SCSU Analytics

it enables businesses to have a more unlimited view of data

Data lakes are defined as "a massive, easily accessible, centralized repository of large volumes of structured and unstructured data".

businesses must have some use cases in mind before constructing a data lake.

COMPARISON WITH ON-PREMAzure SQL is SQL Server behind the scenes, so most of the functionality is already there including tables, views, stored procedures, triggers, functions, primary and foreign keys and clustered indexes.

There is no to need maintain, balance, upgrade or patch the server as this is all done by Microsoft.

mport your data to our survey data analysis software from all major survey programs and file formats. SurveyMonkey SurveyGizmo QuestionPro Qualtrics Survey Analytics Snap Surveys Toluna QuickSurveys Super Simple Survey SPSS (.sav) Triple-S (.xml or .sss) IBM SPSS Data Model (.mdd) Excel (.xls or .xlsx) CSV (.csv)

he chart below originally accompanied our story 22 free tools for data visualization and analysis (April 20, 2011). We're updating it as we cover additional tools, including 8 cool tools for data analysis, visualization and presentation (March 27, 2012) and Six useful JavaScript libraries for maps, charts and other data visualizations (March 6, 2013). Click through to those articles for full tool reviews.

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"Students who worked out at Purdue's gym at least once a week were more likely to earn a higher grade point average than students who visited less or not at all,"

the more than 1,820 students who visit Purdue's France A. Córdova Recreational Sports Center at least 16 times a month earned a GPA of 3.10 or higher. The correlation between grades and gym use also is shown with moderate users. Students who used the gym at least seven times a month had an average GPA of 3.06

Exploiting Library of Congress metadata, the Photogrammar team created a web-based platform for organizing, searching, and visualizing the 170,000 photographs from 1935 to 1945

Student Success Implementation

Technology Initiative:

(a) predictive analytics,

R resides in an interestingly large gap between the other domain-specific languages, SAS and SPSS. R has not only caught up with SPSS, but surpassed it with around 50% more job postings. MATLAB has many similarities to R so it’s interesting to see that it has only around half the job postings. Note that these are specific to analtyics and MATLAB has many engineering jobs that are not counted in this total.

SAS is still far ahead of R in analytics job postings

Figure 2a shows the number of articles found for each software package for all the years that Google Scholar can search. SPSS is by far the most dominant package, likely due to its balance between power and ease-of-use. SAS has around half as many, followed by MATLAB and R.

5. Enough with the text, already

1. Present data that matter to your audience (and not just you)

Data scientists by definition are naturally inquisitive and love to quantify things. That makes them a good fit for the job. The bad news is that they sometimes become a little too enthusiastic about data for data’s sake and will overwhelm their audience with irrelevant information.

Azure Machine Learning is a public cloud-based service that lets developers embed predictive analytics into their applications

Machine learning software has been around for years but isn't easy to use or deploy, and it's also expensive, Sirosh said. Packaging up machine-learning-as-a-cloud service solves these problems, and by being first to bring it to market, Microsoft has a head start on the likes of Google, Amazon and IBM, he said. "I think, on this particular front, that we are the leaders," Sirosh told CRN.   

Hiring Sirosh was something of a coup for Microsoft. He joined last July from Amazon, where he spent close to nine years as a vice president in various machine-learning-related roles.