In this slidecast, Chris Matty from Versium describes the company’s Real-Life Data Intelligence Platform.
In consumer marketing, LifeData allows ever-narrower segmentation of customers and therefore much more precisely tailored products or services. Greater real life insights about people and businesses enable optimized communication strategies. Sophisticated analytics can predict behavior and greatly improve decision-making. LifeData can make existing applications more intelligent and enable entirely new ones. Versium’s powerful data intelligence platform enables all of this and more.”
In this slidecast, Guy Fraker presents: get2know – Big Data for the Shared Economy.
With shared rides, cars, bikes, and even rooms, the issue of trust is huge. The folks at get2know have a developed a “Trust Engine” that uses Big Data to help you decide who you trust to share your stuff. Amazing!
As we build out to scale, we’ll provide a playground for alliance partners to reward consumers who utilize shared services in postive ways. We will deliver a searchable aggregated view of shared economy providers WITH utilization incentives. By doing both in a single view, using single sign-on, we provide an economic reason to be scored. We believe that by partnering with the Collaborative Consumption community, a market is created where no user asks, “ok- I got my score- now what?” get2kno is about creating a market, not building a platform.”
How does Thurston’s model work? It’s rooted in the mountains of data he has collected on market and corporate dynamics, including the anticipation of future changes in the marketplace. Patterns of success or failure then emerge depending on these different market and business behavior factors. “The key is identifying variables that are predictive of success and failure,” says Thurston, who is very hush-hush about revealing those variables. It’s a process that involves “lots of hard, hard work,” he says. “You go through a whole haystack to find one needle.”
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While it’s a powerful platform for analyzing large, static data sets, Hadoop has always been limited by its inability to perform analytics on live data,” said Bill Bain, ScaleOut Software CEO. “There is an increasing drumbeat for real-time analytics using Hadoop, and we’re excited to take an important step towards meeting that need with this release.”
ScaleOut hServer will be available in both a free community edition and in several commercial editions. The community edition enables up to a four-server combined Hadoop/hServer grid for analyzing memory-based data sets of up to 256GB. Read the Full Story or check out our podcast interview with Bill Bain.
In this video, author Alistair Croll explains the concepts of his book, Lean Analytics. Croll strongly advises startups to pick the one metric that matters the most and to focus on it.
This talk was hosted by MaRS, a Canadian organization that provides resources — people, programs, physical facilities, funding and networks — to ensure that critical innovation happens.
Over the last seven years, Thomas Thurston has been developing algorithms—first at Intel Capital, and later in collaboration with Harvard professor Clayton Christensen, and under his own shingle at Growth Science in Portland, OR—to model markets and business behavior, and thereby predict the success or failure of a given innovation. Now he is joining Hambrecht-led venture fund Ironstone Group as a partner to try this method in a venture capital industry increasingly open to data-driven approaches.
In this video, Bruno Aziza from SiSense describes the company’s Big Data analytics technology, which won the People’s Choice Award this year at the Strata Startup Showcase in Santa Clara. The company wowed attendees with its ability to crunch 10 terabytes of data on a single-node machine in 10 seconds.
By utilizing state-of-the-art technology and a unique business model, we aim to completely change the current reality in which only Fortune 500 companies can benefit from high-quality, scalable BI solutions. The time has come for every company to have access to full-fledged BI without compromising on functionality, scalability, manageability, flexibility, governance, collaboration or ease-of-use.
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Can Big Data analytics be used to predict which Startup companies will succeed? In this video, Thomas Thurston from Growth Science discusses the new Ironstone Venture Capital Fund, which is using Business Model Simulation to choose disruptive Startups.
The human mind is good at some things but bad at others. So we use data science and technology to help our brains with the things they weren’t designed for. This marriage between technology and the brain has allowed us to predict business behavior in ways that weren’t possible even a decade ago. It’s the future of venture capital,” said Thurston. This fund is unique. First, instead of mostly using intuition, like most VCs do, we’re using powerful, proven data science to identify disruptive companies. That’s revolutionary. Second, we’re interested in seed- and early-stage companies, which is much needed as our economy rebuilds itself. Finally, unlike a lot of VCs focused on exits and quickly ‘flipping’ startups, we have a long-term view and really want to partner with people growing strong, disruptive, meaningful businesses to make the world a better place.”