With the use of Amazon Web Services for example, one can easily rent a lot of computing power to perform either one-time or permanent large data analysis. Also, since one of the most looked-at is commercial user behavior, a lot more man power has been invested in building tools to handle large data analysis, as for example the work going on at the Apache Hadoop project. Although this is a pretty low level library, it already makes it much easier for developers to handle large sets of computers to handle various problems, may they be data analysis or any other form of extreme computing loads
After writing the last blog on The Ocean of Big Data and its seeming repetition of past Data Warehousing implementation issues and challenges, I decided to further “educate” myself. Who knows, maybe you actually can teach an old dog new tricks! So, I re-read John Mancini’s ...
While I do agree that activity streams will take a larger piece of our mindshare over the next few years, expanded to collect data from any transactional system we connect with to show an even more accurate picture of what we do during the day (from a business perspective, mainly), allowing others to comment, rate, Like, search, and connect with those activities -- all of which will lead to even more possibilities with search and data analysis. If there is any kind of killer app in the next few years, my bet is in the area of business intelligence -- to filter through and organize all of this new data being created
With that said, the only relationship that it will have with your marketing strategy is that it will provide the foundation of what the goal and focus should be Use of data analysis is useless if there is no one there to relate it to the company, the company’s mission and what consumers are looking for
Image-only files are useless in data analysis. Therefore, in order to take the all-important first step in exploiting all of your content is to apply indexes so that computer systems can properly begin to understand the information
Such basic normalizations will not only dramatically reduce the size of the data set, it will also result in better data analysis and visualization: entities that would not be related without normalization can be the missing link between two datasets especially if they are written differently in different parts of the data set or if they are not recognized as being a singular or plural entity properly
For a company, I would think this is a wake up call to be careful about what is said in its social media avenues and to warn employees to be equally careful about posting their travel plans, creating blogs and responding to blogs as all of this can be gathered and put through a data analysis program to establish a profile of your company
" I have written a number of times on the simple idea of increasing your sample size for more accurate data analysis, or in expanding your network to include people or ideas you are not as familiar with while at the same time improving the filters through which you consume data -- allowing you to experience ideas and perspectives that you would not otherwise experience in your limited, closed-off network
They will either jump into it (at the expense of other projects) because it’s the hip new thing to do or so they can tell their board “ Big Data, we’re all over that. ” Or, some upper management pinhead will buy into some smarmy Big Data Analysis service, like the ones that are behind the webinars I am being invited to on an almost weekly basis
4 Comments - no search term matches found in comments.
In recent weeks, IBM has announced the purchase of Open Pages and Netezza and then IBM's strategy for ownership of the most relevant solutions of content and data analysis and management becomes more concrete!
1 Comment - no search term matches found in comments.
8403 Colesville Rd #1100Silver Spring, MD 20910USA
Phone: (301) 587-8202Toll free: (800) 477-2446Fax: (301) 587-2711Email: hello@aiim.org
JoinBenefitsLearn More
About UsTerms of Use