Why you should never trust a data scientist Photo by Jesse Means The wonderful thing about being a data scientist is that I get all of the credibility of genuine science, with none of the irritating peer review or reproducibility worries. My first taste of this was my Facebook friends connection map. The underlying data was sound, derived from 220m public profiles. The network visualization of drawing lines between the top ten links for each city had issues, but was defensible. The clustering was produced by me squinting at all the lines, coloring in some areas that seemed more connected in a paint program, and picking silly names for the areas. I’ve enjoyed publishing a lot of data-driven stories since then, but I’ve never ceased to be disturbed at how the inclusion of numbers and the mention of large data sets numbs criticism. Why are data scientists getting all the attention? What am I doing about it? What should you do? Like this: Like Loading...
Data Visualization usages during the Australian federal election If Australia’s federal election result – the first hung parliament since 1940 – has taught us anything, it’s that reluctance to act and indecision gets you nowhere. But what else have we learnt from this otherwise forgettable display of shallow catch-cries and me-too-ism? At Yellowfin, we realized that perhaps the only positive lesson to be taken from this debacle, was that the use of visual technologies can be a powerful ally for explaining, conveying and consolidating ideas, trends, goals and projections. During the election campaign, a range of media and political parties used graphical representations of key information and data, in varying forms, to convey various economic, environmental and parliamentary concepts. When it came to election night that’s when the numbers really started to come into their own. One of the best visual displays for an election we feel is the electorate map, and the best example of this this time round was on The Age web site.
MOOCs and beyond - Chancen, Risiken und Folgen digitaler Bildungsangebote für die deutsche Hochschullandschaft - Livestream Hier finden Sie eine Übersicht der Videomittschnitte: Eröffnung der Tagung Die digitale Gesellschaft als politische Herausforderung Ulrich Schüller, Abteilungsleiter, Abteilung Wissenschaftssystem, Bundesministerium für Bildung und Forschung, Berlin Keynote How learning technologies are changing global higher educationProf. Vortrag "Hochschullehre digital - Erfahrungen vom Seminar bis hin zum massiven Kurs"Prof. Eröffnung des Gallery Walks: Kurzpräsentationen der Stände "Potenzial von offenen Onlinekursen aus Sicht der europäischen Hochschulen"Michael Gaebel, Head of the Higher Education Policy Unit, European University Association Personalisierung trotz Massifizierung Wie Digitalisierung die Hochschullehre verändern wirdDr. Podiumsdiskussion Konsequenzen der Digitalisierung der Hochschulbildung für deutsche Hochschulen Ulrich Schüller, Abteilungsleiter, Abteilung Wissenschaftssystem, Bundesministerium für Bildung und Forschung, Berlin Prof. Ulrich Schüller Dr.
10 Traits of Amazingly Awesome Infographics Honestly, who doesn't love infographics? They're informative, visually stimulating, and they allow you to easily digest a ton of information quickly. What this usually results in for marketers is a high rate of social sharing that generates a lot of web traffic and precious inbound links to increase SEO. But truthfully, not all infographics are such big hits. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. Want some more examples of effective infographics? Have you ever created an infographic for your business?
A New Data Visualization Paradigm? A triviality to start with: significant data growth It has been stressed over and over again, and there is no need to over-emphasize it here: every individual and every corporation both benefit and suffer from the massive data growth. They benefit because they can get access to more, more up-to-date and more precise information – about their customers, their markets, their suppliers and partners as well as their competitors and also employees and internal processes. However, they also suffer, as they have to deal with the increasing amount of data, have to manage and to store it, and have to enable decision makers to get fast access to only the relevant data. Data-driven decision-making and the need for speed The importance of fueling decision-making processes with data visualization not only stems from the data growth phenomenon. Decentralization of planning and decision-making Until recently, many decision processes were centralized as this approach guaranteed speed and control.
The Open Source Data Science Masters by datasciencemasters Global business intelligence spending to double in four years Spending on business intelligence (BI) software and services will reach $143.3bn in 2016, with two-thirds of this being invested in services. In 2012, the global BI sector was worth $79bn, according to research carried out by business and technology analyst firm Pringle & Company, but this is expected to increase an average of 16% for the next four years. Two-thirds of the money spend on BI will be services related, as for every $1 invested in BI software, $2 will be spent on services designed to maximise its performance. The fastest growing part of the BI sector is analytics tools, with 18.8% growth in software spending and 20.9% growth in services spending, adding up to a market worth $18bn by 2016. Pringle & Company principle analyst Tom Pringle said as data volume and variety grows ever bigger, the necessary investment in technology and services to understand and successfully exploit its value will have to rise. Image: iStockphoto/Thinkstock Email Alerts
Who's Really Using Big Data - Paul Barth and Randy Bean by Paul Barth and Randy Bean | 11:00 AM September 12, 2012 We recently surveyed executives at Fortune 1000 companies and large government agencies about where they stand on Big Data: what initiatives they have planned, who’s leading the charge, and how well equipped they are to exploit the opportunities Big Data presents. We’re still digging through the data — but we did come away with three high-level takeaways. First, the people we surveyed have high hopes for what they can get out of advanced analytics. Second, it’s early days for most of them. High expectations. 85% of organizations reported that they have Big Data initiatives planned or in progress. 70% report that these initiatives are enterprise-driven. 85% of the initiatives are sponsored by a C-level executive or the head of a line of business. 75% expect an impact across multiple lines of business. 80% believe that initiatives will cross multiple lines of business or functions. Capabilities gap. Problems with alignment? More >>
How to Justify Data Virtualization Investments Proving compelling return is critical for any investment today. This is especially important for IT investments which are often an enterprise or government agency's largest capital expense. Technology for technology's sake does not cut it. Increasing business complexities and a plethora of technology choices creates greater-than-ever demands for diligence when making IT investments. IT Business Case 101IT business cases must demonstrate value through tangible business and IT metrics that align with the strategic objectives of the business units that they serve. Further, not only must this value be proven, it must be proven early in the acquisition process to justify technology evaluation efforts and then re-proven again after implementation to justify expanded adoption. Data Virtualization Value PropositionsThere are many ways that data virtualization can deliver value to your business functions and IT operations. Sales Growth Risk Reduction Time Savings Technology Savings Staff Savings