Month: February 2012

Talking, talking, talking about big data

Hang out for a few days at an industry event and you’re doused in trends, hearsay, and preoccupations. It permeates your mind. Acquired phrases come out of your mouth, the hotel food starts tasting good, and at night your dreams may tell you more than you want to know about hot topics.

Sometimes, I just have to get away. The easiest way at the recent TDWI conference in Las Vegas was down the long hallway toward the casino. Among the rooms named for murdered emperors, the “Justin II” was wide open with a noisy crowd of TDWI-badged guys inside.

I stood in the doorway to listen. One of them saw me and asked, “Have you seen it?” Another one asked, “Tell us! What’s it like? How big?”

When I asked what they meant, a third one said impatiently, “Where have you been? Big data! It’s here, and it’s coming, and it’s really big!” Someone near him added, “It’s big. That’s for sure.”

“Velocity, volume, variety,” a fourth man recited. “Unstructured data!” said another one. And another, “Predictive analytics!”

Behind the crowd was a bartender shaking a cocktail mixer. “Hey, guys. I’d like you to try a new drink. We’re very excited. We call it One Two Three Hadoop!” The crowd turned to him, and each one took a glass from the long row of samples.

“Mmm,” they all said as they sipped and sniffed. One asked, “Will this handle it?” The bartender nodded solemnly.

Suddenly, the room quieted. A man in a hurry was forcing his way toward the bar. “Hadoop! Double!,” he told the bartender. The man swallowed the drink, wiped his mouth, and said to the crowd, “Anyone here ever worked with Hadoop?” A man raised his hand, and the man looked him up and down as if considering him for day labor. “You’ll do. Come!”

“Just like that?” the Hadoop worker said. Another man in the crowd pushed forward and said to the man in a hurry, “Let me pose a question, sir! How do you define ‘big data’?”

The man in a hurry just looked at him, annoyed.

“Yes!” said a man in the back. “How will you know it when you see it?”

But the man in a hurry was already half way out the door as his new helper scurried to catch up.

A tall, skinny man next to me said, “That fella’s in too much of a hurry. It’s sure no way to get to fact-based decision making.” A fat man on my other side said, “Or unstructured data!” From behind, I heard, “Or predictive analytics!”

I leaned over to the tall, skinny man and tried to say just loud enough for him alone to hear, “Am I missing something? All this sounds like the same old BI, just bigger, more variety, and all that.”

The man turned and looked at me, his eyes wide and his mouth open and ready to say the words he hoped his mind would deliver soon. Finally, his mouth widened into a grin, and he laughed. Then I heard laughter from all around me. They were doing what crowds do, which is whatever someone else does first.

The bartender held up another bottle. “You guys need alternative solutions to enhance your big data readiness,” he said. “Take a lick of this very smooth 15-year-old MapReduce.” The crowd pivoted back toward the bar.

“This one is the best yet,” one man wheezed, his eyes watering as he resisted a cough. A man near him said, “Yep, this is a big drink. That’s what we need. Big data’s going to be big.” Another added, “Terabytes big!” Another, “Petabytes big!” And a third man, “Zettabytes big!”

A second bartender had appeared. He said, “We’re very excited about this new premium product. We call it NoBS NoSQL.” He poured a new row.

One man gulped his drink and reached for another. “Just how big do you suppose big data is?” he said. A short man next to him took a drink and pronounced confidently, “I’d say about this big,” and spread his arms wide.

A third and fourth bartender had just appeared, and I had to get out of there.

Simple tool, same old resistance

I’ve rarely heard resistance to BI expressed quite so well.

A woman at an oil company said to Metrics Insights founder Marius Moscovici, “If someone wants to know something, they pick up a phone.”

The hell with easy information delivery. Make them ask for it.

I might understand what Marius witnessed if the woman were faced with any of the heavy hitters in business analytics. These things come encrusted with big promises, but big promises come with big upheaval. Data gets disturbed that some people wish would stay buried. They want to say, “Everything’s fine here. Go away.”

You can imagine why. They might fear that data quality isn’t up to snuff, or that someone’s got to govern all that stuff whether it’s “big data” or little data, or they could simply fear anything not invented back when they had nothing to lose.

It’s harder to understand when the information has already been refined and put in a box — and simply needs delivery to a doorstep.

The simple tool from Metrics Insights — the company and the tool go by the same name for now — seems to follow in big tools’ wake and fill in where they won’t. Users drag and drop tiles to assemble other tools’ output onto one screen. It’s simple self-service BI for easy focus, collaboration, and mobility.

It’s making headway with four customers that include Barnes and Noble. Looks to me like a good tool that’s just trying to bridge that last yard.