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How Small Businesses Can Embrace Big Data It's possible to analyze large information sets to boost product quality, improve marketing and further customer relationships -- all without a huge price tag,

By Joanna Schloss Edited by Dan Bova

Opinions expressed by Entrepreneur contributors are their own.

Regardless of the size of your company, chances are you've heard of big data. Technically speaking, big data is a reference to data sets too large and complex for companies to manage within their traditional IT systems.

But a look past the technical jargon will reveal that big data is about opportunity -- the opportunity to learn from your company's data in order to make smarter business decisions. And while it may come as no surprise that large, enterprise companies are taking advantage of the opportunity that big data affords, some entrepreneurs may not know that small businesses can do the same.

If you're the owner of a small business, your ability to succeed in the face of larger competitors has likely been driven by your personal intuition and ability to provide a superior service. But big data is changing the business landscape.

Chances are some of your competitors -- large and small -- are using big data to enhance product quality, improve marketing operations and further customer relationships. This newfound efficiency of your larger competitors can be a very real threat to the sustainability of your business. But what if you could turn the tables on them?

What if as a small retailer, you could analyze the relationship between social-media conversations and buying trends to quickly capitalize on emerging sales opportunities?

Or what if, when launching a new online service, you were able to analyze your site's visitors and track how they move from page to page so as to understand what engages them, the things that turn them off and detect promotional and cross-selling opportunities?

Some believe that big-data analytics projects are too costly and complex for a small business to take on. Indeed most of the analytics solutions on the market were built specifically for larger enterprises, making them costly and complex to implement.

Plus, some solution vendors targeting larger businesses probably don't understand the needs of small companies. Enterprise-software-solution vendors like to tout economies of scale, whereby a huge up-front investment is offset when an application is rolled out to thousands of internal users.

This is meaningless to the owners of small businesses who are focused on simply finding the right tool for the right users quickly so as to accomplish more work done faster.

Fortunately, with big data now on the minds of everyone, new solutions are coming to the market each day and some have been created for the specific needs of smaller businesses.

Here are three characteristics small businesses should seek in a big-data solution:

Related: Celebrating the Freedom to Make Data-Driven Decisions

1. Flexibility and choice

Big-data solutions targeted at large enterprises are typically an all-or-nothing proposition, requiring customers to gut existing systems, thereby imposing a heavy cost and time burden on information-technology departments. This simply doesn't work for small businesses.

When the marketing department of a small company needs a marketing-automation system, it typically acts independently of the IT department, laying out its requirements, cost justifications and system requirements and then researching and choosing the best solution to meet its needs.

As a result, small businesses regularly deploy a variety of solutions throughout the organization, including desktop software for business tasks, a software as a service solution like those of Salesforce or Workday for marketing or HR, a public or private cloud for development and perhaps some custom-built solutions to meet specific needs. This leads to an environment with many different types of data.

A big-data solution for small businesses must allow them to choose only the capabilities they need and leverage the solutions and systems already in place.

The solution should be complete in having everything a customer might need in one pre-integrated package, but the vendor shouldn't force a company to replace a capability it already has implemented and adopted.

Related: How to Make Predictive Analytics Work for Your Business

2. Simplicity

A big-data solution for small businesses should be easy to deploy and use and take only a few days or weeks for a company to start using it -- not months or years. All the capabilities of the system should work together seamlessly. And if the customer is integrating new capabilities with existing systems, it should be possible to accomplish this without the need for expensive specialists.

In addition, the system should not require staffers to undergo a lot of training and should include self-service capabilities so a broader audience of analysts and business users can use it without the need for the IT department to become involved.

3. Cost

Finally, a big-data solution for small businesses must be priced right. Customers should be able to pay for only the capabilities they need, and the licensing strategy should allow them to start small and scale up as the need for analytics increases. This approach is particularly useful for a rapidly growing small business, where it's critical for the cost and capabilities of software investments to align with the rate of growth and expansion of the operation.

The transition from an intuition-driven company to an analytics-driven company is one small-business owners can embrace. Finding the right IT solution, one geared to the specific needs of the small business, can help make it practical and affordable to benefit from the opportunity big data affords.

Related: Overcoming the Challenges of Data Analytics

Joanna Schloss

Business Intelligence and Analytics Expert, Dell Software

Joanna Schloss is a subject matter expert at Dell's Center of Excellence specializing in data and information management. Her areas of expertise include big data analytics, business intelligence, business analytics and data warehousing. Within the Dell Center of excellence, she helps clients deal with the challenges of managing multiple data platforms, applications systems and analytic environments.


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