Big Data
Big Data Management: Possibilities and Challenges
The term big data describes the volumes of data generated by an enterprise, including Web-browsing trails, point-of-sale data, ATM records, and other customer information generated within an organization (Levine, 2013). These data sets can be so large and complex that they become difficult to process using traditional database management tools and data processing applications. Big data creates numerous exciting possibilities for organizations, but along with the possibilities, there are challenges. Managers must understand the pitfalls and limitations, as well as the potential of big data (Levine, 2013).
The focus of this report is the business potential and implications of big data as well as understanding the challenges and limitations of big data management. The potentials for big data are numerous; however, in this report only five potentials and implications for use are discussed. These include the following: knowledge management, social media, in travel, banking, and marketing and advertising.
Knowledge Management One of the greatest potential for big data is knowledge management. A goal of knowledge management is the ability to integrate information from multiple perspectives to provide the insights required for valid decision-making such as where to invest marketing dollars, how much to invest, or whether to expand into a new geographic market (Lamont, 2012).
In terms of knowledge management, three dimensions describe big data: volume, variety, and velocity (Lamont, 2012). Volumes mean breaking up huge amounts of the data, sending out subsets for analysis, and then regrouping the results to produce the output. Variety is a factor because many different types of data may be pertinent to an analysis. For example, social media feeds such as Twitter are able to combine their analyses to include information from both structured relational databases and content such as videos and Tweets. Velocity is a
The term big data describes the volumes of data generated by an enterprise, including Web-browsing trails, point-of-sale data, ATM records, and other customer information generated within an organization (Levine, 2013). These data sets can be so large and complex that they become difficult to process using traditional database management tools and data processing applications. Big data creates numerous exciting possibilities for organizations, but along with the possibilities, there are challenges. Managers must understand the pitfalls and limitations, as well as the potential of big data (Levine, 2013).
The focus of this report is the business potential and implications of big data as well as understanding the challenges and limitations of big data management. The potentials for big data are numerous; however, in this report only five potentials and implications for use are discussed. These include the following: knowledge management, social media, in travel, banking, and marketing and advertising.
Knowledge Management One of the greatest potential for big data is knowledge management. A goal of knowledge management is the ability to integrate information from multiple perspectives to provide the insights required for valid decision-making such as where to invest marketing dollars, how much to invest, or whether to expand into a new geographic market (Lamont, 2012).
In terms of knowledge management, three dimensions describe big data: volume, variety, and velocity (Lamont, 2012). Volumes mean breaking up huge amounts of the data, sending out subsets for analysis, and then regrouping the results to produce the output. Variety is a factor because many different types of data may be pertinent to an analysis. For example, social media feeds such as Twitter are able to combine their analyses to include information from both structured relational databases and content such as videos and Tweets. Velocity is a
References: Bergstrand, J. (2013)) The big challenges of big data. Drucker Institute. Retrieved from http://thedx.druckerinstitute.com/2013/08/the-big-challenges-of-big-data/ Essential Guide (2013) Guide to big data analytics tools, trends and best practices. Retrieved from http://searchdatamanagement.techtarget.com/definition/big-data-management HP (2012) Business-value white paper | Information optimization. Retrieved from http://www8.hp.com/us/en/business-solutions/big-data.html Information Management (2013) 7 Tips to Succeed with Big Data in 2013http://www.information-management.com/white_papers/-10023957-1.html Lamont, J. ( 2012). Big data has big implications for knowledge management. Retrieved from http://www.kmworld.com/ Levine, S. R. (2013). Guest opinion: Management 's big data challenge. Credit Union Times, Retrieved from http://search.proquest.com/docview/1286965135?accountid=35812 Rouse, M (2011). Retrieved from: http://searchcloudcomputing.techtarget.com/definition/big-data-Big-Data