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Data Sheet—Monday, February 2, 2015

February 2, 2015, 1:37 PM UTC
Fortune

Good morning, Data Sheet readers. Thanks to Andrew Nusca for filling in last week, while I updated my scuba logbook. Let’s dive into Monday, shall we? We’ll start with a pop quiz: which high-tech CEO made more last year, Ginni Rometty or Meg Whitman? Bonus question: which one did a better job of earning her salary?

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TRENDING

Does Ginni Rometty really deserve a $3.6 million bonus? Yep, that’s the IBM CEO’s “incentive payout” for 2014. Plus, she could get up to $5 million this year. Still, that pales in comparison to the $19.6 million total package pulled in last year by another powerful high-tech CEO, Hewlett-Packard’s Meg Whitman. Both have plenty to prove over the next 12 months.

Intel is getting acquisitive again. It won’t say how much it is paying for Internet of things chipmaker Lantiq. The company was formed for $400 million from the ashes of Infineon Technologies. Its focus is on the wireless connections between gadgets.

Two Nest execs leave the nest. Both CEO Greg Duffy and tech guru Yoky Matsuoka have left their posts at Google’s smart thermostat division. The latter is taking a job with Twitter.

Speaking of which, Twitter is set to report its late financial results late Thursday amid speculation that CEO Dick Costolo won’t hold that title much longer. The haters are getting so loud that Twitter founder Jack Dorsey last week vocalized his solidarity with a Tweet or two.

Apple, Google and Amazon make nice with Italy. They’ve all promised antitrust officials that they will excise the word “free” from mobile apps that could require payments for certain features.

Comcast’s de facto broadband monopoly. If you use the FCC’s new minimum download/upload speeds, you’ll find that the Internet service provider controls more than half the home market.

Google promises bigger bug bounties to researchers finding flaws in its software, but all the obvious goofs were found long ago.

STARTUPS & DISRUPTORS

Let’s close a deal! Salesforce Ventures is putting $41 million into Appttus, which makes technology for generating quotes and negotiating contracts. It’s one of the fund’s biggest rounds yet for a company that it hasn’t actually taken over (yet).

Another unicorn in the making? Big data company Dataminr, which sifts social media chatter for comments or trends, is close to raising another $50 million. That would put it over the magic billion-dollar valuation threshold.

EX-GOOGLER SEEKS SIMPLER BIG DATA SEARCHES

Three years ago, a Google developer and Facebook image processing engineer teamed up to simplify business intelligence. Their mission: create a universal way to search for answers to basic queries like “How did I win that customer?”

Last August, their startup Metanautix emerged from stealth with $7 million in Series A funding from Sequoia Capital. Its first product, the Quest Data Compute Engine, emerged shortly thereafter. Its unique twist: it doesn’t think business should have to reformat existing data sources to tease out the answers.

“The reality of modern enterprises is that heterogeneity is the norm in data, systems and processes,” wrote co-founder and CEO Theo Vassilakis in a blog post coinciding with the launch. He continued: “Instead of structuring analysis around storage as has been done traditionally, we help you structure analysis around computation—i.e., answering your business question.”

The inspiration for Quest was a custom search engine called Dremel, used internally at Google for business analysis. (Vassilakis was one of the creators.) Early adopters include Hewlett-Packard, Shutterfly and other unnamed companies from the consumer packaged goods, pharmaceutical, and utility sectors. Fortune spoke Vassilakis about Metanautix’s differentiation in a crowded big data software market and how the startup will use its partnership with visual analytics powerhouse Tableau Software to build momentum.

Excerpts from the interview were edited for length and clarity.

Explain the Data Compute Engine concept to a non-technologist.

Basically the way we explain it is to say traditionally when you want to analyze data you first have to put it into a thing, like a spreadsheet or a database, so you can ask questions and get results. What a Data Compute Engine helps you do is to just ask your questions of your database, your spreadsheet, whatever files you have.

Describe some early applications.

An example that is more traditional would be some of the work we've done at Shutterfly, where they're doing marketing analytics. They said, "Let's look at all of our orders. We sell prints and calendars and t-shirts and things like that. How do we get those orders? What part of our marketing works? Was it the e-mail? Was it the ads? What was it that got us the order?"

They were doing that analysis for some time actually with a method called "last touch." That means identifying the last thing that the customer did before they bought—as in they clicked an ad and then they bought whatever. The company figured it must've been that ad that caused the customer to buy the print. Or someone got a direct mail campaign message and then they bought the calendar. That was the motivation.

[Shutterfly] looked at that process and said, "You know, that's a good model. It's a good approximation, but it would be better to look at everything touching the user before their last purchase and since the purchase before that." This greatly expanded the data that they had to consider to do the analysis, so the process became very slow. It took two days to compute the likely marketing channels for all their orders.

One thing we helped Shutterfly do was radically speed that up. We took those two days of compute down to basically 20-25 minutes on a single machine and then just three and one-half minutes on a cluster.

So that’s one class of applications: processing is just faster, simpler, easier. Then there are other classes of applications where we're doing more exotic things: for example, for one utility company we're helping them analyze 3D models of gas pipes and move them around between laptops into the cloud, which lets them query the images and do fancier stuff with that data.

How much help are you giving your early customers? Are you doing a lot of services around those applications or are you kind of pretty much out of the way?

We are at a stage where we've got eight or nine customers and are still early in our development. We want to make sure every one of our customers succeeds. So we do help, but it's not a big part of the objective to build out a whole professional services organization.

I'll give you an example. I was talking to a large entertainment company a couple of weeks ago and they're really interested in predicting box office outcomes of movies. Part of the discussion was about how to build a better model. And of course a lot of us at Metanautix have built models and so we understand this process. We can give input. But our objective at the end of the day wouldn't be to say, "Hey let me build this model for you." Our objective would be, "Hey it's your model. You should own it.” In fact, in order for it to be impactful in your organization you have to own it because it has to change the culture of your org and how you think about collecting data.

Are you still taking on customers very selectively?

We're a Tableau partner, and we are focusing on organizations that have Tableau because it usually represents a commitment by an organization to be data-driven and all of those good things. So one of the things that happened—and we're excited about this—is that the Tableau partnership sort of started the process where people are starting to reach in without us necessarily reaching out.

Ford recently appointed a chief data officer and all sorts "Internet of Things" devices are generating millions of metrics. How does Quest handle this data?

We’ve built a demonstration, a little car that you can kind of drive around with a remote control. Using Quest, we can query the car and say, "Hey car, where are you and what are your sensors telling us?" We can do that with very simple commands.

But actually a lot of data, especially in Internet of Things types of applications, maybe never gets stored. It gets generated and maybe queried on the fly. Then it goes away. Part of what we're trying to do is to say what's really powerful is having the same model of query and analysis for your data, regardless of where it is.

What’s your company’s top priority for 2015?

Build on the Tableau partnership that we've initialized and really go after lots of big Tableau server deployments that are tied into core systems in the enterprise—such as Teradata, such as SAP, such as Oracle. From there, we can really help performance, simplicity, and build real examples and repeatable scenarios. Tableau is where we started, but there are obviously a lot of comparable scenarios out there.

MY FORTUNE.COM BOOKMARKS

Apple, Obama and the Federal Highway Trust Fund by Philip Elmer-DeWitt

Do NFL cheerleaders need their own Bill of Rights? by Claire Zilman

Smile! You’re on the world’s quickest 2-D camera by Robert Hackett

Women are not making progress in male-dominated VC world, data shows by Dan Primack

Want to create more women leaders? Offer paternity leave by Leigh Gallagher

ONE MORE THING

Note to self: leave passwords. Right now, it’s super hard for families to access email and digital records of deceased love ones (think photos, people) who don’t leave specific instructions. A new Delaware law is changing things.

MARK YOUR CALENDAR

IBM Interconnect: Cloud and mobile strategy. (Feb. 22 – 26; Las Vegas)

Gartner CIO Leadership Forum: Digital business strategy. (March 1 – 3; Phoenix)

Microsoft Convergence: Dynamics solutions. (March 16 – 19; Atlanta)

IDC Directions 2015: Innovation in the 3rd Platform era. (March 18; Boston)

Cisco Leadership Council: CIO-CEO thought leadership. (March 18 - 20; Kiawah Island, South Carolina)

Gartner Business Intelligence & Analytics Summit: Crossing the divide. (March 30 – April 1; Las Vegas)

Knowledge15: Automate IT services. (April 19 – 24; Las Vegas)

RSA Conference: The world talks security. (April 20 – 24; San Francisco)

Forrester’s Forum for Technology Leaders: Win in the age of the customer. (April 27 - 28; Orlando, Fla.)

MicrosoftIgnite: Business tech extravaganza. (May 4 – 8; Chicago)

NetSuite SuiteWorld: Cloud ERP strategy. (May 4 – 7; San Jose, California)

EMC World: Data strategy. (May 4 - 7; Las Vegas)

SAPPHIRE NOW: The SAP universe. (May 5 – 7; Orlando, Florida)

Gartner Digital Marketing Conference: Reach your destination faster. (May 5 – 7; San Diego)

Annual Global Technology, Media and Telecom Conference: JP Morgan’s 43rd invite-only event. (May 18 - 20; Boston)

HP Discover: Trends and technologies. (June 2 - 4; Las Vegas)