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It drove the 2012 presidential elections. It can do everything from predict and improve student performance to help retailers increase operating margins by 60 percent and create $300 billion in value in the health care industry. Big Data may sound like the latest buzz word that only the big guys get to use, but it can help small businesses without an IT team or with a small IT budget run a better business, too.
Think of Big Data as this rich explosion of information you’re storing, one that you can dig through to uncover invaluable insights that will help you make better, more profitable business decisions.
Paula Long, CEO and co-founder of DataGravity, an early-stage company with a mission to turn data into information, describes Big Data as data intelligence.
“Big Data doesn’t have to be big in size,” Long said. “We’re not really talking about the size of data. We’re [asking] if there’s information that can help you run your business.”
These insights can tell you things such as whether or not customers are happy and identify any problems. It can also recognize any patterns that are occurring and show you other areas you should be exploring.
Big Data can also help small businesses evaluate the effectiveness of marketing campaigns. ClickFuel, which offers marketing analytics services to small businesses, sees Big Data as an opportunity for growth and as a pathway to making well-informed marketing decisions.
“Many SMBs will sit in the middle of information flows instead of doing something about it,” said ClickFuel CEO Steve Pogorzelski.
“Data-driven marketing is when companies can pull information that allows them to analyze their organization’s Big Data and use the necessary information to market to the right audience,” Pogorzelski said.
It distributes this data throughout the organization, putting them in the right hands. In practice, this data should go from management down to the field, such as on-the-ground sales people who can use these insights to increase sales.
Long predicts that, over the next two years, data intelligence will become more valuable at the higher levels. Small businesses will also want that value, but just can’t hire a data scientist to extract it.
The cost of Big Data
Big Data isn’t cheap. Not only does it require highly specialized skill sets, but it’s also a labor- intensive process that consists of multiple stages. It starts with an assessment of the kinds of data the company currently keeps and what types of information it wants to find out. Combined with the actual mining, analysis, and any additional tools or services companies may need to purchase, Long estimates that data intelligence costs about $150,000 to $200,000. There are also ongoing costs to continue to mine for and analyze data, as well as every time the data changes.
Because it requires a huge investment of time and money, Big Data may seem inaccessible for those with a limited IT budget or no IT team, but there are two types of affordable Big Data solutions for small businesses: data-science-as-a-service providers and third-party software.
For small businesses that don’t have an IT department, data-science-as-a-service providers may be the solution for you. Here are a couple things to consider:
Do you want to work with data analytics consultants that are part of larger consulting firms or would you prefer to work with an independent practice that focuses solely on Big Data? The latter is typically the cheaper, more SMB-friendly option.
Next, evaluate the different services they provide. While they may all look like sound investments, you don’t need the entire package. To start, figure out which single service will give you the main answers you’re looking for. For instance, Steve Kearns, DataGravity’s director of product management, says that some data consultants offer specific services such as search engine analytics. They’ll use their own search engine to mine for data and then analyze it using their own search metrics.
Ben Lorica, chief data scientist and researcher at O’Reilly Media and an editorial board member at Big Data Journal, also recommends DataHero and Kaggle, which uses crowdsourcing to extract and analyze big data.
For small businesses that have an IT department, but a limited IT budget, Lorica also recommends the following services:
- Cloud services like Birst and GoodData (for visual analysis and reports), Amazon Redshift and Google BigQuery (for interactive query analysis), Google Analytics (free, scalable, Web analytics)
- Public data sets (e.g., U.S. Census) or data services that are publicly available (e.g., http://www.google.com/trends/)
- Visual analysis tools (Tableau, Datameer, SiSense, QlikView) that run on laptops and can even crunch surprisingly large data sets. There are also some machine-learning and statistics tools that do the same (GraphChi, SkyTree Advisor).
If you decide to do everything in-house, keep in mind that you’ll need IT people who can learn whatever service you decide to use. If your IT team isn’t up for the job, avoid making a very expensive mistake and hire outside consultants.
Another costly mistake businesses make is misusing and misunderstanding the concept of big data. Big data is all about figuring out the kind of data you have and knowing the right questions to ask.
“Results are only going to be as good as the data they have,” Long said. “A lot of them come into this thinking they can construct fairly complicated questions about the data, but they don’t really have that in the data itself. For example, they’re looking for patterns and there may not be any. Because they don’t have any insight in what they’re storing, they don’t really know what they couldask.”
To get the most out of Big Data, Long advises companies to be strategic in their approach.
“First you want to do an assessment of what you have for storage and what you’re keeping. You want to be very crisp about what you want to glean from the data and sort of put together a map. Then go talk to a consultancy agency and say, ‘Here’s the kind of data we’re storing and here’s the kind of questions I want to ask.’”
You can have all the information you want, but if you don’t know the right questions to ask, Big Data won’t get you the results.