In general, computer scientists treats code and data in two very different ways. Virtual memory was originally developed to run big programs (code) in small memory, while data are entities kept in external storage and must be retrieved into memory before computing. As a result, today’s application developers think by instinct the programming model based on storage and explicit data retrieval. This model, referred to as storage-based computing, plays an important role and has done a great job…Continue
Added by Yuanjen Chen on October 31, 2013 at 7:24pm — No Comments
Added by Vincent Granville on October 31, 2013 at 9:30am — No Comments
The term "critical thinking" is often found in job postings. Some would argue that this essentially means, "Thinking outside the box." Karl Marx, who asserted that labourers represent a class of people, has been described as a critical thinker. Regardless of how a person feels about Marx, it goes without saying that the phenomena of social classes is well-established. Politicians for instance fight for the support of the "middle class." How precisely does such an observation by this…Continue
Added by Don Philip Faithful on October 30, 2013 at 4:25pm — No Comments
Added by Mitchell A. Sanders on October 29, 2013 at 1:30pm — No Comments
Smart organizations are using the power of data science and data produced by embedded sensors and machine devices to better measure performance, discover patterns, prevent problems, and improve…Continue
I'd add an 11th one as well: you check data science sites before you check news sites in the morning!
10. You think … “So much data, so littl…”
9. You know what heteroscedasticity is.
8. Your best pick-up lines all include the word “moneyball.”
7. You look at your grocery…Continue
To be short, in-memory computing takes advantage of physical memory, which is expected to process data much faster than disk. In-place, on the other hand, fully utilizes the address space of 64bit architecture. Both are gifts from the modern computer science; both are essences of the BigObject.
In-place computing only becomes possible upon the introduction of 64bit architecture, whose address space is big enough to hold the entire data set for most of cases we are dealing with today.…Continue
Added by Yuanjen Chen on October 29, 2013 at 1:00am — No Comments
Big Data is big in nature, however Education data is not that big yet compared to Big Data. Quantitative analysis, Audio-Video recorded data of Education related research and general research work conducted by the academic institutions is steadily increasing. The data change is started within our education system as our students are taking exams, courses, conducting their research using computerized means. This means that the searching behaviors of students or whoever associated with…Continue
Added by Atif Farid Mohammad on October 27, 2013 at 7:39pm — No Comments
In this blog post, I describe my early experiences leading me to conclude, data as we know it tends to be "disembodied" - that is to say, often lacking any kind of connection to different types of bodies. When we talk about things being disembodied, I suspect some form of decapitation is…Continue
Added by Don Philip Faithful on October 27, 2013 at 1:30pm — No Comments
STEM is an acronym for the fields of science, technology, engineering and math and it has a push within United States, however there is a big factor is not taken into consideration yet by the masses in the world of Education, and that is the best use of Big Data. This is a lacking factor, as we are still exploring Big Data and its utilization at a novice level by our selves. Education by itself is a huge and vast field to conduct the research, by have an exploration within the research…Continue
I have always found the task of converting qualitative data into something quantifiable a bit challenging. A common route might be as follows: assemble all of the resources containing qualitative information (e.g. questionnaires containing open-ended questions); seek out apparent themes in the responses; and quantify how frequently these themes are mentioned or raised. This methodology leaves open the question of when something is or isn't a theme, and whether something must be a theme in…Continue
Added by Don Philip Faithful on October 25, 2013 at 7:49pm — No Comments
I have so far encountered two general types of data . . .
This is data that conforms to prescribed criteria. I sometimes describe it has the metrics of criteria or measurements of conformity. For instance, an organization might want to measure something potentially obscure like "efficiency." It therefore becomes necessary to establish under what conditions or criteria something is efficient. I describe…Continue
Added by Don Philip Faithful on October 24, 2013 at 1:05pm — No Comments
Before you select the best model based on your favorite goodness of fit statistic – Mean Squared Error, Gini, K-S, AUC, or misclassification rate – STOP! Model performance metrics are not a one size fits all measure. As an analyst, selecting the right performance metric might mean the difference between having an exceptionally good result, and having no result.
The classic example: There is only a 3% prevalence of the event of interest in my…Continue
Added by Laura E. Wood Squier on October 24, 2013 at 8:00am — No Comments
This is my first post here. I'm glad to introduce this newly launched big data analytic engine, the BigObject. In the past 2 years we have been working on an optimal approach to handle big data for analytic purposes and challenging the existed models, some assumptions of which are no longer valid. For example, as the data size grows so rapidly, is it still practical that we stick to the relational models neglecting the time spending in data retrievals? What impact did…Continue
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Here is a refresher from the last post:
“I went on a job board and searched for the number of job postings that listed Big Data tools as part of the requirements.”
I created a comprehensive list for Big Data skills in response to the…Continue
A mathematical problem related to big data was solved by Jean-Francois Puget, engineer in the Solutions Analytics and Optimization group at IBM France. The problem was first mentioned on Data Science Central, and an award was offered to the first data scientist to solve it.
Bryan Gorman, Principal Physicist, Chief Scientist at…Continue
While discussing the value of Big Data in helping to shape a customer-centric brand in my last Intel IT Center article,…Continue
There has been much discussion and debate about the definition of data science and the new rare breed of sexy bird called the data scientist. The …Continue