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Every two days we create as much data as we did from the beginning of time until the year 2000. That's according to business author Bernard Marr.
As a small business owner, you might be collecting data on anything from the number of people visiting your website to what products in your online or physical store are selling the best and perhaps even the buying preferences of your customers.
Data can help you determine which online marketing content is most effective, what products to stock up on and which to phase out and even which customers to send email or text messages to when their favorite items go on sale.
With this explosion of data and nearly limitless storage capacity, businesses of all sizes have the potential to extract greater business intelligence than ever before. However, for data to be valuable, you must harness it. Businesses must collect data, process and analyze it, and tease out insights from it.
When you do that, plain old data transforms into "big data." But there are some challenges when it comes to big data. The challenges are manageable -- just know what you're in for.
Identifying sources of data
Your business is generating more data than you might realize. Has anyone in your organization taken the time to identify and gather data in a centralized way?
In most organizations data is scattered and siloed. It's in multiple software applications. It's in different departments. It's in a wide range of media and formats (audio, video, text, images, spreadsheets, databases, sensor data).
The first challenge is figuring out where it is, what's valuable, and how to bring it all together.
The price of storage has dropped dramatically in recent years. But price is only one of several storage concerns. First and foremost, think about scalability. A flexible cloud solution that allows expansion as your data grows is a great solution.
Ask these three questions: Does your storage solution simplify the data collection process? Does it accommodate many formats of data? Does it store data in a manner that enables easy analysis later?
Ensuring privacy and security of data
The more data you have, the greater the responsibility to keep it secure and protect the privacy of customer data or confidential company data.
You need robust technology for security. But that's only one level of protection.
Data governance policies and best practices are also essential to make sure data is handled securely by employees. Legal requirements such as the new GDPR requirements covering data of EU citizens places even more responsibility on businesses.
Make sure you have reliable vendors with strong security and privacy practices. Businesses in industries that are regulated or subject to higher standards of data handling, (e.g., health care, law, and financial) must be especially diligent. It's also good to revisit your insurance coverage for cyber liability.
As datasets grow larger, it becomes harder to manually process and draw insights from data. So, you will need some level of computerized processing. To use a simplistic example, imagine trying to work on a spreadsheet with millions of columns and rows. It wouldn't be feasible. But a computer can compile and process that same amount of data (and much more!) in a fraction of a second.
Artificial intelligence and machine learning make big data truly usable. Machine algorithms process data far faster and in far more detail than humans. The result is deeper insights and predictive learnings based on data patterns that would have been nearly impossible to spot by humans.
Applying data to business needs
Last but most important, is the challenge of applying data insights to your business needs. Businesses have to develop big data competencies and skills. For instance, you may have a lot of data, but do you and your people know how to use it? Do you know what data is most important to your business? Do you know how to interpret the data and apply it business problems? Do you know which charts and graphs to create, and who needs to see them in your business?
Big data is delivering real-world results for businesses of all sizes. But like all tools, it has to be implemented properly to offer the best results.