When it comes to managing big data, it may well be worth remembering the old saying that “if the mountain won’t come to you, you must go to the mountain.”
Indeed, spending on big data technologies continues to rise, and with good reason. Most markets today are highly competitive—and mature—making it difficult for companies to differentiate themselves; big data technology makes it possible for them to discover insights based on data that can lead to new products or approaches to customer service providing that very differentiation they seek.
Source: Oracle
Rather than hunting for what he refers to as the “mythical data science unicorn,” companies should instead form shock troops of “citizen data scientists”—business analysts they already employ, armed with tools allowing them to act as real data scientists.
The profile of this unicorn is pretty rare indeed: an advanced degree in statistics plus very strong programming skills and familiarity with machine learning are table stakes. Demand for this kind of talent is far greater than the supply: According to McKinsey, by 2018, demand for data scientists will outstrip supply by more than 50%.
The other challenge for companies looking for big data success is that even if they do hook a unicorn, their mythical beast of burden is likely to be yoked to a heavy plow of bad-quality data and cleanup rather than bouncing innovation on the tip of its magical horn. So much of the data involved in big data projects are messy, and come from a variety of sources and inputs, that highly paid data scientists can spend up to 70% of their time doing data cleansing work like converting names in lower case to upper case, says Lynskey.
This is where the right tool can really help. With no coding knowledge required, citizen data scientists can up a company’s big data game with Oracle Big Data Discovery Cloud Service, which provides easy-to-use wizards, a point-and-click user interface, and the compute power of Oracle’s cloud to perform as many calculations and permutations of a problem as needed.
It’s “very business-user-friendly,” says Lynskey. “We can do machine learning in the background and then just present smart results to them.”
Even companies that do employ real data scientists can benefit from the work done by citizen data scientists. With so much data scrubbing required before a Big Data project can get off the ground, “the joke is the data scientist has been turned into a janitor, and you don’t want a PhD doing janitorial work.” Using Oracle Big Data Discovery, “companies can leave what we call the data wrangling to the business analysts, so their data scientists can go and do the more advanced analytics.”
For many companies, successful big data projects can be the difference between thriving and merely surviving (or not). Customers are ever-more demanding, and competitors aren’t standing still. All the more reason to enlist citizen data scientists as adjuncts to professional data scientists; as Lynskey says, “Big data is a team sport.”
For example, European research organization CERN uses Oracle Big Data Discovery to enable users to analyze data from a wide range of data sources in the organization’s quest to better understand the universe.
Obviously, most company’s big data strategies are focused on more earthly topics such as better understanding customers, creating new products or services, decreasing employee attrition, identifying transportation issues, or identifying reasons for hospital readmission rates. And that’s not even tapping the surface.
The potential of being able to spin up an instance of Oracle Big Data Discovery Cloud Service to tackle these and myriad other issues gives companies of all sizes the opportunity to gain the insights they need for a competitive edge—without big upfront costs or an in-house data scientist.
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