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If you're involved in a business that uses or intends to use analytics to make better decisions, you've undoubtedly heard of big data. But what is big data, exactly?
Big data represents massive amounts of information. The data can represent information about your customers, their preferences and actions or about your organization's internal processes, inventory or anything you need to track to make more informed business decisions.
Due to its volume, big data is often perceived to be more reliable than smaller data samples. But the volume of sample sizes isn't the only benefit of big data. The “4Vs" of big data represent the benefits big data can offer to businesses. These include volume, variety, velocity and veracity.
If you're ready to start making more informed business decisions and receiving more accurate insights, your initial big data management action items will simply be how to get started. These steps can help guide you through the process:
Explore your data collection potential. You'll want to make sure you know the type of data to collect, where you can find it and the preparation it may need once it enters your platform. It may need to be sorted, cleaned or enhanced, and you'll need to determine the right tools for the job. When managing big data, most companies make the transition from spreadsheets to IT systems designed for big data management.
Take an agile approach to big data management. Create your team, which should include developers to deploy your chosen platform, data analysts and a project manager to ensure efficient operations. Run a “proof of concept" test with a small sample to ensure your project will be manageable and provide the data you need.
Choose and deploy a big data platform. Numerous platforms exist to help businesses collect and manage big data. Your team should work together to help find the best one for your organization and then deploy it.
Determine your storage methods. The storage you choose will depend on your performance requirements, infrastructure and budget.
Commence data processing and analysis. What are you looking to discover from the data? You'll need to specify data correlations to aid the predictive algorithms.
Use data visualization tools to help achieve actionable insights. A data visualization format—a graphic representation of big data—helps decision-makers view and understand the analytics.
Having access to copious amounts of data brings another organizational question: How to best manage it all.
Business leaders need to ensure the data will be safe, secure and quickly accessible. Three methods of storing big data stand out above the rest.
Constant encryption. You can store big data on local servers if you use constant encryption, making the data less vulnerable to a cyber attack.
Warehouse storage. Many organizations choose to outsource big data storage, putting the responsibility on a company with the infrastructure to securely store their data.
Cloud storage. Cloud storage puts all your data in the hands of a third party, securely stored on a Web and always accessible from any internet-connected device. It's similar to warehouse storage, except you will never see the physical location and your data is constantly backed up.
In addition to determining how best to store your data, big data comes with a set of management challenges. Understanding these challenges could help your organization learn ways to meet them using these strategies:
Find big data storage solutions that are scalable. The sheer volume of big data that makes it so helpful to organizations also introduces storage and analysis challenges. Compression and de-duplication can reduce the size of the files, but sorting and analyzing data requires the right tools as well. The amount of data continues to grow, which means companies must continue to scale their storage and analysis tools.
Analyze data quickly. If we think back to the 4Vs of big data, velocity—the speed at which organizations can accumulate and analyze data—is the most crucial. Converting big data into actionable insights quickly continues to be a challenge.
Enlist the help of big data management experts. As with many fields of technology, recruiting and retaining talent to implement big data projects, manage and analyze data can be a challenge.
Verify data. Another nod to the 4Vs of big data, organizations must find ways to test the veracity—or validate—the data.
Many big data management challenges can be overcome by following best practices for managing big data analytics programs.
Define your goals. What do you wish to accomplish through big data analysis? What are your Key Performance Indicators (KPIs) in this area?
Determine the data needed to achieve those goals. Having access to massive amounts of data doesn't always mean you have the right data. Determining what data points you want to collect before you start could save your organization time and money.
Start slowly. Because you're always assessing and adjusting, ease into your company's big data adoption. Test methods as you move forward, using an agile project management process that enables you to make adjustments as needed.
Evaluate and evolve your technology requirements. As your big data needs change, make sure your platforms, storage and analysis tools fit your needs.
Collecting, managing and analyzing big data may seem like a lot of work, but the positive impact of big data in business can be tough to ignore. Big data could be important for businesses who want to stay ahead for a number of reasons, and the business insights offered can be used in a number of ways:
Gauging brand sentiment and competitive positioning. Use big data to see how consumers and users feel about your brand and allow it to help you determine how you stack up against competitors.
Gaining marketing insights. Which email campaign was most successful? Which social media ads get the most clicks? You could find valuable marketing insights in big data analysis.
Targeting and remarketing initiatives. Today's businesses must stay in view of consumers more than ever, touching them at different places in the buyer's journey through different challenges. Big data help make it possible to run more accurate retargeting campaigns.
Helping to ensure customer satisfaction. The four elements above could potentially lead to greater customer satisfaction and enhanced profitability through repeat customers and word-of-mouth referrals.
As businesses continue to use big data, its findings and usefulness will likely expand although also will the risk for breaches and cybercrime. Even so, the tools used to store and analyze such data may gain greater sophistication. And, as artificial intelligence evolves, analysis that reveals valuable business insights may continue to emerge.
In addition, predictive analytics may help business owners make informed decisions ahead of marketplace changes. From QR codes on store shelves that monitor inventory to store kiosks that track customer behavior, the Internet of Things may begin to play an even greater role integrating data collection with real-world action for more accurate inputs.
All such advancements point to the potential of those organizations committed to using big data to hone in on the insights they need to grow and flourish.
This article is intended for general informational purposes only and does not constitute legal advice or an opinion on any issue. It should not be regarded as comprehensive or a substitute for professional advice.
