll get the most value out of your data.

This is where the five Vs of big data come together: volume + velocity + variety + veracity = value. 

volume + velocity + variety + veracity = value

To unearth this value, you should have a dedicated big data team in place that can help you make your way through all five Vs.

Once you’ve got your expert team together, the analysis can begin and your data will be closely scrutinized before it’s formulated into reports by a visualization expert.

That way, people across your business can understand the value of the data presented.

No matter how you choose to process your data, it’s all about surfacing the right information and transforming it into actionable business insights.

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