Business beneifits slide enforces doing the planning work upfront and a tailord approach to the business model/context enables better marketing programs and forecasts to identifying new business opportunities.
Brings attention that Analytics projects requires alot of planning; platform, gathering data, analysis of data, making it interactive and visual presentation so that management and customers see the outcomes.
@Beth - well - database size is important - it directly correlates to processing power - that said, the idea of using Hadoop or other "slice and dice" data systems brings parralell processing power to large data sets
Just for the benefit of the people !! I can think of two usecases which are currently used at my company. One mobile app developed for field marketing people to capture useful information from the prospective customers during major launch events and other one is, company app being used for capturing the location of employees for doing demographic study analysis for new campus movements !!
@Pierre - there are countless ways to visualize the data - so, the real question becomes what type of data are they trying to visualize? So, more importantly, one has to know what type of questions they want to ask of the data - before selecting a particular visual reprsentation
Hi Frank, you mentioned about developing a visual approach for the enduser - can you provide an example for for forming enduser questions that can tease out what kind of visualizations may be useful? It seems like we have a variety of ways to display data.
If the analytics are deployed and a offsite person can query and get answers. In most cases that is planned. The main advantage of having mobile analytics is able to respond to questions that arise randomly. Then the offsite person needs to be trained well... in using the app.
Frank, I have a few questions for you! For one, do you think mobilizing analytics calls for a self-service interface that allows mobile users to manipulate the data more so than if they were in the office?
I first extrat the citation graph between the papers, then extract citation sentences that mention a given tool, or techniques described in the papers and then compute the similarity scores between the citation sentences and the text they refer to in the cited papers
I think visual helps, but we're still in a state where what kind of visual varies. if we help the enduser articulate what the end use of the data is, we can develop a visual display that is valuable in the field.
"GIS is frequently confused with GPS because it is a more generic acronym (Geographic Information System) used to describe a more complex mapping technologythat is connected to a particular database. Because it's generic, it is a broader term than the GPS in its technical sense."
I am more astounded by how much influence APIs is leading to much of the mobile data analytics. Means really seeing how a source influences measurement assumptions and the interface being created for BI
I'm Trying to set up a Cluster to process Master Data while I'm waiting... But I've been keeping an eye on this too... Wish I had these Servers for Home use... these three machines are just Sick! *GRIN* combines 96 Cores, little over Half a TB of RAM!... I wish I had one at home... hahahahaha!
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