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 Big Data | The volume of digitally recorded information has increased exponentially in recent years and has made the term Big Data omnipresent. Purchasing books online, chatting with friends on social networks, and downloading videos on mobile phones, are just a few of the activities that contributed to a total of 1.8 zettabytes (1 trillion gigabytes) of stored data sets in 2011. By 2015, this amount is predicted to grow to 7.9 zettabytes.
Big Data is defined by four characteristics: data volume, variety, velocity, and value, while often lacking structural or organizational patterns. In order to effectively use the vast amounts of data obtained from consumer activity, it is necessary to engage professional data analysts and software to evaluate and organize this complex information. By "separating the signal from the noise," commercial and government organizations are then able to gain actual insights into customer behavior and needs and as a result, enhance products and services.
The increased availability of smart, connected devices combined with an unprecedented level of memory processing capacities as well as significantly reduced storage prices created new challenges for the handling of digital data. Since Big Data information is often an unintentional byproduct of general user, buyer, and customer activity, the ubiquitous information collection has raised concerns about privacy and data protection.
Two upcoming events at the GCRI on May 16 and June 27 with Dr. Jeanette Hofmann from the Social Science Research Center Berlin (WZB) and Gerhard Weikum, Research Director at the Max-Planck Institute for Informatics (MPII), will address the benefits and future challenges of Big Data. Please visit our website for more information.
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Thoughts on Big Data Dr. Hofmann will speak at the upcoming GCRI event, "Temptations of Big Data," on May 16, 2013.
The term Big Data has been in use since 2008, but only in 2012 did it hit the mainstream media. For some, Big Data indicates a new era where data sets measured in petabytes and larger have become the norm. Critics, on the other hand, find nothing new in Big Data. Census data, they argue, have always been big. The term Big Data may thus fall into the category of what the Canadian philosopher Ian Hacking calls "elevator words." Definitions of elevator words are vague, if not circular, and their value is volatile. Big Data applications that sound promising today might be associated with data leaks and surveillance tomorrow. For now, however, Big Data connotes new ways of aggregating, analyzing, and exploiting data.
Interestingly, 75% of online data is generated by individuals while 80% is held by companies. Big Data creates economic value. If AGFA (Apple, Google, Facebook and Amazon) constituted an economy, it would already be the 49th largest out of 194. From a user's perspective, Big Data looks like a double-edged sword. No doubt, society benefits from a rapidly growing array of new information services that make everyday life more convenient. At the same time, the quality of many personalized information services depends on the amount of data about us that is stored. With the use of digital assistants and other smart phone applications, we are disclosing increasing amounts of information about ourselves without knowing the future consequences of such informational generosity.
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Benefits and Challenges of Big Data: Interview with Prof. Dieter Kempf
In this GCRI interview, Prof. Kempf discusses benefits and challenges of Big Data accumulation and technologies in Germany, especially with regard to legal frameworks and privacy issues. Since July 1996, Prof. Kempf has served as Chairman of the Executive Board of DATEV eG, a software company and IT service provider for tax consultants, auditors and lawyers. He began his career as a DATEV board member in 1991 where he was in charge of the divisions of product and software development. Prior to working with DATEV, Prof. Kempf was an auditing assistant with a specialization as electronic data-processing (EDP) auditor for Arthur Young GmbH auditing firm (later Ernst & Young GmbH), and completed internships in France and the U.S. In 1984, he became authorized signatory and leader of the EDP-Auditing and EDP-Consulting Group at Arthur Young. Subsequently, Prof. Kempf served as Partner (shareholder-managing director) from 1989 until 1991.
Prof. Kempf became Associate Professor for Business Administration at Friedrich-Alexander-University Erlangen-Nuremberg in 2005. He was born in Munich and holds a diploma in Business Administration from Ludwig-Maximilians-University in Munich.
To read the interview, click here.
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Fraunhofer Big Data Survey Shows Potential for Business - Big Data fosters more effective business management
- Big Data facilitates mass customization
- Big Data leads to more intelligent products
69% of the survey participants listed strategic competitive advantages as their company goal for Big Data use: 61% want to increase sales, while 55% want to achieve higher productivity and cost reduction. Although all participants indicated specific goals, one third of the companies still lack the budget for Big Data purposes or haven't planned accordingly yet.
The Big Data Living Lab, which allows companies to try out sample data sets to experience the possibilities of targeted data evaluations, was introduced earlier this month at the 2013 CeBIT trade show. CeBIT is the world's leading high-tech event showcasing digital IT and telecommunications solutions and takes place annually in Hannover, Germany.
For more information on the survey, click here.
Source: Fraunhofer IAIS press release "New Big Data survey shows potential for business," December 13, 2012
Photo © Fraunhofer IAIS
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Innovation: SAP HANA
Whenever companies have to go deep within their data sets to ask complex and interactive questions, and have to go broad (which means working with enormous data sets that are of different types and from different sources) at the same time, SAP HANA is well-suited. Increasingly there is a need for this data to be current and preferably in real-time. Add to that the need for high speed (very fast response time and true interactivity), and the need to do this without any pre-fabrication (no data preparation, no pre-aggregates, no-tuning) and you have a unique combination of requirements that only SAP HANA can address effectively. When this set of needs or any subset thereof have to be addressed (in any combination), SAP HANA is in its element.
SAP HANA allows for faster business processes, smarter business innovations, and a simplified IT landscape while opening the door for inventive ways to optimize the business and remain ahead of the competition.
Learn more about SAP HANA here.
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Big Data Privacy Issues in Public Social Media Big Data is a new label given to a diverse field of data-intensive informatics in which the data sets are so large that they become hard to work with effectively. The term has been used primarily in two contexts: First, as a technological challenge when dealing with data-intensive domains, such as high energy physics, astronomy or Internet search, and second, as a sociological problem when user data is collected and mined by companies such as Facebook, Google, mobile phone companies, retail chains, and governments. We investigate the second issue from a different perspective - in particular, how users can gain awareness of the personally relevant Big Data information that is publicly available on the social web. The amount of user-generated media uploaded to the Internet is rapidly expanding to the point where it is beyond human capacity to sift through all the content to see which media impact our privacy. Based on an analysis of social media use on Flickr, Locr, Facebook, and Google+, this paper discusses privacy implications and the potential of the emerging geo-tagging trend in social media. It also presents a concept with which users can stay informed about which parts of the social Big Data deluge is relevant to them.
Click here for more information.
2012 IEEE International Conference on Digital Ecosystems Technologies (DEST), 18-20 June 2012, 1-6.
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