Wednesday, May 18, 2016

How to Create Sample Application with Ruby on Rails

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You’ve probably already used many of the applications that were built  with Ruby on Rails: Basecamp, GitHub,Shopify, Airbnb, Twitch, SoundCloud,Hulu, Zendesk, Square, Highrise. Those are just some of the big names, but there are literally hundreds of thousands of applications built with the framework since its release in 2004. 
Ruby on Rails is open source software, so not only is it free to use, you can also help make it better. More than 4,200 people already have contributed code to Rails. It’s easier than you think to become one of them.
Ruby on Rails for Developers
Ruby on Rails for Developers
Optimizing for programmer happiness with Convention over Configuration is how we roll. Ruby on Rails has been popularizing both concepts along with a variety of other controversial points since the beginning. To learn more about why Rails is so different from many other web-application frameworks and paradigms, examine The Rails Doctrine

Rails is a web application development framework written in the Ruby language. It is designed to make programming web applications easier by making assumptions about what every developer needs to get started. It allows you to write less code while accomplishing more than many other languages and frameworks.

How to create Ruby on Rails Sample application: Click Here

Wednesday, May 11, 2016

2 Major Differences Between Computer Science and Information Science Courses

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Computer Science:

Computer scientists are, in fact, scientists. They are focused with the theory of computational applications. That means they understand the “why” behind computer programs. Using algorithms and advanced mathematics, computer scientists invent new ways to manipulate and transfer information. Computer scientists are generally concerned with software, operating systems and implementation.
Like Neo in The Matrix, computer scientists can see and make sense of code. Computer science students will learn the fundamentals of different programming languages, linear and discrete mathematics, and software design and development. Computer scientists study the machine itself and understand how and why various computer processes operate the way they do.
Computer Science Vs Information Science
Computer Science Vs Information Science

Information Science:
To put it bluntly, computer engineers make computer parts work together. Computer engineers are responsible for the research, design and development of computer equipment like circuit boards, microchips, routers, video cards, etc. Some universities may treat this discipline as an off-shoot of electrical engineering.
It is beneficial for computer engineers to have a grasp of computer science. Computer engineers often deal with hardware-to-software integration, meaning they have to design and build processors and hardware that can support a given program. As technology advances and our devices become smaller and smaller, a main goal of computer engineers is to create microchips and microprocessors that work economically and efficiently.
Computer engineering students will study concepts in computer science, engineering and mathematics. By combining these three fields, computer engineers are able to solve hardware problems and create state-of-the-art machines that can handle the many tasks computers perform. 

Thursday, April 21, 2016

SPARK is Replacement for MapReduce in Bigdata Real Analytics!

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Apache Spark is among the Hadoop ecosystem technologies acting as catalysts for broader adoption of big data infrastructure. Now, Looker -- a vendor of business intelligence software -- has announced support for Spark and other Hadoop technologies. The goal? To speed up access to the data that fuels business decision making.

Hadoop's arrival on the scene 10 years ago may have started the big data revolution, but only recently did adoption of this technology begin spreading to a wider audience. Apache Spark is one of the catalysts for the growing adoption rates.

Spark can be used as a replacement for MapReduce, a component of Hadoop implementations, to speed up the processing and analytics of big data by 100x in memory, according to the Apache Software Foundation.


In today's business environment, in which real-time analytics is the goal and organizations don't want to wait for data warehouses and analysts to provide batch intelligence back to business users, Spark has gained momentum.

And here's one case in point: Looker, a business intelligence platform used by Avant, Acorns, and Etsy, this week announced support for Presto and Spark SQL. The company also updated its support for Impala and Hive, other Hadoop ecosystem technologies that speed up analysis on Hadoop.

Looker's announcement of support for these additional Hadoop ecosystem technologies lets organizations "leave data in Hadoop and process it at speed and at scale," said James Haight,

Read more here.

Wednesday, April 20, 2016

SPARK is Leading Skill Set Fetching More Jobs

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Spark: With job postings up 120% year-over-year on Dice, demand for this open-source cluster-computing framework is broad-based. Government contractors and financial-services firms are just a few of the groups eager to find candidates with this skillset.
2015 Average Salary: $113,214


SPARK Jobs
Big Data and Cloud: As companies expand their tech infrastructures, they need cloud and Big Data services such as Azure (#2), Hive (#8) and Cassandra (#9) for data storage, analysis and security. Big Data and cloud-related skills dominated the Highest Paid Skills list on Dice’s salary survey for the second straight year.
2015 Average Salary: 
Big Data—$121,328
Azure — $110,207


Salesforce: This customer-service platform serves as the bedrock for many companies’ customer service departments. Demand for Salesforce professionals seems unlikely to decline anytime soon. Employers are even willing to offer telecommuting options to lure Salesforce talent.
2015 Average Salary: $107,810

JIRA: JIRA, a project-management platform that’s free for open-source projects and nonprofits, has enjoyed an increasing rate of adoption over the past few years. With software teams always on the lookout for professionals with project-management experience, counting JIRA among your core skills is a great way to stand out.
2015 Average Salary: $111,103

Wednesday, April 13, 2016

Chaid a Skillset for Data Science Engineers

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Chaid is one of the Chaid is one of mostly asked skills for Data Science engineers.The CHAID Analysis (Chi Square Automatic Interaction Detection) is a form of analysis that determines how variables best combine to explain the outcome in a given dependent variable. The model can be used in cases of market penetration, predicting and interpreting responses or a multitude of other research problems.

CHAID analysis is especially useful for data expressing categorized values instead of continuous values. For this kind of data some common statistical tools such as regression are not applicable and CHAID analysis is a perfect tool to discover the relationship between variables. One of the outstanding advantages of CHAID analysis is that it can visualize the relationship between the target (dependent) variable and the related factors with a tree
image.
Best IT Skills
[ Best IT Skills ]
Different Scenarios where CHAID analysis can be used:

CHAID Analysis for Surveys -Most survey answers have categorized values instead of continuous values. Finding out the statistical relationship in this kind of data is a challenge. CHAID Analysis is a good solution for such survey studies.

Related: How to Make Career Change from Mainframe to Data Analyst

CHAID Analysis for Customer Profiling -Based on historical customer data, CHAID Analysis can be used to analyze all characteristics within the file, for example, product/service purchased, dollar amount spent, major demographics and demography of the customers, and so on.

A blue print can be produced to provide an understanding of the customer profile: strong or weak sales of products/services; active or in-active customers; factors affecting customers’ decisions or preferences, and so on. Such customer profile will give the Sales & Marketing Team a clear picture of which type of person is most likely to buy the products and services based on factual purchase history, geo-demographics and lifestyle attributes.

CHAID Analysis for Customer Targeting -Recruiting new customers via direct contact (phone or mail) is a time consuming and costly effort. For most products or services, the hit rate is less than 1%. That means, in order to get a new customer, over one hundred contacts are required.

By mapping the current customer list to a general population database (e.g., SMR Residential Database that contains 12 million listed households), CHAID Analysis can find the household clusters that have much higher incidence rates than the average. By concentrating on these household clusters, the actual hit rate can be dramatically raised. The result is “Fewer phone calls or mail pieces with higher sales returns!” .

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