How would you like to win $100 for your Startup? In this video from GTC 2014, Todd Mostak from MapD demonstrates the company’s GPU-powered in-memory relational database software for Big Data. The company was declared as the winner of the GPU Technology Conference’s Early Stage Challenge this year, and they will be going home with a cool $100,000 check.
Over at insideHPC, the RichReport is featuring a slidecast with Axel Kloth from SSRLabs. The Silicon Valley Startup has developed an innovative Big Data coprocessor architecture optimized for bandwidth and power efficiency.
Scalable Systems Research Labs is a Silicon Valley startup focused on the development and sale of a family of coprocessors to solve the “Big Data” problem by accelerating execution of applications for customers who demand higher performance and where the power supply or cooling capacity is limited. These coprocessors work with a variety of standards-based application programming interfaces (APIs). SSRLabs’ family of coprocessors improves floating-point computation and analysis of multi-dimensional datasets at substantially higher performance levels and lower power consumption compared to traditional processors.”
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Over at Business Insider, Max Nisan writes that Chicago-based Startup FoodGenius is bringing Big Data to the food industry. The company sells a dashboard that runs analytics on what 330,000 restaurants are serving, allowing customers to see nationwide trends.
The food world has really been split down the middle,” said FoodGenius co-founder Justin Massa. You’ve got grocery [on the one side], and restaurants or food service on the other. On the grocery side of the world, they’ve had data for a long time. Companies like Nielsen and IRI, although they don’t describe themselves this way, were some of the first ‘big data’ companies. They were taking large sets of data that were really messy across lots of different areas and stores, normalizing them, and providing insights about the industry. On the restaurant side of the world, I think there’s never been a robust data industry largely because the data just didn’t exist.
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At first blush one might presume that QuantCell is some Java Swing version of yet another spreadsheet program. In actuality it is the latest taxon in the phylogenetic tree of the computer spreadsheet evolution that started with VisiCalc in the late 1970′s, and is now dominated by Microsoft Excel, certainly one of the most popular computer programs of all time. Where prior incarnations of the spreadsheet category were restricted by the rows, columns and functions that were vested into it by the programmer, QuantCell is consummately extensible thanks to its knowledge of Java and JVM languages. Most recently QuantCell has found a niche in big data, providing templates for quickly entering Map and Reduce formulae into its latticework. At its most basic level QuantCell cells can accept not only the traditional functions generally associated with a spreadsheet; they can also contain instantiations of Java (or Scala or Jython or R) objects.
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Over at the Montreal Gazzette, Joseph Czikk writes that Plot.ly is a new online platform that allows users to create and collaborate on publication-quality graphs and charts that require large amounts of data. More powerful than Microsoft Excel or Google Docs, it enables data analysts to work together in real-time.
Plot.ly is the first tool where teams that have to work on data-driven problems together can rapidly share and annotate their graphs and results through the cloud,” said co-founder Chris Parmer.
Over at CNN Money, By JP Mangalindan writes that while many organizations continue to struggle to make sense of Big Data, a new Startup called Optensity has built a system that assists decision-making without worrying about where the data is located, how it’s formatted, and how it’s changing.
One thing popping up is called the “Internet of Things,” said Optensity Founder and CEO Pamela Arya. “That’s an example where we think our tool could be really useful in the future. Because the Internet of Things is basically a world of sensors, where you would compute on the sensor as the data is throwing off the sensor to find out interesting things. Hey, nobody’s been in the house for a while, but the air conditioner is still running. That kind of thing. So you needs two sensors there: a physical sensor. No one’s moving around. Another sensor saying the air conditioning’s running. So those kinds of problems are where we see the future of where data is going.”
In this podcast, Deepak Jeevan Kumar from VC firm General Catalyst Partners describes his efforts to help entrepreneurs with disruptive ideas in big data, cloud computing, data center infrastructure, cyber-security, and clean energy.
Deepak Jeevan Kumar has been with General Catalyst since 2010, first in Boston and later in the firm’s Palo Alto office. He specializes in incubating and launching big data and cloud computing startups. Deepak has been closely involved in General Catalyst’s investments in AltiScale, DataGravity, ParElastic, Push Computing, Sunglass.io and Virtual Instruments. Prior to joining GC, Deepak led Sun Microsystems’ high performance computing work in the Asia-Pacific region. He has the distinction of being a key architect of a few top 10 supercomputers in the world. He also had a short stint at the Yale Investments office. Deepak is a graduate of the National University of Singapore, earning a B.Eng. in Computer Engineering; the Singapore-MIT Alliance, earning a S.M. in Computer Science; and the Yale School of Management, earning an M.B.A.
Over at GigaOM, Derrick Harris writes that there are now more choices for businesses that want out-of-the-box functionality for machine learning, predictive analytics and general data science.
An offspring of Greenplum (former Greenplum parent company EMC is an investor, in fact), Alpine Data Labs is doing what amounts to Microsoft Visio for predictive analytics. Its software sits right inside a company’s data store (that can be Hadoop or any number of popular databases) and lets users analyze the data by drawing flow charts. It’s a little more complex than just pulling down a menu and selecting “cluster,” but it’s a whole lot easier than trying to code those functions.
Over at Entrepreneur Magazine, Mikal E. Belicove writes that of the power of Big Data for small business is “knowing the now.”
If your business can gain insight from data-logging sensors, you can distill that knowledge into timely, intelligent decisions and trigger the right action at the right time. Or, put another way, today you no longer use data to see what happened; instead you use it to see what’s happening in real time, which allows you to pinpoint your marketing, improve service, reduce costs and save time. The possibilities are endless.
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Lean Analytics is the dashboard for every stage of your business, from validating whether a problem is real, to identifying your customers, to deciding what to build, to positioning yourself favorably with a potential acquirer. It can’t force you to act on data–but it can put that data front and center, making it harder for you to ignore, and preventing you from driving off the road entirely.