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Knowledge Series: What is Google Trends Data Mining Using R Programming?

What is Google Trends Data Mining Using R Programing?

Mostly misunderstood as a keyword research tool, Google trends are much more than that. Google trends were not merely built to give a match to monthly keyword volume, Google trends were built with an advanced level of sophistication, to generate insights which are visual and dynamic in nature. Google trends are capable of presenting an entire life cycle of a keyword phrase, past, present and some kind of future as we may predict. So, what are Google trends exactly? It is essentially a service that brings together the relative frequency of Google searches over a period of time.

Google trends tool opens the possibilities to obtain incredible amounts of information from one of the world’s largest search engines. The google trends tool is derived from Google search data. ‘Trends’ to simply put it is numeric and also a historic representation of the search data. This feature differentiates google trends from google keyword planner, as in google trends, an index is created to represent the ‘trending’ instead of the definite volume. Therefore, the data presented by google trends can actually depict actionable insights which the keyword planner function cannot present.

Google trends thus adapt a multi-dimensional approach of comparing queries against required options. It is a fairly simple tool to use. To start one needs to put a search term in the query box, and then you can proceed to select from the various filtering options. Like…

  • Region – search definition can be Geo-specific
  • Time Frame – you can select a variety of predefined time frames. Like ‘last seven days’, ‘one month, etc…, you can go back in time up to the year 2004.
  • Categories – one can select and limit the terms and focus only on a certain category. This way you will be able to study specific trends with the possibility of discovering new searches or themes.
  • Engines– through this option you can choose between news, youtube, shopping search, thus offering increased flexibility and further allowing to choose focus on the right to intend.

All the results are presented as separate graphs,
(a) Interest over time, which offers a historical trending,
(b) Regional Behavior, offering on how localized behavior was during that time.

One can use ‘R’ to extract the data from google trends using ‘gtrends’. Using Google trends one can perform the simultaneous search on five terms, more than five terms are not possible, also it does not provide data in API format. These issues can be dodged using R especially by using ‘gtrends’ package. There are various functions in R that can be used to build automated solutions, which can be further applied to build end to end solutions.

Google trends thus become a powerful tool especially for a data scientist or even a marketing analyst’s inventory.
For the marketing department of any company or brand, google trends are like a goldmine of information that could perhaps supersede findings from focus groups, on other metrics like brand health by the region, or brand topics of discussion over a period of time. Once you understand what the consumers for a particular brand are searching for, you can start building your messages around those areas of opportunity and interest.

As with any data-driven insights, the flexibility and the opportunity that Google trend offers with tools like gtrendsR, the possibilities are fathomless. Learning the applicability of data mining using R on google trends will surely be very valuable in the long run.

  • October, 26th, 2017
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Is SAS The Best Programming Language?

Like many great debates that run over centauries, comparison of SAS with other programming languages, discussing their pros and cons, is a common and continuous process. It is a point of consideration between analytics for long now, on the language of choice, SAS or Python or R.

The technological advancements are so dynamic, that this debate can take place every couple of years and get answers that can sway on either sides. In this blog, we will discuss the global trends and the ecosystem of SAS, by itself of what SAS offers, and about the advantages of knowing SAS as a language.

Commercial analytics has always seen a strong presence of SAS as SAS offers a huge collection of statistical functions. SAS has a good support system to aid quick adaptation of the language, SAS provides excellent technical support. The only areas that work against SAS is the cost, it is the most expensive option and it lags in terms of latest statistical functions, when compared with other languages like R and Python.

To make an informed decision about SAS being the best programming language, let’s understand all the attributes of the language.

In terms of Convenience and Price, lets accept that SAS is a commercial software, hence it is expensive and not very affordable for most of the professionals. So unless you are associated with an establish institution which has invested in SAS, it might be difficult for you to lay your hands on SAS.

SAS is comparatively Easy to Learn, precisely for analysts with SQL knowledge. Like mentioned above it has a good support system, with tutorials and comprehensive documentation, but they are costly when compared to other programming languages, which are also known for some amount of simplicity. However, the GUI interface of SAS is very stable.

Data Handling Capabilities of SAS used to be a USP of SAS till a while ago. But on recent comparisons specially with R and Python, it can be easily said that this is no longer the case.

The Graphical Capabilities of SAS are good and can be considered to be only functional, any customisations require great understanding of the SAS Graph Package, and even then customizing on SAS is difficult. A little disadvantage when compared with other languages.

Developments in Tools of SAS are more or less at par with other languages. Other open languages have new version roll outs, on open contributions, hence the chances of error are possible. SAS also releases updates and they are well tested.

SAS is still considered the market leader in the job scenario in most established corporations. R and Python along with other programming languages becomes a preferred option for new companies looking for cost efficiency.

To conclude, yes it looks like the market is opening up more to other programming languages as well. So it completely depends on your conditions. If you are a fresher, it is recommended that you learn SAS as a first language, purely because it holds a high market share of jobs and is fairly easy to learn. If you are a veteran in the analytics world, then diversifying and adapting a new programming language is recommended. After all, knowing more than one language only adds to the flexibility and opens that many opportunities for you.


  • October, 7th, 2017
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How Beneficial is Data Science Prodegree for Your Career?


Data Science is one of the most sought after career tracks at the moment. There is a reason that the hype on data science exists. The fundamental focus of data science is that it assists human being on taking better decisions, quicker decisions. And it’s not that this is a requirement of only a handful of industries from a particular segment. This is true across industries, even where decisions are automated for e.g. in online shopping, retail etc.,

There is a rapid growth in the data science field. Its prominence is directly proportionate to the record level of increase in the raw material i.e. structured and unstructured data. There are a number of other factors that are adding significance to this field. The number of sensors that accumulate information like internet, phones etc.., along with advanced and sophisticated machine learning techniques that help give better insights with the help of better extraction algorithms. All these forces are working in one direction, the direction to ensure that the skills of using available data to extract actionable insights for business to impact better decision making which in turn will impact the revenue of the company is here to stay. Recognising this most MBA’s have also introduced Data Science into their MBA curriculum.

What skills does one learn in order to become an effective Data Scientist?

Large bits of unstructured data are not easy to interpret, one needs a unique skill set, one needs to develop useful auxiliary skills, some technical attributes required to apply is the top line. One needs to create a perfect balance of various skills. Predictive modelling, analytics, organisation skills and above all communication skills.

Besides the above to be able to secure a lucrative job in the organisation of your choice one needs to develop excellent and valuable coding skills. Efficiency in SAS Statistical Analysis System, R programming language, Python programming language etc.., further aids your skills as a data scientist or analyst. It helps you to think logically in terms of algorithms, which in turn allows you to better manage irrelevant data.

Another additional set of skills that are essential to have academically and through experience are contextual understanding of possibly any given situation, skills in probability and statistics.

And finally the most important of all the skills is the ability to communicate, explain, in the method and language of the audience, your findings. So storytelling and presentation skills become imperative.

Why Data Science Prodegree at Imarticus Learning?

To begin with the Data Science Prodegree at Imarticus is designed in association with Genpact as the knowledge partner. It essentially covers all foundational concepts and offers hands-on learning of leading analytical tools such as SAS, R, Python, Tableau etc., and the learning is integrated with relevant industry case studies and projects, which is essential in gaining in-depth problem-solving capabilities.

The course is divided into four semesters and is focused on ensuring that the candidate not only gain the theoretical knowledge of the tools but also learns best industry practises and business perspectives through live interaction with the gurus of the corporate world through guest lectures and regular project submission. To ensure maximum learning efficacy the course ranges over 200 hours and is delivered in two modes, online and classroom.

The course offers career readiness assistance too, at Imarticus the Career Assistance Services provides you customised industry specific mentorship, with assistance in resume building workshops and one on one mock interviews.

The Data Science Prodegree is a power packed course endorsed by Genpact, which has a comprehensive coverage aided by project based learning, with effective and efficient program delivery along with career assistance. Thus preparing you to confidently apply your newly learned skills and excel in your given role right from day one, making you a sought after data driven decision maker.

  • May, 10th, 2017
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The Promises of Artificial Intelligence: Introduction

Artificial Intelligence

The field of Artificial Intelligence seems to working on a winning streak. In the year 2005, the U. S Defence Advance Research Project Agency, held the DARPA Grand Challenge, which was supposedly held to spur development of autonomous vehicles, basically in order to make self-driven, smart cars. This challenge was taken up and successfully completed by 5 teams. In the year 2011, in a great competition of Jeopardy, the IBM Watson system, was successfully able to beat two long time, human champions of the same legendary game. Another great win of technology over the human race would be in the year 2016, when Google DeepMind’s AlphaGo system was able to successfully defeat the world champion of Go Player, who was reportedly the world champion for 18 consecutive times.

While these feats of technology over the human brain are extremely commendable, today the long surviving dream of humans, which basically revolved around developing technology to control their surroundings, has finally come to fruition. This has resulted in the form of Google’s Google Assistant, Microsoft’s Cortana, Apple’s Siri and Amazon’s Alexa. As a result of all of these AI (Artificial Intelligence) powered virtual assistants, people are able to make greater use of technology in order to live better lives.

Artificial Intelligence is considered to be a field of computer science, which is entirely devoted to the creation of computing machines and systems, all of which are able to perform operations that are similar to human learning and decision making. According to the Association for the Advancement of Artificial Intelligence, AI is, “the scientific understanding of the mechanisms underlying thought and intelligent behaviour and their embodiment in machines.” While these intelligence levels can never be compared to those of the humans, but they can certainly vary in terms of various technologies.

Artificial Intelligence includes a number of functions, which include learning, which primarily includes a number of approaches such as deep learning, transfer learning, human learning and especially decision making. All of these functionalities can later help in the execution of various fields such as cardiology, accounting, law, deductive reasoning, quantitative reasoning, and mainly interactions with people, in order to not only perform tasks, but also to learn from the environment.

While the recent changes may be extremely mind blowing, the promise of AI has always been existing since era of electromechanical computing, this began in the time period, after the World War 2. The first conference of Artificial Intelligence was held at the college of Dartmouth in the year 1956 and at that time, it was said that AI could be achieved within the time period of summer. Later on, in the 1960’s there were scientists, who claimed that in the next decade, it would be possible to see various machines controlling human lives. But it was in the year 1965, when the Nobel Laureate, Herbert Simon, who is supposed to have predicted the words, which would have some substance and which were, “In the next 20 years, it would be possible that machines would be able to do any work of labour that man can”.

With Artificial Intelligence, going in full fervour, the field which it has affected most in the field of Data Science. And as there are many who believe that there is a great to achieve in this field, have begun to get trained in the same by approaching professional training institute – Imarticus Learning.

  • February, 20th, 2017
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R Programming in Business Analytics

R programming language

Data Science as a concept has existed for quite some time, but it’s come into the limelight in very recent times. The whole world is witness to the kind of magic and power, that data analytics generally exudes, as a result of which, it is imperative for every business out there to be able to acknowledge this phenomenon. Regardless of the size, manner, focus area or revenue of a firm, it is essential for it, to understand the dynamics, behind the enormous amount of data, that it generates due to its clients and the maintenance of the same. While there are field where spreadsheets still hold the place of power, but they have long become redundant and obsolete, all because of the emergence of data analytics tools. These data analytics tools are essentially the very important cogs of the proverbial machine, which help data scientist accomplish absolute feats with predictive analytics. So when it comes to the go to tools of data analytics, there ensues an intense debate, so as to which one could happen to be the best or the most efficient aid.

Certification in R ProgrammingWhile many believe that SAS programming (mainly due to its time honored presence in the industry and its huge client base), is the tool to go for, lately the younger generation has been differing opinions. Many believe that the best programming language right now is the R Programming language, one of the main reasons cited here, is the fact that R, is an open sourced programming language, which means that it is easily accessible as well as free to be downloaded. Being free of cost, over time, R has generated its own community of users, which includes numerous data scientists, who have all the liberty to develop updated beta versions and to fix the bugs. It has become the hot favorite of all those data analysts and data scientists, working to analyze huge amounts of information and being able to formulate new breakthroughs, in various business fields.

Apart from being a great tool for use in data analytics, R programming comes to be of major use when it comes to business analytics. This programming language basically, makes it very easy for any business to go through its entire data, in the most hassle free manner. It primarily scales all the information, so that numerous parallel processors, are able to work at the same time. As many computers don’t have sufficient memory, to handle and deal with enormous amounts of data, R programming offers ScaleR, which is a part of the application that does the job of trying to re-purpose great amounts, into smaller chunks of information, so that it can be processed on a number of servers, at the very same time. As R allows the users to analyse statistical information in the most sophisticated of manner and in literally a matter of minutes, which most of the other languages cannot really accomplish; this makes R a force to reckon with in the world of business analysis. Rising popularity of R has led to quite a number of people opting to get professional trained in this language, for which majority of them look for institutes offering certification courses like Imarticus Learning.

  • February, 8th, 2017
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How Does Facebook Identify Where You Are From Your Profile Photo?

We all know that Mark Zuckerberg of Facebook is strongly passionate about Machine Learning and Artificial Intelligence, but how has that impacted our everyday online social life?

You may think you’re just uploading a photo, but facebook knows how many people are there, whether you’re outside or inside, and if you’re smiling.

The technology that Facebook uses, Artificial Intelligence, is a rigorous science that focuses on designing systems that make use of algorithms that are much similar to that of our human brain. AI learns to recognize patterns from large amounts of data and come up with a comprehensive conclusion.


What does that have to do with how Facebook knows if I’m smiling or not?

Facebook photo recognition

Facebook is constantly teaching their machines to work better. By using deep learning, they train AI to structure through various processing layers and understanding an abstract representation of what the data could be. By using their system called “convolutional neural network”, the computer is able to go through layers of units and understand whether there is a dog in a photo.

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Facebook works through layers. In the first layer, it is able to identify the edges of objects. In the second layer, it is able to detect combinations and identify it to be an eye in a face or a window in a plane. The next layer combines these further and identifies them to be either an entire face or a wing on a plane. The final layer is able to further detect these combinations and identifies if it is a person or a plane.

The network needs to be able to read the labels on the database and identify which of these are labeled as humans or plants. The system learns to associate the input with the label. The way facebook works is that it is able to now identify not only that there are humans in a photo, but how many humans, whether they are indoors or outdoors, and their actions, i.e. if they are sitting or standing.

However, a photograph that has been uploaded may need to be completely zoomed in for Facebook’s AI to understand intricacies if a person is smiling or not.



It may not always be perfect in its recognition, but it’s getting there.

A lot of information can be extracted from a photograph. Facebook is only going to get better with its AI and making use of big data.


data scienceArtificial Intelligence and Machine Learning is a concept that will be looked at in Imarticus’s Data Science Prodegree. This course is a cutting-edge program designed and delivered in collaboration with Genpact, a leader in Analytics solutions. Students get their hands-on learning with 6 industry projects and work with industry mentors.




Written by Tenaz Shanice Cardoz, Marketing & Communications.


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  • February, 1st, 2017
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Having Technical Knowledge Is Not Enough For Data Scientists

Data Science today has become the most advanced field industry in comparison to all those industries that have existed in the market sphere. One thing that is very evident about this field is that it is ever evolving in nature. This is one of the reasons why a lot of data science experts advice professionals to forever remain on their toes when it comes to the various developments in this landscape.

Mark Twain’s famous line, “Don’t let school interfere with your education” work the very best for all the professionals in this sphere.

As the field of Data Science is fairly new, there are a number of tweaking’s, replacements, additions and newer solutions being introduced here almost on a daily basis also. This is the reason why it makes it so imperative for Data Scientists to be aware of all the newer trends. After getting certified in any one data analytics tool, keeping in touch with the various new developments in terms of other tools and functions, becomes very important for any Data Scientist, who is looking to expand and improve their career. Data Scientists are time and again advised to learn and relearn certain ‘soft-skills’, which will help them stay on top of their game when it comes to the various requirements of the industry.

While technical knowledge is of utmost importance, being able to develop certain professional traits and habits has great benefits Data Science professionals for these. It is said that learning never ends, it is a continuous process. Similarly for a data analyst, keeping up with all the market trends and trying their best to expand their skill set is a per-requisite. This is the very reason, why a number of professionals today reach out to us to help them gain knowledge of other data analytics tools like SAS Programming, R Programming, Hadoop, Python and more. It is always a better bet to add to your laurels than just resting on them. The most crucial parts of being a Data Scientist is not just to have great skills, but also be able to communicate their results very effectively. As this field has expanded from just being IT related to more fields throughout the market sphere, the same is expected out of a Data Scientist. A professional who has all the technical knowledge, but does not have any knowledge of the business perspective, would not be able to effectively deliver the results of the analytics work.

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Business strategizing and development are two very important parts of data analytics and until a professional is not able to deliver on the technical as well as the business front, he becomes more of a liability than an asset to a firm. Thus reaching a balance between these two aspects will open up a candidate to huge benefits thus. Apart from working on your soft skills, working on your networking skills can also make a world of difference for all the data scientists out there. Attending a number of conferences and related events, will not only help you learn a trick or two but also will help you gauge current trends and give you a sterling CV.

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  • January, 25th, 2017
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The Most Important Concepts to Keep In Mind When It Comes To Big Data in HR

Big Data For HR

The phenomenon that is well known as Big Data Science has literally gone on to spread all over the globe in a similar fashion as that to a raging wildfire. The world of business and commerce has remained no stranger to this concept and field and in fact has embraced it more than any other. Big Data has been the catalyst in some of the most remarkable discoveries, especially in the field of HR. While the technical aspect dictates that the various valuable insights provided by big data have made for amazing growth and development of a number of firms, it has also helped a number of HR managers in targeted recruitment as well as employee enhancement. As a professional in the HR industry, regardless of the position, there are a certain number of things and concepts that one has to abide by. As surprising as it may sound, it has been proven recently that these few concepts still hold great value and importance, especially when it comes to big data in HR.

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The first basic thing, that all HR professionals need to remember, is the massive difference that there is between “story telling” and “story selling”. This is basically only in the context of how a professional perceives a certain data set. It is important for these professionals to be able to distinguish between a very neutral interpretation of data and on the other hand, a data set that is used to derive a certain expected solution. This skill becomes very important in a market, where every vendor and seller is out there to promote their business solutions, entirely on the basis of data and numbers. When faced with numerous such vendors, it holds in positive stead for you to be a little skeptic.

Impact of Big Data on Different Risk TypesAnother basic concept here is not confusing correlation to causation, which is the one of the primary attributes of statistical analysis. This simply put in layman terms, goes on to state that just because two things are related to each other, it does not mean that they are also the cause of each other. This is very important especially in the world of Human Resources, because HR services are most often related to positive business results. This would only be possible, when the professionals are able to realize the difference between certain variables, that can actually cause similar kind of impact, thus statistically stating the connection between the various HR activities and profitability. The most basic trick to know here, is when you would not require causation at all, when only correlation would be enough to provide the required results. While these days, the data is very much required by the HR professionals, in order to determine the correlation and causation, as well as, evaluation of results and making the decisions. It is also important to know when and how the sample size, taken into account is sufficient.

Thus we can infer that HR is soon becoming the latest avenue for all the data scientists out ther to test their abilities. There is no surprise hence, in the increasing popularity of various institutes. Imarticus Learning, provides excellent professional training in a number of data analytics tools like R, SAS, Hadoop and so on.



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  • January, 18th, 2017
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Application Of Analytics In Business Functions

Almost everyone today is familiar with the one key process, which makes use of all the data, in the world today, in turning helping every sector achieve respective goals. Data Analytics, since its inception has gone on to become the most prerequisite process throughout various industries, like Finance, Sports, Health Care, E-commerce, Retail, Manufacturing and so on. While these industries consider the process of data analytics very essential, it is also essentially used in a number of Business Functions. Regardless of any kind of organization, data analytics as a process, has come to becomes really important, in terms of a number of business functions, especially Marketing and HR. Apart from these, the various other business functions, which employ the use of data analytics include sales, supply chain management, Manufacturing, Strategy and many more.

Marketing Marketing

The first rule of marketing, for any firm is striving hard to not only understand their target audience, but also to find and attract more people like them. Now as there are a huge number of customers and clients out there, it may make the task of knowing your audience, seem extremely daunting. This is where the importance of data analytics comes in. It is this process which helps the firm in figuring out the various nuances of every customer and thereby add more value to the company, by gathering data across all the present marketing channels and consolidating it into a common marketing view. Data Analytics helps in measuring, managing and analyzing the marketing performance, so as to increase the effectiveness and to double the rate of return of investments. The various questions that data analytics helps to answer in this field range from, performance of marketing initiatives to the allocation of marketing resources and the activities, that are conducted in comparison to that of the competition. The field of marketing involves the use of various tools of data analytics, in order to investigate the past performance and predict the future on the basis of it.

Human Resourse
Human Resources

For any firm, regardless of the field of specialization, Human Resources department makes for the most important part. This is mainly because of the fact, that this department is responsible for providing the perfect talent in order to perform the suitable functions, so as to generate profits for the company. Data Analytics in this field, collects all the related data and helps in the creation of a single representation of the entire workforce, looking to be placed in the said field. The various valuable insights that the data provides, can be then used for taking various business decisions, in order to help drive the business processes, thus improving not only the productivity but also the profitability of the company. The various key areas in HR, where data analytics is important are, talent acquisition and retention, building leadership, optimizing of compensation and benefits, attrition and so on.

This why, the market has seen a growing demand for those, who are proficient in using data analytics tools. Many candidates have also begun to show great interest, in this field and are looking to get certified in various data analytics tools like SAS Programming, R Programming, Hadoop and so on. Imarticus Learning is making it possible for the candidates to get into the career of their choice, by providing industry endorsed courses in various data analytics tools.

  • December, 13th, 2016
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Advantages Of R Programming Language

R is a programming language, mainly dealing with the statistical computation of data and graphical representations. Many data science experts claim that R can be considered as a very different application, of its licensed contemporary tool, SAS. This data analytics tool was developed at Bell Laboratories, by John Chambers and his colleagues. The various offerings of this tool include linear and non-linear modelling, classical statistical tests, time-series analysis, clustering and graphical representation. It can be referred to as a more integrated suite of software facilities, for the purpose of data manipulation, calculation and data visualization. The R environment is more of a well-developed space for an R programming language, inclusive of user-defined recursive functions as well as input and output facilities. Since it is a relatively new data analytics tool in the IT sphere, it is still considered to be very popular amongst a lot of data enthusiasts.

There are a number of advantages of this data analytics tool, which make it so very popular amongst Data Scientists. Firstly, the fact that it is by far the most comprehensive statistical analysis package available totally works in its favour. This tool strives to incorporate all of the standard statistical tests, models and analyses as well as provides for an effective language so as to manage and manipulate data.

One of the biggest advantages of this tool is the fact that it is entirely open sourced. This means that it can be downloaded very easily and is free of cost. This is mainly the reason why there are also communities, which strive to develop the various aspects of this tool. Currently, there are about some 19 developers, including practising professionals from the IT industry, who help in tweaking out this software. This is also the reason why most of the latest technological developments, are first to arrive on this software before they are seen anywhere else.

Why Learn R Programming

When it comes to graphical representation, the related attributed to R are extremely exemplary. This is the reason why it is able to surpass most of the other statistical and graphical packages with great ease. The fact that it has no licence restrictions, makes it literally the go-to software, for all of those who want to practice this in the earlier stages. It has over 4800 packages available, in its environment which belong to various repositories with specialization in various topics like econometrics, data mining, spatial analysis and bioinformatics.

The best part about R programming is that it is more of a user run software, which means that anyone is allowed to provide code enhancements and new packages. The quality of great packages on the R community environment is a testament to this very approach to developing a certain software by sharing and encouraging inputs. This tool is also compatible across platforms and thereby it runs on many operating systems as well as hardware. It can function with similar clarity for both the Linux as well as Microsoft Windows Operating Systems. In addition to this, the fact that R can also work well with other data analytics tools like SAS, SPSS and MySQL, have resulted in a number of takers for this data analytics tool. Imarticus Learning The Data Science Prodegree powered by Genpact is one such course which offers both SAS and R along with the opportunity to be a Data Scientist at Genpact.

  • December, 10th, 2016
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