Big data has become integral to business growth for many enterprise operations in a broad range of industries. Used to its full potential, big data goes well beyond analytics to provide actionable business intelligence that can then be leveraged to make real-time business decisions that can give you an edge in today’s ultra-competitive business landscape.
The challenge arises from the voluminous amounts of data the enterprise outputs on a daily basis, as well as the speed at which that data is created. In addition, the types of data that can be attributed are becoming more and more unwieldy.
As business data becomes digitized, new data sources will continue to present themselves, creating an unstructured glut of data that may well be useful—but for which there are not yet any algorithms to make sense of it all. With the recent explosion of IoT connected devices contributing to the noise and new data sources coming to light each and every day, IT managers need to find a way to harness the useful data and discard the rest.
Do data-driven companies perform better?
According to a study conducted by the Harvard Business Review, data-driven companies tend to be more productive and more profitable by an average of five to six percent over companies that are driven by hunch and intuition.
The reality is that the big data revolution has changed the way business is managed. Amazon, a company whose skillful leveraging of big data has managed to bury thousands of brick-and-mortar businesses, is a prime example of this. With the ability to track customer preferences and purchasing habits, Amazon was able to market their services and tailor their offerings, putting them ahead of the curve in ways that local retailers could not (at the time) fathom.
So, in essence, handling big data has worked for Amazon—but significant challenges still remain.
Big data challenges for IT managers
The challenges of harnessing big data to its greatest advantage are evidenced by a list that is commonly known as the Three V’s of big data:
1. Volume: insane quantities
Volume, in the big data sense, refers to the sum of all data produced from all sources. The amount of data generated by the enterprise is growing by the minute; the more connected businesses become with their various channels, the more options and choices that are made available to the consumer, the more numbers will continue to grow. Data comes from online business practices, from customer transactions, from social media interactions – enough to easily fill 20 million or more filing cabinets every hour of every day.
Recently, this area has seen an almost exponential gain, largely because of IoT connected devices and the mountains of data that they produce. The challenge here is to be able to extrapolate the useful data from the rest and be able to sort it into actionable blocks that will then support business decisions. It’s also going to become increasingly urgent to be able to dispose of useless data quickly in order to save money as well as server real estate.
2. Velocity: constant, escalating flows
The ability to make real-time business decisions that affect the growth and success of the enterprise is the key to big data’s usefulness. The more agile a company is, the faster they can have a solution in place or strategize based on the insights that the data provides. From retail stores to Wall Street, the faster they can apply the data to their business activities, the further ahead they will be.
The challenge for IT managers today is to find a way to not get bogged down beneath a pile of useless data. While the issue has largely been addressed through the implementation of advanced, highlycalable indexing systems, there are new types of data being produced by IoT, AI, machine learning, and cognitive applications. Where daily insights may have been enough at one time, data that is up-to-the-minute—or second—is preferable, so performance and simplicity in big data solutions is a must.
3. Variety: a wide assortment
Lastly, the variety of big data is a massive challenge. As stated above, there are many new sources of data, and they seem to be multiplying. When you consider all the various sources of data that can possibly be collected – browsing data, social network activity, customer service or help desk calls, connected IoT devices, smartphone and other device use, email, email attachments, encrypted packets, physical sales, online sales, referring sites, and all the data that is tied to a specific location – efficient ways of sorting and disseminating all this data must be constantly evolving to meet today’s needs.
Big data solutions that were introduced before the introduction of the iPhone—keep in mind this was just over 10 years ago—are no longer adequate, nor are they agile enough to scale to current data trends.
One of the problems IT managers face in terms of data variety is the ability to name newer data sets in a standardized manner. Currently, there must be constant attention paid to newer data elements and the nomenclature that refers to them. With a more standardized language to describe the variety of incoming data, it will be easier to prove ROI for big data tools that adequately address the issues of velocity and volume.
Analytics and big data
When you talk about big data, the mention of analytics is usually not far behind. Analytics provide a way to make sense of all the data, putting it into an understandable form so that value can be derived from it. Without a way to analyze all the data you output and subsequently collect, the undertaking would be fairly useless.
So, therein lies the biggest challenge for today’s enterprise IT managers: to be able to channel that data effectively in real-time – or at least as quickly as it can be realistically mined. Managed infrastructure-as-a-service (IaaS) and database-as-a-service (DaaS applications) may help to improve efficiencies in data collection and deliver the analytic one-two punch we are all looking for.
If you are doing business in Arkansas and would like to learn more about how big data can strengthen your business, reach out to Business World today, or call us toll-free at 888-981-1230 to schedule a no-obligation consultation.