Category: Analytics

After the success of our first introduction to Virtual Reality and Mobile applications, we decided to take a further look into how Snapchat became what it is now. The field of data science has really expanded, especially from all the data it now has access to.
When it started, Snapchat was just a basic photo sharing application popular amongst the frequent users of social media. This application soon went on to accomplish great feats in the technology sphere with its path breaking Virtual Reality enhancements, as well as the powerful facial recognition enhancing technology it has developed. You must have noticed there this different face, that can be superimposed on your face, while in the selfie-mode of Snapchat, this very feature is popularly know as ‘lenses’ or in the more common parlance, filters. While all of the social media lovers out there are rejoicing this new, inane way of social networking, very few of us realize that there’s a very advanced and impressive technology behind it.

The facial recognition technology used here is all the result of this Ukrainian start-up called, Looksery; which was recently acquired by Snapchat for as much as 150 millions dollars. Although Snapchat doesn’t seem to be making much noise about the same as they want to maintain their position, by remaining a more light hearted application. At the basic level a computer vision is used, which is based on the patterns that are seen of a human face, so you would see those certain neon or white colored points either under your eyebrows, tip of your nose and such. While the face recognition technology used by Snapchat goes a step ahead, to get that perfect specific setting, so that a dog nose sits exactly on your nose and not on your chin. The firm actually got itself involved into a lot of rigorous research and development, where this system was trained with numerous, manually drawn points on faces, which would help it make the filter look real. After several tries, this system is then able to mask your entire face perfectly, with the help of those points. This Snapchat trend is not just powerful, but also has sparked off trends with websites like Facebook and Google, dabbling in the field of face recognition software as well.
This application has proved to be a path-breaker by introducing this new powerful trend on the IT sector. While Snapchat restricts it to just one or two faces and is used for purely recreational purposes, there are considerable chances of this software being used for tracking people. With the number of lawsuits being filed, there are certain unwanted effects that are coming to the fore, like the recent controversy with Facebook, it is also important to note why this technology is very much needed. There is a lot that can be done with the help of this, from tracking people in pressing situations to getting feedback on the functionality of various services, the options are endless. These developments combines with advanced data analytics tools, can pave a way for all the governments to be synced in with the on goings within the society. If appropriately developed, this software can go on to actually match a face of anyone. Without even knowing the identity of that person. Thus, Snapchat in a way has open up a treasure trove of possibilities with this facial recognition software.
The field of Data Science would be one of the first ones to benefit from this ever increasing phenomenon. As Snapchat is already generating scores of data with their ever popular filters, it can also encourage advanced data analytics processes so as to enhance end customer service. This would add to the ever increasing demand for professionals, proficient in the skills of data anlytics. A lot of institutes have begun to pick up on this trend and are now offering specialized programs. For instance Imarticus Learning is one such institute that offers courses, which meet the current industry demands of data analytics tools like R Programming, SAS Programming, Hadoop and others.
And, yes, Snapchat is currently hiring for Data Scientists.

Big Data is defined as data that is too large and too complex for data tools to for data tools to capture, store and analyze. Experts in the data science industry, identify data with the three V’s which are, volume, variety and velocity. For instance, the amount of shares traded on the stock market in the US amount to about 7 billion, the number of tweets on twitter daily amounts to 400 million, the number of likes generated by Facebook on a daily basis is about 3 billion and about 10 terabytes of data is generated in one flight from NY to London; all of these come under the purview of Big Data. Studies and research have stated that in the last two years about 90% of the world’s data has been generated.
While no doubt there is a huge amount of data present in the virtual space all around us, but just this data on its own is not really of any use to us, unless there is someone who can make sense out of it.This is where data analytics comes into play.
Analytics can be defined as the scientific process of transforming data into insight, which aids in making better decisions as well opening up new avenues of opportunities, all for a competitive advantage. Analytics thus branches out into business analytics and data analytics. Business analytics does not really make use of tools and techniques as much as it makes use of valuable insight, that is derived from unstructured data and further on leads to a business strategy. The role business analytics thus is analyzing the performance of the firm in the past and providing insights, as to how a certain firm should go about its future business performance. This is basically achieved through data and statistical models, quantitative analysis and evidence based management. Today, with the rapid generation of large amounts of data mainly for business transactions, availability of advanced data storage sets as well as the availability of advanced tools to analyze the same; has all resulted in the growing need for analytics in the business sphere.
Analytics branch out into three main types namely, prescriptive analytics which basically deal with enabling smart decisions based on data, predictive analytics which deal with predicting the future on the basis of historical patterns and thirdly, descriptive analytics which means basically mining the data to provide business insights. In simple terms the branch of prescriptive analytics would deal with something like the reason behind air fare hikes every year, predictive analytics would deal with how these e-commerce websites hand you discount coupons, which you actually end up using and descriptive analytics would deal with how certain movie websites, recommend just the right movie to users. Data Analytics in the current year has resulted in people using smart and integrated everyday gadgets, advanced gadgets which could enhance the performance of an individual in a work place and the boom that has been caused by the advent of Virtual Reality.

Thus analytics is soon to become one of the most highly rewarding careers and companies have already begun to demand more and more trained professionals. With the announcement of careers in this field, being considered as the sexiest careers of the 21st century, a lot of people are opting for a career in this field. This has in turn led to a growth in institutes, which excel in offering tailor made courses so as to ensure the generation of the sought after skill set among candidates. Imarticus Learning offer courses in the various tools and technologies of data analytics, while aiming to bridge the gap between academics and industry at the same time.

The virtual world so far was considered to be just that, having no direct tangible connections to the real, physical world. This scenario changed radically, with the big data and analytics, and finally now introduction of the concept of Virtual Reality. While the millennials have already been taken by the social media storm, with a majority of them being active across all social media platforms like Facebook, YouTube, Twitter, Pinterest and others, VR changed the entire game for them.
Virtual Reality glasses have become raging fad today and almost everyone either is obsessed with watching movies or playing games with Virtual Reality Glasses. This trend is skyrocketing by the minute, with Facebook and Google already adopting the virtual reality technology and YouTube starting to make their 360-degree videos, there’s a new player in the market. It’s the picture sharing, social media application Snapchat. This app started off as an exclusive application where the users would share photos with each other while protecting their privacy as well.
This application came with some really note-worthy features like, you could decide the amount of time your pictures would be viewed for, you could also keep track of how many people viewed your stories, if anyone replayed or if someone took a screenshot of your photo. At the peak of its popularity, it was considered to be the best photo-sharing app, because it always offered users with the newest, fun ways to engage over social media. But then, it went on to do something, that totally changed the app-game as it was and resulted in Snapchat leaving behind all the other applications in terms of user engagement.

Their first stride into the Virtual Reality world was with the acquisition of computer vision company, Obvious Engineering’s app Seene. Although at the time when this acquisition happened, it was kept all under wraps, but today you would be aware of its full effect from those much-loved snap chat filters. May it be
doggy ears or pumpkin face, Snapchat launched itself with successful ferocity in the world of augmented reality. This took full effect, when people went absolutely gaga over those 3D selfie lenses and the concept went viral, overnight.
While every other social media application and website, was trying their best to find out ways to connect the physical world, to the virtual one; Snapchat actually was the closest to it. While the virtual reality in this application, currently is only limited to these facial lenses that can be seen in selfie mode. These lenses, although working on 3D technology, are a little different from the actual augmented as there is no use of GPS, locations or any other face recognition features. These are just designs superimposed on your face, earlier these used to be just still designs but they have now evolved into full blown video filters and yes, they definitely are as exciting as they sound.

Cut to the future, Snapchat has already launched new virtual reality glasses, which don’t just show you things but let you record small videos and post them on the app. Needless to say there’s some revolutionary technology right there. Apart from this, there was also the recent announcement of them hiring, an acclaimed Hollywood visual effects specialist. These are clearly tell tale signs of something big that definitely going to break the internet, surely millennials cannot wait for it to happen already.
Learn all about what’s Trending and how you can get into the exciting field of Analytics with Imarticus Learning.

Hadoop is an open source programming software, mainly used in the field of Data Analytics. Information Technology has seen a great boom since the latter half of the 20^th century, thus making it one of the most sought after careers, in India. In 2014, an even greater evolution took place in the IT field. There was a huge amount of data in the virtual world, which could be transformed into valuable information for the growth of businesses. Data Science soon became the sexiest field to work in, of the 21^st century. The professionals working here were known as Data Scientists and possessed exemplary data analytics skills. There were various tools that a Data Scientist could use like R Programming, SAS Programming, Big Data Hadoop and more.
Among these tools, Hadoop has the highest demand, so much so that the Indian Big Data Hadoop industry is anticipated to grow five-fold in the coming years. Apart from being an open source software, which means that it is free to download and is very accessible, it can deal with almost petabytes of data with much more efficiency and ease, as compared to the other tools. The big data industry has actually been able to pan out into a varied array of fields, all due to Hadoop becoming the go-to data analytics technology.

The Hindu, which is one of the most eminent newspapers of our country, announced that by the end of the year 2018, India as an individual country will face a shortage of close of 2 lakh data scientists. This makes the year 2016, the right time to make the most out of this opportunity, by acquiring the specific skill set.  The whole business of big data, revolves around extracting, storage, mining and analysing and drawing meaningful insights from all the data generated. This is fast becoming the newest marketing strategy for firms in sectors from health to social networking sites. There have also been predictions as to the fact that, India will soon figure among the most favourite destinations, for outsourcing IT professionals with Hadoop skills. Thus it is evident, that the future of careers in Big Data Hadoop is very bright, with all the states competing to become the major global hub of data analytics.
A career in Hadoop, no doubt is extremely rewarding, as there are ample opportunities to accelerate career growth as well as get those coveted salary packages. Firms have already begun to hire professionals with a speciality in Hadoop skills, thus making it one of the most lucrative career options. The various roles herein include, product managers, Hadoop developers, database administrators, team leaders, software testers, and senior Hadoop developers and so on. Looking at the way things have been progressing so far, it does seem that the upward trend of career opportunities is here to stay. One of the main reasons why Hadoop in particular would see more growth, in terms of opportunities is, the fact that it allows storage of extremely large volumes of structured and unstructured data and their management.
is one such institute offering courses in various data analytics tools, like R Programming, SAS Programming, Big Data Hadoop and more.

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With the boom of the digitalization era and the advent of Big Data, firms and companies started taking notice of the amount of data that was created. It is known that, if one could burn all the data onto CD drives and stack them, the pile would reach the moon twice. Easy access to technology has led to the number of users and thereby, the amount of data generated on a daily basis. As this data cannot be stored in traditional storage systems, there are new systems devised specially for it. What we can infer from this is if one wants to interpret this data, they have to possess a certain set of skills. These people with a specific set of skills are popularly known as Data Scientists.
Data Science is the field, where big data is studied, interpreted and analyzed to draw insights and then take relevant business decisions. There are a lot of professionals in the field of data science, who make use of various tools to help them in data analytics. SAS programming, R Programming, Python, Pig and so on are some of the tools used for data analytics. Interestingly enough, a lot more professionals use SAS programming than R.
The reason is some of the fundamental differences between the two, which will be elaborated in this article.
SAS or Statistical Analysis System is a very old programming software which has been used by almost all the professionals including Data Scientists. It has been on the scene for a much longer time than R programming and is the default software in a lot of firms.
Another fundamental difference is that, R programming is open source software while SAS is licensed software. The major reason for R programming getting a lot of popularity is the fact that it can be downloaded and used free of cost, while SAS programming is considerably expensive.
R programming is primarily coding/programming software, where someone with a background in the field of IT works well. Whereas there have been so many people who have been using the SAS software for everything but statistical use. The SAS programming software is more of a graphical user interface, where the coding part is rarely needed.
Being an open source, R Programming also has its downsides, as it does not have any accountability because; it is out there for everyone to change and use as they go. In addition to that, it is not tested at all as there is no central authority providing this software. With being free, comes no support in fixing of any issues as well, which then leads the user to take help of Google for solving the issues.
Contrary to that, as SAS is licensed it provides high level technical support and comes with great accountability. Although it is expensive, it is very reliable as there are a number of timely upgrades to this software. While R programming is a software that is not tested at the same time, SAS is a thoroughly tested programming language.
Although it may seem that there are stark differences in both the programming language tools, it is evident that R programming is of utmost use in research institutes and for people who want to practice learns it. SAS on the other hand, cannot be used just for learning due to its highly expensive nature.
While it may seem that one of the two programming languages is important and the other is not, it is not the case. For a data scientist, it becomes imperative to have knowledge of how to use every tool there is. One can achieve the same either on their own, or by taking a course on any tool.
Imarticus learning is an institute that offers both short term and long term courses on data analytics, R programming, SAS programming, Python and more.

In a world where customer is king and has a plethora of options to choose from, client engagement and retention is driven by Digital Technologies. This necessitates the business to consolidate data from internal sources as well as external ones like Social Media, emails etc to enable targeted and relevant offerings as per specific customer interests. A large quantum of inputs has to be generated to enable ourselves for this is fairly achievable, by following customer needs, feedback & social media. Additionally it is imperative to have the databases for knowing current customer and prospect profiles, which includes their demographics, geography, and expressed interests.

Insightful Analytics plays an incredible role in bringing the customer and business together in a continuous engagement as it boosts customer experience, through appropriate offering which may not be evidently visible without usage of advanced analytics. It also helps to predict by systematically analyzing customer history in terms of their purchasing trends, shifting preferences and how they may like to interact with and respond to the business. The following steps are extensively used by businesses today:

• Predict – Analyze customer’s history; predict how they will act – as expressed by what they browse and what they buy, how they interact etc.
• Prescribe – Advisory and personalized prescriptions, product recommendations based on customer needs, and offering a personalized, client centric product or service.

To build this ability, replacing the existing Legacy application stack may not be the most Optimum decision and that actually is not possible in all such cases where traditional businesses have been using applications which seamlessly blend business with IT for smooth conduct of services offered.  In such cases, organizations choose to upscale the stack appropriately and continue to thrive. Of course there are certain definite enablers which such organizations will need in order to achieve the needful within existing stack of applications.
Enablers getting significant attention in market place today:

Cloud Enabled Delivery

This includes leveraging the right blend of private, public and hybrid cloud ecosystem for most optimum computation and storage capacity. Addendum provisions to handle sudden loads through auto scaling and accelerated speed to market. In the Digital era, making the erstwhile IT systems ready for the future is one of the key success factors for accelerating the speed of business. This involves modernizing the legacy stack with ease of implementing alternatives, enabling faster results with contained risks.
Quick & accurate identification of the optimum fit involves a solution that imparts agility to surf through the large IT landscape and determine the best fit modernization approach for a particular area to Improve Business/IT collaboration through insights

Digital Readiness

It is important to enable legacy applications with Analytics & Cloud platforms by unlocking the potential of existing assets, as also taught in big data courses in India. This accelerates delivery of business innovations through connectivity to the ecosystem of customers, channels and vendors in a secure manner. Organizations need to be careful to have an ‘Inclusive‘ approach that enables co-existence of old along with new.

How to enhance core systems as effective expeditors:
Organizations need to drive business innovations in the Digital Era and that shall necessitate improving the Core Systems to deliver end to end agility, flexibility & scalability. To strip this approach down to simplistic one we can recourse to either / or both of the 2 below

Cloud First

To Impart required scale through flexible deployment of platforms on either private, public, hybrid cloud and Enables applications to scale automatically depending on the utilization and workload parameters

Mobile First

To Build for the future by prioritizing accessibility from Mobile devices over desktops and by leveraging responsive designs along with content prioritization

Imarticus Learning, an Education Excellence 2015 award winner offers certification courses in finance including financial modeling, risk management courses, financial analyst course and CFA course in India. It offers both classroom and online finance courses to make it extremely easy and flexible for an aspirant to pursue their dream career.