How open source helps startups get a big data boost

How open source helps startups get a big data boost

How open source helps startups get a big data boost

Big data isn't new. We've actually had fairly sophisticated data infrastructure long before Hadoop, Spark, and such came into being. No, the big difference in big data is that all this fantastic data infrastructure is open source software running on commodity servers.

Over a decade ago, entrepreneur Joe Kraus' declared that "There's never been a better time to be an entrepreneur because it's never been cheaper to be one," and he was right, though he couldn't have foreseen how much so. Though Kraus extolled the virtues of Linux, Tomcat, Apache HTTP server, and MySQL, today's startups have access to a dazzling array of the best big data infrastructure that money doesn't need to buy.

In this way, startups are able to put a target on the backs of much better-funded enterprise rivals.

Take Bidtellect, for example, an adtech startup. The Bidtellect platform helps advertisers, agencies, and media companies deliver targeted native ads across all devices, in any format. In practice, this means that Bidtellect must track and analyze the potential inventory of ad placements—which number in the millions daily—to see how each is affected by numerous variables. Once ads start running, it's essential to track their performance against client KPIs.

Read Also:
Devs will lead us to the big data payoff at last

As Jeremy Kayne, Bidtellect's CTO, told me in an interview, Bidtellect is engaged in "a kind of arbitrage," whereby the company buys inventory on a per-impression (per-display) basis, but then sells ads on a per-click basis. In order to build a viable business and not a candidate for bankruptcy protection, "It's essential that we're able to predict how many clicks an ad will generate on a given site, on a certain device type, at a certain time of day, and across scores of other variables—so we can price it right and make a fair profit."

This is where big data comes in.

"To accurately make these predictions, identify viable advertising opportunities, and negotiate workable rates and pricing, we had to find a practical way to collect, manage, and understand the billions of transactions and data points involved," Kayne said.

The system that collects and tracks all of this information amounts to petabytes in data volumes. This is big, but it's about to get bigger.

Read Also:
Get Master Data Management Right – and Fast – with Full-Production Analytics

 



Chief Analytics Officer Spring 2017

2
May
2017
Chief Analytics Officer Spring 2017

15% off with code MP15

Read Also:
Devs will lead us to the big data payoff at last

Big Data and Analytics for Healthcare Philadelphia

17
May
2017
Big Data and Analytics for Healthcare Philadelphia

$200 off with code DATA200

Read Also:
Devs will lead us to the big data payoff at last

SMX London

23
May
2017
SMX London

10% off with code 7WDATASMX

Read Also:
Internet of Things brings new era of weather forecasting

Data Science Congress 2017

5
Jun
2017
Data Science Congress 2017

20% off with code 7wdata_DSC2017

Read Also:
Data governance as an accelerator, not a roadblock

AI Paris

6
Jun
2017
AI Paris

20% off with code AIP17-7WDATA-20

Read Also:
Big Data Will Rule Your Home

Leave a Reply

Your email address will not be published. Required fields are marked *