big data

Do Small Businesses Need Big Data?

In almost every industry in the world today, it’s difficult to escape discussions about the role of data in helping companies attain growth.

Data is everywhere – in the phones we use, books we read and even the websites we visit.

The right kind of data can help companies make crucial business decisions, increase revenue, design products to fit specific needs, streamline operations and forecast the company’s health.

By definition, big data isn’t very different from normal data, save for the fact that there’s a lot of it moving really fast.

Due to this, implementing big data plans require high-level of strategic planning.

And this is where the small corporations fail and sometimes, even the large ones.

It does, after all, represent the culmination of advancement in technology that’s been a decade or more in the works.

New technology comes with the burden of exorbitant pricing, lack of sufficient skills and a general lack of resources such as manpower and money.

These bottlenecks may have had their place in the tech industry five or so years ago, but no single company or individual can maintain a monopoly on technological advancement for very long.

The ability to use big data and the benefits that come with it have slowly become widespread, so that small to medium businesses (SMEs) can now enjoy most of the benefits big data has to offer.

The Big Data – Small Business Divide

Big data hasn’t traditionally been an area that small businesses have explored.

Then again, big data as we know it is nearly two decades old, and yet it has seen more change than a lot of sectors are able to deal with in such a short span of time.

The three main obstacles that slowed adoption were high storage costs, lack of data and problem with processing large amounts of data.

The inability to process large amounts of data was the first problem out the door, with Google’s MapReduce paper giving birth to Hadoop in the early 2000s.

Naturally, with the means to collect data, the amount of data available quickly grew.

And finally, competition between hardware vendors drove processing and storage costs into the ground during the following years. This effectively saw the birth of big data, and with it, the data age.

The stage had effectively and rather dramatically set for the use of data as a weapon to enable companies to come out on top.

With the stage set, new products such as Spark, BigQuery and Storm began to emerge.

Add on top the now dirt-cheap cloud infrastructure that saw similar growth back then, small businesses have basically no real excuse for not using big data.

Why Do Small Businesses Need Big Data?

The mid to late 2000s saw a radical shift in how companies monetize their products.

They moved away from focusing on complex protocols and processing speed, instead of shifting their attention to the newly-available petabytes of data.

Large corporations like Yahoo were fast to adopt solutions like MapReduce and Google even later produced their own Google MapReduce, which would go on to birth BigQuery.

Small companies are still expected to compete with companies such as Amazon, despite only 23% of companies  taking advantage of the benefits of big data.

Cheap cloud Infrastructure means that to adopt Spark or Hadoop in their stack, companies don’t necessarily need a managed solution like BigQuery.

They are free to host whichever platform has the most potential.

It’s crucial to pick the right platform for the job, considering just how many there are in the market today.

Questions you might have to contend with include: How is Hadoop different from spark?

Is Hadoop friendly for small businesses, or will you need something easier to manage like Ceph?

To be successful, small businesses need to use the same set of tools that large corporations use, if not better ones.

Big data presents an opportunity to create what could be the competitive edge that small businesses need to make the leap to medium businesses, and the latter to large enterprises.

Key advantages of using big data for a small business include:

Faster Availability of Insights

Distributed computing has made inroads in the tech industry because it helps companies do more in less time.

Traditional methods for analyzing data, which almost always involve a transactional database, aren’t able to offer the same kind of speed-optimized analytic solutions that big data options can grant users.

At some point, sticking with traditional solutions becomes more expensive and less effective than what new technology offers.

Any small business with a vision for a data-oriented future should assess the viability of big data platforms and the role they could potentially play if adopted.

Providing Customer Insight

Business decisions are almost entirely driven by market forces.

Imagine having information about how much a person using your platform is likely to spend, at what point they are likely to drop out of the sales funnel and how likely they are to return.

All this information and more can be gleaned from the abundance of data about spending history of previous customers and how they interacted with your website.

With the data collected from your site, the most obvious challenge – collecting data – is eliminated.

A common sentiment raised by small businesses is a lack of specialized manpower to plow through the complexities of setting up a data analytics platform.

The truth is, most businesses don’t need to build complicated software or hire a dozen data scientists to get customer insights from data. Once the data is collected, all that’s left is picking the right platform for the job.

Improve Marketing Campaigns

Big data allows for the creation of customer profiles, which allow businesses to more easily customize marketing campaigns to make them personal.

Personalized emails stand out in a customer’s inbox as highly-relevant content and are 26% more likely  to be clicked than regular emails.

Perform Risk Analysis

Big data gives small businesses the power to comprehensively analyze the amount of risk associated with various business ventures.

In fact, some machine learning models could even suggest viable solutions for the problems.