Posted April 16, 2012 by Heidi Isern, Director Dealmaker Media
Metamarkets is a big data company that combines Hadoop, in-memory computing, and Cloud architectures to deliver insights over massive data in milliseconds. We are pleased to have them presenting at our Under the Radar Conference on April 26th. Before you watch them pitch, learn a few things about their company culture. Mike Driscoll, Metamarkets CEO, answers a few questions on what makes Metamarkets unique.
1. If your company was a movie, which one would it be and why?
We aspire to make the science fiction dashboards of Minority Report a reality.
2. If you could give a TED Talk, what would it be about?
I would talk about the magic of data science to make this invisible universe of data visible and tactile.
3. What Hollywood star would play your CEO?
Jeff Goldblum or anyone with experience portraying slightly mad scientists.
4. What one piece of advice would you give to other entrepreneurs?
“Vision without execution is hallucination.” – Thomas Edison
5. Which other internet startup do you respect the most?
I love how DropBox has taken a simple idea and executed on it beautifully.
6. Who’s the most impressive founder you’ve ever met and why?
I met Marc Benioff at a conference in Germany last year and he had enough charisma to fill a room. His one piece of advice was “go bigger.”
7. What’s the first website you check out every day?
My Twitter feed.
8. What’s your company’s theme song?
The Pandora station seeded with Moby.
9. Whose Twitter feed inevitably makes you laugh?
Aaron Levie, Box.net’s founder, has a hilarious Twitter feed. My favorite last Tweet read: ”With Instagram’s $1B acquisition, I can no longer recommend building enterprise software over photo sharing apps.”
10. What’s been your favorite moment since starting your company?
This may sound sad, but I am someone who is in a state of perpetual dissatisfaction about my start-up. I think we can always be better, and I’m not one for looking back and feeling overly proud. We have so much more to do. At the same time, I am pathologically optimistic about our prospects for the future. The day that we cross over into being a viable, profit generating entity will be my favorite, crowning moment in the company’s history.
As a special thank you to our blog readers, enter promo code: “utrblog” when registering to receive $100 off your ticket to attend UTR and see Mike and others present on stage!
Posted February 21, 2012 by Heidi Isern, Director Dealmaker Media
Right now companies are inundated with massive sets of real time information. Petabyte size data comes via Twitter feeds, computer log files, geo-local information, and more. However, few corporations know how to make actionable business decisions with this type of “Big Data.” A recent Mashable article claimed that only a third of companies in their study had the capacity to turn raw data into anything useful.
This is where a Data Scientist can help. A Data Scientist is an emerging role that corporations are finding highly valuable to help analyze their information. Mashable called it the “Career of the Future”
GigaOm wrote about a spike in demand for Data Scientists because “Petabytes of data are useless if no one can make sense of it.” In fact, after talking to multiple recruiting firms they found that technical engineers can make a 25% salary increase for understanding hadoop architecture and big data analytics.
What Makes a Data Scientist Special?
Many say it’s their ability to create a perfect blend of math and art (in terms of data visualization).
In an interview with Forbes last fall, Monica Rogati, Senior Data Scientist at Linkedin said, “By definition all scientists are data scientists. In my opinion, they are half hacker, half analyst, they use data to build products and find insights. It’s Columbus meet Columbo – starry eyed explorers and skeptical detectives.”
These detective/ explorers will continue to be highly sought after as our big data explosion continues. Big data analytics companies will also emerge attempting to support (or replace) the role through their software platform. After all, it’s not the size of the data, it’s what you do with it.
Come to our Under the Radar Conference to meet emerging big data analytics companies as well as LivePerson’s own Data Scientist, Vitaly Gordon.
Posted February 9, 2012 by Heidi Isern, Director Dealmaker Media
The open source software Hadoop is creating a lot of buzz in the big data world. It’s commonly known as the MapReduce algorithm on which Google built its empire. Forrester Research calls it, “The Open Source Heart Of Big Data.”
However, as the buzz builds the term is thrown around recklessly, leaving many confused as to how it works and where it is used. Derrick Harris of GigaOm authored an article explaining Hadoop terminology and top uses.
Derrick writes, “Hadoop is an Apache Software Foundation project consisting of two primary subprojects — Hadoop MapReduce and the Hadoop Distributed File System. MapReduce is the parallel-processing engine that allows Hadoop to churn through large data sets in relatively short order. HDFS is the distributed file system that lets Hadoop scale across commodity servers and, importantly, store data on the compute nodes in order to boost performance (and potentially save money). “
Three Ways Hadoop is Used
Distribution: Distribution refers to the way in which large data sets are moved between Hadoop clusters and other environments. Companies like Cloudera and the new HortonWorks play in this space.
Management Software: These Hadoop products act as an operating system and help you trouble shoot. There aren’t many unique vendors in this space. Derrick writes, “Such products are usually sold or offered by companies peddling Hadoop distributions because even when commercially packaged, Hadoop is still a complex architecture…”
Application software: Application software resides on top of Hadoop distribution and improves processing and/or performs analytics. Derrick mentions Karmasphere Analyst, Hadapt, and HStreaming. Jeff Kelley from Services Angle also calls out a few others “Hadoop applications of the future” such as Datameer, Tresata and Tidemark.
To learn more about how Hadoop is used, read Derrick’s full article in GigaOm. To discover more emerging Hadoop companies transforming the world of big data, come to our Under the Radar Conference on April 25-26 in Mountain View, CA.
Posted November 30, 2011 by Clare Jacobson
I’ve been talking to a LOT of people lately about Big Data. Frankly, it’s a term I keep hearing, and when I ask people about what is means to them, I get a ridiculous array of answers:
1. Big data is about analytics, social media, and reporting.
2. Big data is about privacy and ensuring that the data we generate online stays safe and is used responsibly.
3. Big data is about figuring out where to store the data that is generated in the cloud.
4. I don’t know what Big Data is, and no one really does.
5. Big data is everything.
6. Big Data is a buzz term that really doesn’t mean anything.
7. Big Data is about leveraging stored data and giving businesses new streams of revenue and insight.
So, I’m going to venture out here and add another voice to the discussion.
Big Data: Placing bets on who’s going to win
What’s NOT online these days? We have our banking information, our photos, our medical records, our contacts, our messaging, our directions, our shopping habits, our libraries, our newspapers, our tweets, our location and movements, our blogs… the list goes on. Everything has a place online these days and somewhere, all of our tracks our being traced and stored. A little creepy? Yes. Unavoidable? Pretty much unless you live under a rock. There is SO much information out there and the entrepreneurs that figure out how to best leverage and act upon that data have a colossal chance right now. This is “Big Data.”
Big Data is about “the benefits we will gain by cleverly sifting through data to find and exploit new patterns and relationships.” Big Data is big business, adding a new level of certainty to business decisions, and promoting new discoveries about nature and society.
The list of startups working in Big Data is infinite, and the easiest way to classify them would perhaps be to group them into verticals. For example:
Retail Big Data, Medical Big Data, Geolocation Big Data, Privacy Big Data, Storage of Big Data, etc.
If anyone asks me, I’m going to say Big Data is about dealing with all the content we are all constantly generating, and the winning players are going to be the ones who can prove they have information that is valuable and predictive. Then they just need to convince their customers their data analysis is what the business needs to stay relevant. Sounds easy, right?
Now go ahead, convince me I’m wrong.
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