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BI Forecast: 30% In-Memory, 30%+ mobile

Interesting (German) article about the future of BI. Key statements:

  • BI is the only remaining differentiator in Enterprise IT. ERP and CRM are commodity. 
  • By 2012, 40% of BI spendings will be with system integrators due to their experience about industry specific requirements according to Gartner
  • By 2012, 30% of analytical applications will run In-Memory according to Gartner
  • By 2013, more than 30% of BI functionality will be used mobile according to Gartner. MobileBI will open new opportunity for niche players to cater new user groups and user groups
  • Othe hot topics are Big Data and Analytics
    • #BI
    • #Big Data
    • #Analytics
    • #Mobile BI
  • 1 year ago
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Analytics in Gartner’s Hype Cycle 2011

Gartner’s Technology Hype Cycle is famous for tracking enthusiasm, disillusionment and eventual realism that accompanies each new technology and innovation.

It’s 2011 version features both Big Data and Predicitve Analytics. Advanced Analytics is mentioned as a key technology driver:

Note that Predicitve Analytics is already in matured state while Big Data is just approaching the hype. What and when will be the delusion of Big Data?

Source: memeburn

Source: memeburn.com

    • #Analytics
    • #Big Data
  • 1 year ago
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Free Big Data eBook from O'Reilly Radar

Big Data is one of the trends fueling the ongoing rise of analytics, aka data science. During the last months the O’Reilly Radar blog has been an authoritve voice on this trends. They now published their articles as an ebook.

    • #big data
    • #resource
  • 1 year ago
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Data is a vital raw material of the information economy, much as coal and iron ore were in the Industrial Revolution. But the business world is just beginning to learn how to process it all.

The current data surge is coming from sophisticated computer tracking of shipments, sales, suppliers and customers, as well as e-mail, Web traffic and social network comments. The quantity of business data doubles every 1.2 years, by one estimate.

Mining of Raw Data May Bring New Productivity, a Study Says - NYTimes.com

Source: The New York Times

    • #Big Data
  • 1 year ago
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The Data Deluge "Economist in Feb 2010"

A 100% non-technical motivation of big data opportunities and challenges.

    • #Economist
    • #Big Data
  • 1 year ago
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Hadoop & Startups: Where Open Source Meets Business Data

Bold prediction about open source big data technology expanding it’s influence beyond Web startups to traditional Enterprise IT:

Hadoop is the ultimate trojan horse in enterprise IT. It strikes at the heart of business — the data — in a way that adds value immediately, while setting the stage for viral growth in the future, connecting the two ecosystems and the technological and cultural levels.

Whether you agree or not — great read for its many references for emerging big data technologies.


    • #Hadoop
    • #Open Source
    • #Big Data
    • #Analytics
    • #Programming
    • #Tools
  • 1 year ago
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A litltle dramatic but there is truth to it. Big data is a huge opportunity for science to develop and test theories more rapidly and thouroughly than in past centuries.
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A litltle dramatic but there is truth to it. Big data is a huge opportunity for science to develop and test theories more rapidly and thouroughly than in past centuries.

Source: Wired

    • #Science
    • #Big Data
  • 2 years ago
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Is Big Data is the End of Theory?

Was the Wired magazine right back in 2008: Is big data the end of models and theory-driven science as we know it? I don’t agree with the technophilian fundamentalism offered in the article but big data almost certainly posseses a disuptive power that will blend into current science practices in ways no one can predict today. Article quotes:

“Sixty years ago, digital computers made information readable. Twenty years ago, the Internet made it reachable. Ten years ago, the first search engine crawlers made it a single database. Now Google and like-minded companies are sifting through the most measured age in history, treating this massive corpus as a laboratory of the human condition.”

“At the petabyte scale, information is not a matter of simple three- and four-dimensional taxonomy and order but of dimensionally agnostic statistics. It calls for an entirely different approach, one that requires us to lose the tether of data as something that can be visualized in its totality. It forces us to view data mathematically first and establish a context for it later. For instance, Google conquered the advertising world with nothing more than applied mathematics. It didn’t pretend to know anything about the culture and conventions of advertising — it just assumed that better data, with better analytical tools, would win the day. And Google was right. Google’s founding philosophy is that we don’t know why this page is better than that one: If the statistics of incoming links say it is, that’s good enough. No semantic or causal analysis is required.”

“Correlation is enough.” We can stop looking for models. We can analyze the data without hypotheses about what it might show.”

    • #Science
    • #Big Data
    • #Statistics
  • 2 years ago
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Behind the Information Overload Hype

WSJ with an interesting analysis on the ongoing big data hype:

Wielding numbers that stretched to 20 or more digits, researchers recently reported on the world’s massive ability to store, communicate and compute information. All three have grown at annual rates of at least 23% since 1986, according to a study published this month in Science.

…

But the digital avalanche isn’t as massive as those numbers suggest. Much of the growth reflects the surge in high-resolution video and photos. In addition, while there is much more information available, each piece is being consumed, on average, by far fewer people than in the past.

    • #Big Data
    • #Web
  • 2 years ago
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I love applying Advanced Analytics to business problems.

My interests include Data Mining, Statistical Analysis, Predictive Analytics, Forecasting, Operations Research and Optimization, Big Data, Open Data and Data Visualization, Enterprise Software, and the Internet.

All opinions my own.

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