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Accelerating Insights from Your Data

In this special webcast, Tim O'Reilly, founder and CEO of O'Reilly Media, talks with Microsoft Technical Fellow Dave Campbell about the new and exciting tools emerging for data analysis and insight. With machine processing power and data storage growing cheaper by the day, the value is now moving to the data itself. New options allow for the refinement and combination of data like never before. Where data was once "locked" behind applications, these file sources are now opening up, allowing people and organizations to find new ways to analyze existing as well as new data for faster and deeper insights. From creating a language translation tool with raw machine data, to real-time traffic redirection, the potential benefits that can be realized from the evolution in insights is unlimited. Tune into the webcast and see how Microsoft is working with the data community to develop new tools that will unlock insights from previously unimaginable sources at breakneck speeds. For more information, please visit www.microsoft.com/bigdata. <iframe allowfullscreen="" frameborder="0" height="315" src="http://www.youtube.com/embed/iazPuiuJdVE" width="560"></iframe>

Accelerating Insights from Your Data

In this special webcast, Tim O'Reilly, founder and CEO of O'Reilly Media, talks with Microsoft Technical Fellow Dave Campbell about ...

5:38 AM

Personalizing your game character

Personalizing your game character

I know that this topic has nothing to do with Business Intelligence, but it has to do with technology innovation and it is so cool so I cann...

4:06 AM

Technology trends

Technology trends

KPCB Internet Trends 2012 View more presentations from Kleiner Perkins Caufield & Byers

12:52 PM

Cloud Computing BI

Cloud Computing BI

What is Business Intelligence? What is LITEBI? A brief introduction to LITEBI and its Cloud Computing Business Intelligence platform

11:20 AM

Microsoft beats data-sorting record with new approach

A new approach, called Flat Datacenter Storage, pushes computational sorting to each data server  Besting a record set by Yahoo in 2009, the research arm of Microsoft have deployed a new technique for quickly sorting large amounts of data, called Flat Datacenter Storage (FDS). The researchers will discuss their work at an Association for Computing Machinery conference dedicated to databases this week in Scottsdale, Arizona. They are also implanting their data-sorting techniques in Microsoft's Bing search engine, where it could boost response times to user queries. "Improving big-data performance has a wide range of implications across a huge number of businesses," said Microsoft Research project leader Jeremy Elson, in an online entry describing the work. "Almost any big-data problem now becomes more efficient, which, in many cases, will be the difference between the work being economically feasible or not." In tests conducted under the MinuteSort benchmark, the system set up by Elson and his colleagues was able to sort 1,401Gb of data in a minute, which beat Yahoo's previous record of 500GB in the same time. Microsoft also boasted of sorting the data using fewer resources: The system used 1,033 disks in 250 machines while Yahoo required 5,624 disks across 1,406 machines to complete their operation. FDS starts with a similar approach as Google's MapReduce -- as it is implemented in Apache Hadoop -- by moving the computational sorting to each individual data server. Unlike Hadoop, however, every server trades information with all the other server in the sorting cluster. The researchers used an additional Microsoft networking technology, called full bisection bandwidth networks, to boost the bandwidth, allowing each computer to both send a receive send up to 2GB per second. Refer: <a href="http://www.computerworld.com/s/article/9227390/Microsoft_beats_data_sorting_record_with_new_approach?taxonomyId=9">http://www.computerworld.com/s/article/9227390/Microsoft_beats_data_sorting_record_with_new_approach?taxonomyId=9</a>

Microsoft beats data-sorting record with new approach

A new approach, called Flat Datacenter Storage, pushes computational sorting to each data server Besting a record set by Yahoo in 2009, the...

7:12 AM

Effective big data strategies detailed

Businesses beginning a big data analytics program with advanced business intelligence software may be concerned about affordability. However, according to PC Advisor, there are easy steps that companies can take to make sure that their deployments are successful. These steps include deep research into the business case at hand and prudent financial planning. Careful planning "[Big data is] new technology solving a business problem that we often haven't proved. That's important for CIOs to keep in mind," financial consultant Jeff Muscarella told PC Advisor. "The business is going to be coming to them with all sorts of half-baked ideas for what they can do with Big Data. They have to ask: Will it really drive revenue? How and for how long?" According to the source, carefully vetting business ideas for new big data projects is vitally important for CIOs trying to save money on their big data projects. Gathering details on each projected usage of data means less chance of failure. The source urged companies to target their big data projects, to fire "bullets" rather than "cannons" at specific problems that can provide value for the company. Muscarella told the source that companies can start small to prove that a process works before moving to the company-wide infrastructure level. Myths vs. reality As a widely hyped technology often presented as the future of business intelligence, advanced analytics and big data have received a large amount of press. To avoid business confusion, several publications have offered clarifications of what the technology can and cannot offer companies. The Economic Times stated that any business with a product to sell and any company hoping to help make up the potential market for big data. As companies begin to harness the power of big data, competitors could take of the systems in a bid to compete on an even level. The source sought to puncture myths about what big data can and cannot do. It stated that big data's endgame is unknown, and that many of the features of big data analytics are still spoken of in the future tense. The source found that companies can already use the technology to provide "amazing" customer insights from vast quantities of "irrelevant stuff." While it is important to be careful when integrating big data, making the effort could become a required part of business strategy Industry News from: <a href="http://www.panorama.com/industry-news/article-view.html?name=Effective-big-data-strategies-detailed-774397&utm_source=dlvr.it&utm_medium=facebook">http://www.panorama.com/industry-news/article-view.html?name=Effective-big-data-strategies-detailed-774397&utm_source=dlvr.it&utm_medium=facebook</a>

Effective big data strategies detailed

Businesses beginning a big data analytics program with advanced business intelligence software may be concerned about affordability. However...

7:22 AM

Predictive Analytics and Data Mining

Derive useful insights to make evidence-based decisions Today's organizations accumulate huge volumes of data from a variety of sources on a daily basis. However, turning increasingly large amounts of data into useful insights and finding how to better utilize those insights in decision making remains a challenge for most. To get answers to complex questions and gain an edge in today's marketplace requires powerful, multipurpose predictive analytic solutions so you can learn from, utilize and improve on knowledge gained from vast stores of data. BIandIT Ltd provides a wide range of software for exploring and analyzing data to help uncover unknown patterns, opportunities and insights that can drive proactive, evidence-based decision making within your organization. Text mining applies the same analysis techniques to text-based documents. The knowledge gleaned from data and text mining can be used to fuel strategic decision making. Components of Predictive Analytics and Data Mining Exploratory Data Analysis – Get dynamic visualization, advanced statistical techniques and core data mining capabilities to quickly identify relationships and opportunities. Model Development and Deployment – Streamline the data mining process to create highly accurate descriptive and predictive analytic models based on large volumes of data. Analytics Acceleration – Generate faster results and improve data governance with in-database analytics. Scoring Acceleration – Maximize the performance and accuracy of your analytic models.

Predictive Analytics and Data Mining

Derive useful insights to make evidence-based decisions Today's organizations accumulate huge volumes of data from a variety of sources ...

6:51 AM