By: Lauren Landry
Big Data has swiftly earned a lasting place in our lexicon, because its potential is real and impact undeniable. Companies can collectively scoff and brush big data off as just another trend, but that decision could lead to worse decisions down the road.
“Every era has a bold new innovation that emerges as a defining advantage for those who get out ahead of the curve,” said Ali Riaz, CEO of enterprise software company Attivio, referencing the industrial revolution and, later, the information age. Giants of industry who took advantage of new machinery or market leaders who learned to leverage relational databases have historically had the upperhand.
“Today’s advantage — the new currency, if you will — is big data,” Riaz added. “Companies that don’t get ahead of this tsunami by using big data to their advantage will be crushed by it.”
Yet, this deluge of data isn’t new, it’s just been given a catchy two-word title.
When asked to define big data, Ely Kahn, co-founder and VP of business development for big data start-up Sqrrl, described it as massive amounts — tera- and petabytes’ worth — of unstructured and semi-structured data “organizations have historically been unable to analyze because it was too expensive or difficult.” With technologies like Hadoop and NoSQL databases surfacing, however, Kahn claimed those same organizations can now make sense of this type of data “cost effectively.”
To Marilyn Matz, CEO of fellow big data startup Paradigm4, the revolution goes beyond just high volumes of information, though.
“It is about integrating and analyzing data collected from new sources,” Matz said. “A central capability this enables is hyper-personalization and micro-targeting — including recommendation engines, location-based services and offers, personalized pricing,
precision medicine and predictive equipment maintenance schedules.”
No matter the industry, big data has a key role to play in moving the needle for companies, whether large or small. And that goes for companies currently unable to determine what their “big data” is. The unrecognizable could be customer sentiment in social media, server logs or clickstream data.
“Once you have identified untapped sources of data,” Kahn said, “you can use tools like Hadoop and NoSQL to analyze it.”
Matz broke down, by industry, what that ability to analyze could mean.
In the Commercial Sphere
In the commercial sphere, if a company knows 10 or 100 things about you and your situational context, then that company can do a far better job offering you something relevant to exactly where you are and what you might be interested in, increasing their opportunity to capture your respect, attention and dollars.
In the Industrial World
In the industrial world, if a manufacturing company knows where equipment is operated (hot and harsh climates versus moderate climates), as well as how that equipment is being used (lots of hard-braking) and collects data across a large fleet, then it can predict maintenance before costly breakdowns, saving millions of dollars — and it can price warranties more accurately, as well as improve designs and manufacturing processes.
In Pharma and Healthcare
In pharma and healthcare, evidence-based outcome studies that integrate genomic data, phenotypic data, clinical data, behavioral data, daily sensor data, et al., can lead to more targeted and effective treatment and outcomes for both wellness and illness.
Attivio has been using big data in one of the most vital ways by focusing on detecting military personnel who are at risk for suicide.
But, of course, big data still comes with challenges. Riaz acknowledged the reality, which is that every large organization is comprised of disconnected silos of information that come in all different formats; let alone the various business units, applications, protocols, information repositories, terminologies and schemas that doesn’t always mesh.
“Just dumping data into these unorganized but separate systems is anarchy and an egregious waste of time and money,” Riaz said. “Yet, this is how many technologies address the problem. It essentially just creates another big silo for the information to live in.”
Moving forward, additional ways to combine structured and unstructured data, as well as merge data from within an enterprise to data from outside of it, will need to emerge. And when it does, the impact will be glaringly obvious.
As Riaz posited:
The time to solve big problems with extreme information is upon us. Businesses, organizations and governments are putting a lot of faith – and money – into technology solutions to help them make sense of it all. As a technology industry, we owe it to these companies to deliver real products that deliver real results to real problems, not just create more work.
So, let’s start by making that first big decision: Understanding big data’s importance, no matter how big of a buzzword it’s become.
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