How AI is Reshaping Job Market in India - Edure

How AI is Reshaping Job Market in India

September 17 2019

The evolution of AI was not a spontaneous development, the revolution took place periodically, like the invention of the spinning wheel in the beginning, then the electricity paved the way for second evolution, the designing of computers became the third great industrial transformation and finally the fourth greatest revolution ‘the age of Artificial Intelligence’, that has immensely transformed the way we live, work and connect. The evolution of technology was always around us and our life has been transforming with all these developments in technology since then. But the word ‘AI’ has made a different impact on this evolution wheel; the shift of technology from machines to machine learning, from humanoids to Artificial Intelligence had obviously paved the way for another industrial revolution. Developing countries like India, is among the one who turns to be the most affected by the arrival of any new technology; especially after the surface of Artificial Intelligence in the Indian Industries. On the one side, AI adoption rate in India is quite high, well on the other side, like the saying goes ‘everything comes with a price’; the opportunities and risks that Artificial Intelligence poses for the Indian industry and society is also quite high, especially in the employment sector. Currently the most critical question that swings on the ‘future of AI in India’ is that, ‘Will Artificial Intelligence create more jobs than that it destroys?  Is AI literally reshaping the Indian job markets?’ Well, precisely soon after the arrival of the AI, the technology has been addressed as a ‘dilemma’; ‘Will it replace humans and create an inevitable worldwide unemployment crisis, or will AI transform India’s job sectors into new potentials?’


Well it is true that automation is impacting employment all across the globe, especially in India. As per a report, the proportion of jobs threatened by AI Automation in India is 69 percent year-on-year. The employment sectors in India like automobiles, pharmacy, IT industries are at full swing in the AI adoption rate, which is impacting and reshaping the workforce. Where on the one side, the technology revolution is driving India to new heights, in terms of skills, better governance and growth, whereas on the other side, the new automation trend is fading out of employment opportunities; at least that’s what we believe! However, we are failing to understand a strong point that an evolution is a part of growth and advancement. The materialization of automation in Indian industries will only up-skill and re skill the talents that any market currently requires, that will not only create a skilled employees but also accelerate country’s economic development. 


If on one side, technology is taking away our jobs, well on the other hand, it is also giving an opportunity to upgrade our skills and talent. Although the arrival of advanced technology is reshaping our Indian job markets through human replacement with machines, but it is paving the path for India to make a mark in the corporate world. In other words, if AI is a destroyer of employment, well it is also an architect of building a skilled employment and corporate growth. 

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The way the world is becoming more and more data driven, it is triggering the significance of technology in our daily life and work life. Technology like Humaniod robots are no more just a fictional word, or confined to Hollywood or Bollywood movie; they are the reality of our reshaping tomorrow. According to an expert prediction, companies will continue to develop technology like AI (Artificial Intelligence), ML (Machine Learning), Automation, VR (Virtual Reality) and Cryptocurrency in the near future, while the IT job roles like Software developers, Data Scientist, Cybersecurity are going to dominate this transforming world in the coming years. Even the demand for top-notch workers are only meant to increase with time. So let us have a look at the most in-demand tech jobs of 2020:


1. AI as a service


You know how Artificial Intelligence and Machine Learning are finding its way for the acceptance and adoption in the real world, especially in the market sphere of retail and e-commerce. So far the advancement of technology has resulted in reducing human errors, improving the customer experience, increased productivity and so much more. Where some companies and websites are only in the developing stage of integrating AI chat bots into their business, while some companies have taken a step ahead with the new-gen AI platform integration with AI chat bots, Virtuual assistants and Voice search optimization like Amazon's Alexa, Apple's Siri, Amazon Go store and Microsoft's Cortana. AS for Chatbots, like VR and AR, it is also making a place among the customer service professionals. According to a report by TechEmergence, AI Chatbots will soon emerge as the 'must-have' application in the coming years. Only with the Machine Learning algorithms and Artificial Neural Networks (ANN) research and studies, made it possible for AI to take a deeper leap into the development of a system that echos human behavior.


2. 5G data networks


Another amazing technology that is going to make a trend in the near future is the fifth generation wireless cellular technology, that is 5G data networks. The arrival of 5G with advanced antenna technology will result in sharp increase in speed and responsiveness of wireless networks.

3. Automation


An accurate definition of Automation would be like this 'a simple transfer or shift of tasks from Man to Intelligent Machine! Even though the Automation and AI are not new to us, and yet only recently, we have started to push the limitations of machine's capability when it is coupled with AI; paved the path for the era of Intelligent Automation. Today, the Intelligent Machines are capable of doing of their own which we believed to be a distant future; from automated self driving cars to automated checkouts in Amazon grocery store, we are now surrounded by the new generation machines.


4. Personalised and predictive medicine


Welcome to the future where the technology like ML and AI is now incorporated in healthcare! Analyst are making use of new and existing data sources to deliver personalized care with predictive analytics. The benefits of using predictive analytics can evolve as better care and lower costs. Vinnie Ramesh, Chief Technology Officer, Co - founder of Wellframe stated that " Predictive analytics is not reinventing the wheel. It is applying what doctors have been doing on a large scale. What is changed is our ability to better measure, aggregate, and make sense of previously hard- to- obtain or non - existent behavioral, psycho social and biometric data. Combining these new data sets with the existing sciences of epidemiology and clinical medicine allows us to accelerate progress in understanding the relationships between external factors and human biology—ultimately resulting in enhanced re-engineering of clinical pathways and truly personalized care.


5. Computer vision


The basic definition of Computer vision (CV) is a technique connected with science and technology that help machines/computers to "see" and understand the content of digital images such as photographs and videos. Computer vision along with the advanced concept of deep learning paved the path for model like photograph classification, object detection, face recognition and many more.


6. Extended Reality


Extended Reality (XR) is an emerging term that refers to all real and virtual combined environment created by technology, which also related the human -machine interactions generated through computer technology and wearable, such as, Augmented Reality (AR), Mixed Reality (MR) and Virtual Reality (VR) are among other examples of extended reality.


7. Blockchain technology


Do you know that major industries like IBM, Microsoft and Amazon are developing their own block chain technology platform. It provides a safe, secure and an instant authentication to massive online transactions and let users to store data in different locations globally. It was basically introduced by Bitcoin to bring revolutionary changes in the evolutionary web industry. 


We can say that we are about to see the most defining era in human history! 




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Thinking about a career in Machine Learning but confused about required industrial skill set! Well, as you might have heard how AI is advancing every technology, transforming every industry virtually, from self driving cars, automated stores to automated fraud protection and all this would not have been possible without the dynamism of Machine Learning. When i say AI, you already know the rising career opportunities and scopes for an AI engineer and it is no different for a ML engineer. Now to start building a career in Machine Learning could be a trickier question! Because if you want to learn Machine Learning without any technical knowledge could be possible but mastering ML without any basis in Linear algebra, Probability and Python programming is not practical. Machine Learning may seem pretty intimidating, but it is far trickier than it looks.


Now, before discussing on the skills you need to become a Machine Learning engineer, lets first dig into the most elementary question 'what is machine learning?' While we usually do online shopping in Amazon or Flipkart, you might have noticed a different deals on the products such as combo offers, discount offers, coupons or even product recommendation while checking out products or similar to your shopping preference. Have you ever wondered how they can predict such product combo list or recommendation based on your search? Well, this is called machine learning! The modern machines have the ability to observer and then learn the customer's behavior based on their shopping preference, trends, interest and thus predict a list of products which will surely interest the targeted customer. In simple words, Machine Learning is a subset application of artificial intelligence, which enables machines to learn from its experience and makes predictions based on its experience. The application enables the computer or machine to make data-driven decisions rather than being explicitly programmed for carrying out a certain task. Moreover, the machine learning programs or algorithms are designed in a way that they learn and improve over time when exposed to new data.


Google's Chairman, Eric Schmidt, once stated that 'Google's self- driving cars and robots get a lot of press, but the company's real future is in machine learning, the technology that enables computers to get smarter and more personal'. So we can say that we are now living in the most defining and revolutionizing era of human history. Now let us dive on the skills that qualify you as a Machine Learning Engineer:


Programming fundamentals


Here, you can choose between the five most favored language for Machine learning, that is, if your expertise or interest is in sentiment analysis, natural language processing, network security, fraud detection, robot locomotion, bio informatics and bioengineering then you have choose from the languages like Python, R, Java, C/C++ and JavaScript.


Probability and Statistics


It is one of the core concepts that a Machine Learning Engineer 'must' have to perform quick and easy maths and generate results using statistical methods. 


Data modeling and evaluation


Data modeling and system design is the next skill that you need to master. Data modeling is used to model data in a standard, consistent, predictable manner, that will help your machine in estimating the underlying structure of a given data sets, or finding useful patterns.


Machine learning algorithms


To be the finest Ml engineer, you have to understand the most essentials of Machine Learning Algorithms. So the algorithms of Machine learning are divided into categories based on the purpose of its use such as Supervised learning, unsupervised learning and reinforcement learning. Each different type of machine learning algorithms solves different nature of problems. However, to visualize the big picture of ML you have to use all the combination of different algorithms to unleash machines' true power!


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You might be wondering about 'What's the next trend in Artificial Intelligence?' The concept of AI has been around us for many decades, yet it only became a part of our real-world after 1950, until its true potential was discovered. Now with the new phase of technology revolution is at hand we can soon see ourself walking and networking among the AI robots. In short, the world is literally shifting from Robots to Machine learning to Deep Learning. Although the AI technology has been here for long but the field yet to be explored deeply. Along with more deep research and study on the various potentials of ANN, we will soon see a new phase of AI automation reshaping our future. In simple words, the age of AI autonomy is no longer a distant future!  In the present scenario, Artificial Intelligence is widely spreading across every industry, even tech giants like Google, Facebook, Amazon are making large scale investments in AI technology, With the new developments making headlines everyday, we will soon see the advancement and adoption of AI technology on different models across various industries by 2025. Well, for now, let's have a look at the top significant Artificial Intelligence technologies of 2020: 


1. AI enabled chips


Embrase the new AI hardware trend, that will put the power of Neural Networks in the Palm of you Hand! The major smartphone manufacturers like iPhone, Huawei, Samsung, Qualcomm have unleashed the power of AI enabled chips through their smart products. But you might be wondering about 'What does this new AI hardware accelerated smartphones can do that weren't possible in the past? Well, what does this new generation AI chip can do is that it will make your smart device smarter than ever before! In simple words, it will make your device more efficient by reducing power consumption, increase battery life, allow onboard device processing and lower response time vs offloading cloud computing. Hold tight, because this new era has just begun to unleash its potential!


2. Evolution of AI with IoT


The convergence of AI with IoT is a new phase of evolution in this data driven world! but this thought have might put you in dilemma that how the convergence of IoT and AI going to change the standards? Well, the combination has the capability to unlock the potential that we have never seen before. The emerging AI technology has the potential to create new and much more improved business opportunities through the smart tasks like voice recognition, language translation, decision-making, while Internet of Things (IoT) let interconnect a chain of devices that transfer data over a network; so you can think if AI is coupled with IoT, we can create something that is beyond any human imagination. Well, it's just a story line, the potential just begun to be unleashed! 


3. Automation


An accurate definition of Automation would be like this 'a simple transfer or shift of tasks from Man to Intelligent Machine! Even though the Automation and AI are not new to us, and yet only recently, we have started to push the limitations of machine's capability when it is coupled with AI; paved the path for the era of Intelligent Automation. Today, the Intelligent Machines are capable of doing of their own which we believed to be a distant future; from automated self driving cars to automated checkouts in Amazon grocery store, we are now surrounded by the new generation machines. 


4. Deep Learning


Even after mastering the basics of artificial intelligence and artificial neural networks, yet developers are struggling to figure out the true potential of Deep Learning; in other words, 'the potentials of Deep Learning seems boundless'. Even the scientist described the design of neural network architectures as more art than science! Deep Learning may be an application of AI yet it has more powerful potentials to unleash, or we can even say that the power of Deep Learning with Neural Networks and GPUs are driving powerful new opportunities for AI.  .


5. Cloud Computing


There had been major technological development globally which had transformed our era fro web search to digital era, where one such development was 'Cloud Computing'. And the technology has found an easy adoption and acceptance in the real world, even Tech giants like Google, Facebook, Amazon has already unraveled its power into their business. As for now, Cloud Computing plays a major role in the advance evolution of digital technology. 


6. Natural language Generation:


you might be wondering 'what role does Natural Language Processing (NLP) play in AI application?' Well, NLP is one of the techniques in the area of machine learning, which is focused on teaching computers to understand natural human language more accurately. NLP also enables computer programs to understand unstructured data to make inferences and provide context to language, just like a human brain.


7. Speech Recognition:


Well, what speech recognition does is, it transcribes and transforms human speech into a format that machine applications can understand. Currently, speech recognition is used in interactive voice response systems and mobile applications.


8. Virtual Agent:


Virtual agent, also known as Intelligent virtual agent, virtual rep or Chatbot, provides automated customer service, just like Louise, a virtual agent of eBay. It is usually a computer generated, animated, artificial intelligence virtual character that is used to describe a program based on artificial intelligence to serve as an online customer service representative by leading an intelligent conversation with users, responds to their queries and performs adequate nonverbal behavior. 


9. Machine Learning:


Whereas Machine learning is an application of AI that provides computer systems with the ability to learn automatically and improve from experience without being explicitly programmed, through algorithms, application program interface (APIs) and data. 


10. Biometrics:


AI Biometric technologies is used as a form of identity access management and access control solutions, through physical and behavioral identification systems like face recognition, fingerprints, voice recognition etc. The encoded biometric information is later stored in a database and digitally sampled during authentication and verification.




Get ready for the arrival of a new future with AI!

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The evolution of AI was not a spontaneous development, the revolution took place periodically, like the invention of the spinning wheel in the beginning, then the electricity paved the way for second evolution, the designing of computers became the third great industrial transformation and finally the fourth greatest revolution 'the age of Artificial Intelligence', that has immensely transformed the way we live, work and connect. The evolution of technology was always around us and our life has been transforming with all these developments in technology since then. But the word 'AI' has made a different impact on this evolution wheel; the shift of technology from machines to machine learning, from humanoids to Artificial Intelligence had obviously paved the way for another industrial revolution. Developing countries like India, is among the one who turns to be the most affected by the arrival of any new technology; especially after the surface of Artificial Intelligence in the Indian Industries. On the one side, AI adoption rate in India is quite high, well on the other side, like the saying goes 'everything comes with a price'; the opportunities and risks that Artificial Intelligence poses for the Indian industry and society is also quite high, especially in the employment sector. Currently the most critical question that swings on the 'future of AI in India' is that, 'Will Artificial Intelligence create more jobs than that it destroys?  Is AI literally reshaping the Indian job markets?' Well, precisely soon after the arrival of the AI, the technology has been addressed as a 'dilemma'; 'Will it replace humans and create an inevitable worldwide unemployment crisis, or will AI transform India's job sectors into new potentials?'


Well it is true that automation is impacting employment all across the globe, especially in India. As per a report, the proportion of jobs threatened by AI Automation in India is 69 percent year-on-year. The employment sectors in India like automobiles, pharmacy, IT industries are at full swing in the AI adoption rate, which is impacting and reshaping the workforce. Where on the one side, the technology revolution is driving India to new heights, in terms of skills, better governance and growth, whereas on the other side, the new automation trend is fading out of employment opportunities; at least that's what we believe! However, we are failing to understand a strong point that an evolution is a part of growth and advancement. The materialization of automation in Indian industries will only up-skill and re skill the talents that any market currently requires, that will not only create a skilled employees but also accelerate country's economic development. 


If on one side, technology is taking away our jobs, well on the other hand, it is also giving an opportunity to upgrade our skills and talent. Although the arrival of advanced technology is reshaping our Indian job markets through human replacement with machines, but it is paving the path for India to make a mark in the corporate world. In other words, if AI is a destroyer of employment, well it is also an architect of building a skilled employment and corporate growth. 

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Whether you are thinking of jumping into Python Development or looking out for a career in Data Science? In anyway we are excited to share with you our hand-picked collection of the best Python libraries. Well, we all know that Python offers an awesome choice of open-source libraries for Data science. So turn your programming into a scientific computing language to scientific data analysis and modeling tool with the best Python libraries!

The Python offers an awesome choice of open-source libraries for Data science and so we are! Our wise faculties with their expertise will make you a skilled full-stack Python developer. Learn the interactive coding with Edure!

1. Scikit-Learn

Scikit-Learn is considered as one of the best Machine Learning libraries for working with complex data and most popular among ML libraries for classical ML algorithms. It contains numerous number of algorithms for implementing standard machine learning and data mining tasks, such as reducing dimensionality, classification, regression, clustering and model selection, while also offering features like Cross-validation, Unsupervised learning algorithms and Feature extractions. It would be a great tool to start out with ML.

2. Numpy

Numpy as being another machine learning library, it allows data scientists to turn computing language using python into a powerful scientific analysis and modelling tool. Libraries like TensorFlow uses Numpy internally for better performance in multiple operations. This versatile library lets you perform multi-dimensional arrays effortlessly on various generic data.

3. TensorFlow

Like the name suggests, Tensorflow is a framework that associate in defining and running computations involving tensors. It works like a computational library for writing new algorithms and is widely used in applications for machine learning. Plus, TensorFlow is optimized for speed and it uses techniques like XLA for quick linear algebra operations, which makes it accessible to visualize every part of a graph which is not an option in Numpy or SciKit. So, if you want to work on a machine learning project in Python, then you should consider choosing TensorFlow.

4. Keras

Keras is another high-level machine learning library which allows a easy and fast prototyping. It provides an easier mechanism to build and design a Neural Network. The most amazing factor about Keras is that it offers efficiency to compile models, process data sets, build visualization and much more. Just like Numpy, Keras is also used internally by libraries like TensorFlow and Theano. As being modular in nature, Keras is flexible and apt for building more complex models and innovative research. Those who are looking for work on a deep learning project, Keras is the best library to choose.

5. PyTorch

PyTorch is recently gaining attention among the machine learning developers due to its rich Application Programming Interface to solve issues related to neural networks. It is primarily based on Torch, which allows program developers to execute tensor computations and dynamic computational graphs automatically. Above all, it can be used internally with other libraries and packages like Cython and Numba. As being used in NLP, Pytorch is outplaying than TensorFlow in many ways.

6. LightGBM

Just like its name suggests, LightGBM is literally light and fast. It is actually designed to work fast and efficiently to implement methods and models like elementary models and decision trees. Unlike any other machine learning libraries it is fast, user-friendly, handle large-scale data and highly scalable. LightGBM provides high performance gradient boosting frameworks which makes it popular among developers.  

7. Eli5

Eli5 is a machine learning library build to help overcome challenges like debug machine learning classifiers and explain their predictions. It is designed to track the working process of an algorithm and offers build-in support for several ML frameworks. Moreover, it helps to implement several algorithms for inspecting black-box models and supports other libraries like Scikit-learn, LightGBM and many more.

8. SciPy

SciPy is specifically designed for scientific and technical computing to work with NumPy arrays. It offers many user-friendly and fast N-dimensional array manipulation, while it is easy to use. So if you want to work on a project to manipulate numbers, then give SciPy a try!

9. Theano

Theano powers you to evaluate mathematical expressions efficiently through its multi-dimensional arrays and large-scale computing, along with features like speed and stability optimization and dynamic C code generation. Well, it is build on the top features of NumPy and Theano and considered as one of the fast Python Deep Learning Libraries. It was designed to execute all types of computation that requires large neural network algorithms used in Deep Learning.

10. Pandas

If you are looking to work on a data manipulation and analysis project then you Pandas would be an apt choice for you! Pandas offers data structures and operations for manipulating numerical tables and time series. This open source library in Python is considered the finest for its features such as high-performance and easy-to-use, while it uses most of the functionalities of NumPy.

With these enriched collection of industry-standard Python libraries, you can learn to carry out complex mathematical computations, manipulate Dataframes and build complicated-dynamic models seamlessly.

Learn the interactive coding with Edure! Python and Data Science Training in Trivandrum. Start now!

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You might be wondering about 'What's the next trend in Artificail Intellience?' The concept of AI has been around us for many decades, yet it only became a part of our real-world after 1950, until its true potential was discovered. Now with the new phase of technology revolution is at hand we can soon see ourself walking and networking among the AI robots. In short, the world is literally shifting from Robots to Machine learning to Deep Learning. Although the AI technology has been here for long but the field yet to be explored deeply. Along with more deep research and study on the various potrntials of ANN, we will soon see a new phase of AI automation reshaping our future. In simple words, the age of AI autonomy is no longer a distant future!  


In the present scenario, Artificial Intelliegence is widely spreading across every industry, even tech giants like Google, Facebook, Amazon are making large scale investments in AI technology, With the new developemnts making headlines everyday, we will soon see the advancement and adoption of AI technology on different models across various industries by 2025. Well, for now, let's have a look at the top significant Artifical Intelligence Trends of 2019: 


  1. 1. AI enabled chips


Embrase the new AI hardware trend, that will put the power of Neural Networks in the Palm of you Hand! The major smartphone manufacturers like iPhone, Huawei, Samsung, Qualcomm have unleashed the power of AI enabled chips through their smart products. But you might be wondering about 'What does this new AI hardware accelerated smartphones can do that weren't possible in the past? Well, what does this new generation AI chip can do is that it will make your smart device smarter than ever before! In simple words, it will make your device more efficient by reducing power consumption, increase battery life, allow onboard device processing and lower response time vs offloading cloud computing. Hold tight, because this new era has just begun to unleash its potential! 


  1. 2. Evolution of AI with IoT


The convergence of AI with IoT is a new phase of evolution in this data driven world! but this thought have might put you in dilemma that 'how the convergence of IoT and AI going to change the standards?' Well, the combination has the capability to unlock the potential that we have never seen before. The emerging AI technology has the potential to create new and much more improved business opportunities through the smart tasks like voice recognition, language translation, decion-making, while Internet of Things (IoT) let interconnect a chain of devices that transfer data over a network; so you can think if AI is coupled with IoT, we can create something that is beyond any human imagination. Well, it's just a story line, the potential just begun to be unleashed! 


  1. 3. Automation


An accurate definition of Automation would be like this 'a simple transfer or shift of tasks from Man to Intelligent Machine! Even though the Automation and AI are not new to us, and yet only recently, we have started to push the limitations of machine's capability when it is coupled with AI; paved the path for the era of Intelligent Automation. Today, the Intelligent Machines are capable of doing of their own which we believed to be a distant future; from automated self driving cars to automated checkouts in Amazon grocery store, we are now surrounded by the new generation machines. 


  1. 4. Deep Learning


Even after mastering the basics of artificial intelligence and artificial neural networks, yet developers are struggling to figure out the true potential of Deep Learning; in other words, 'the potentials of Deep Learning seems boundless'. Even the scientist described the design of neural network architectures as more art than science! Deep Learning may be an application of AI yet it has more powerful potentials to unleash, or we can even say that the power of Deep Learning with Neural Networks and GPUs are driving powerful new opportunities for AI. 


  1. 5. Cloud Computing


There had been major technological development globally which had transformed our era fro web search to digital era, where one such development was 'Cloud Computing'. And the technology has found an easy adoption and acceptance in the real world, even Tech giants like Google, Facbook, Amazon has already unraveled its power into their business. As for now, Cloud Computing plays a major role in the advance evolution of digital technology. 


Get ready for the arrival of a new future with AI!

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We know that Data Science helps in accurate, better and faster decision-making, similarly Tableau is an extremely powerful visualization software that helps to make more and better data-driven decisions. With Tableau you can easily learn to analyze and display data with a simple drag and drop design; it primarily comprehended in business intelligence and analysis. Let me make it more simple for you, Tablue is a BI tool used to visualize and analyse critical data in an easy and attractive format, which is currently being used by thousands of companies worldwide, even some business organization consider it as a 'must-have' for projects related to Data Science. 


Well, before digging deep into the features of Tableau, let first understand what is Data science, how data visualization is being used in data science to solve problems, communicate predictions and make better business decisions! Data Science is basically about discovering knowledge, finding patterns and hidden insights from a large database. Data scientists transform this raw data into models and visually communicate these meaningful insights about a product or customer information using data visualization such as statistical graphs, plots, information graphs and other tools. In simple words, Data Visualization allows scientist to give the extracted data a visual form through visual representation using charts and non-charts. With data visualization, data findings become more communicable and complex data becomes more accessible, understandable and useful. It has even been advised by industry experts that if you are pursuing a career as a Data Scientist or Data Analyst, then Data Visualization is 'must-have' skillset! 


I hope you got a fair idea on "how data visualization supports communication?" Now lets learn how Data Visualization with Tableau helps in making communication more clear, attractive and how it contributes to make more data-driven decisions! Well, Tableau's ease of use comes from its 'drag and drop interface' feature, that is, it lets users to perform the tasks like sorting, comparing and analyzing with more ease and comfort; to be more precise, its a hassel free software that is compatible with multiple sources, including excel, SQL server and cloud-based data repositories. Moreover, the simple representation of graphs is merely the tip of the iceberg, there is a wide array of visualization methods to present data in more effective, interactive and attractive ways, which are basically categorized into two types, that is 'General types of data visualization' and 'Specific methods to visualize data'.


The common general types of data visualization includes Chats, Tables, Graphs, Maps, Infographics and Dashboards, while the more specific examples of methods to visualize data are Area Chart, Bar Chart, Box and Whisker Plots, Bubble Cloud, Bullet Graph, Cartogram, Circle View, Dot Distribution Map, Gantt Chart, Heat Map, Highlight Table, Histogram, Matrix, Network, Polar Area, Radial Tree, Scatter Plot (2D or 3D), Streamgraph, Text Tables, Timeline, Treemap, Wedge Stack Graph, Word Cloud and Mix and Match method. We can even say that Data Visualization with Tableau makes an A-1 choice for Data Scientists and world-class software solution for business organizations.  


Another feature of Tableau that makes a great tool for Data Scientist/Data Analyst is that it offers a seamless cross-language operations with Python, R and also with DBMS like SQL. This unique functionality of Tableau allows users to import the R and Python scripts in Tableau, that not only helps the user to access to a rich collection of statistical analysis with ease, but also let them gain a deeper insight from the data, and provides more accurate approach to predictive analysis. Well, you can even create visuals quickly with Tableau, and can switch between models to find the best representation chart that best represents your information with just few clicks, it can easily manage huge amount of data and allows customizing options along with hassel free integration with multiple data sourses. In simple words, Tableau is just more than a data visualization tool, it is more like a new approach the graphical representation of data that makes communication faster and data more attractive. It is fast, user-friendly and a simple-to-use tool, that helps to make more data-driven decisions. 


Now, let see how the integration of R and Python with Tableau amplifies data with visual analytics? Well, Tableau makes it easier and quicker to identify patterns and build models by integrating with the programming language R and Python. With R, patterns can be analysed and even can be reproduced effortlessly, users can also create multiple charts to get meaningful insights, which increases the possibility to fetch the unseen patterns within the datasets. Furthermore, the data discovery is only with Tableau's in-built drill-down and data blending features. Moreover, with such extensive functionality in data exploration, every industry around the world wants to harness the power of Data visualization to stay ahead of the competition. 


So if you are feeling intimidated to learn Data Visualization skill with Tableau, then check out the details related to our Tableu training program at our website and get certified in Tableau from either IBM, Microsoft or Harvard University. 

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Do you know that each time you browse the internet, search at youtube, google some trends, shop online or even when you like a fb page or post, you are creating and sharing data about you; each time and in every single minute you are passing valuable info about your interest, preferences, and trends. Do want to know, how these information about you being used in this data-driven world? Well, all these raw data are extracted to find meaningful insights and patterns by Data Scientist/Analyst to help offline/online enterprises to figure out current trends, which help them to plan their future operational strategies and business development. In simple words, Data is transforming the digital world unexpectedly; be it offline or online enterprises, it is redefining the way of how we do business. 


The accessibility of data has opened many possibilities towards development; not just the technological development but also for the business development. In short, data has the potential to turn the table around for any business! In the current scenario, each and every company around the world wants to incorporate data analysts into their company to make better and faster business decisions; be it a start-up, well-established companies or the top MNCs, everyone wants to take full advantage of the critical data around them to stay ahead of the industrial competition. Remember, it's just the beginning of this data driven world, there is much more to come and the potential is not explored to the fullest, the future is just about to unfold itself. 


A research has pointed out that the data has started creating a massive impact on business, on our way of living and even how we connect with technology. In every single day around 2.5 quintillion bytes of data are created, which drives a rush among global companies to hire Data scientists to tame their business critical data, even the demand for a Data Scientist job has grown from 15% to 28% annually. Just like the more data is being produced, it will demand more number of analysts. Even Eric Schmidt of Alphabet Inc recently stated on the impact of data science on Industries that, "Not sure whether Data Science can forsee the future or be able to predict the world's end or not, but as for now it is literally escalating the growth of industry by 7% faster than any time in human history." The biggest opportunities of this digitally revolutionizing world is undoubtedly in Artificial Intelligence and Machine learning and Data is only paving the path for the AI revolution to come. 

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Eric Schmidt of Alphabet Inc recently stated on the impact of data science on Industries that, "Not sure whether Data Science can foresee the future or be able to predict the world's end or not, but as for now it is literally escalating the growth of industry by 7% faster than any time in human history." Thus, as being from an IT industry, we also share the same thoughts on the wide possibilities of data science. Hence it won't be too long when Data Science will become the next big thing in the near future! Well, here's why?


Although the field is new, yet it is proliferating its demand in the industry and expanding its career scope in the analytic field. Well, just like a flower can bloom only if it is a bud, similarly Data Science is an unseen field which is as new as a bud, and has many potential to unfold, to be explored! According to a report by Rutgers Online, which says that around 76% of Data Scientists have less than four years of working experience, which means that there is a shortage of skilled Data scientist globally. The report also points out that there is shortage of 79.7% data science professional around the world; countries like US alone need 1.5 millions of Data Scientist and Analyst to tame their large size unstructured business data. Well, the shortage of scientists and their lack of enough experience also states that the field is yet to be explored, it is yet to unlock its superpower literally!


Secondly, the career roles of the Data Science is yet need to be scrutinized. As per a survey report, only 55.9% scientist are working as a Data Researcher/Scientist and around 40.2% of professionals are working as a Business Developer Analyst. The fields like Data Architect, Data Administrator, Data/Analytics Manager, Business Intelligence Manager still remain mostly untouched. Although, Data Science has become the hottest job of the decade, yet it still remains mostly unexplored, unseen, unknown; in simple words 'Alien'.


Although, on one side it is yet to me be scooped out, yet has some percentage of explored fields, and one of them is 'Deep Learning with AI and ML'. It is being predicted that Deep Learning will be a significant tool kit for Data Scientist that will let them to foresee the developing future and scopes. Tech giants like Google, Netflix, Amazon and even researchers at MIT uses deep learning to predict future, that is, it assists them to figure out what their viewers or audience want to watch next or buy more. Where is cutting edge and uses neural networks to echo the human decision-making, there Deep learning goes much more deep, that is, with its advanced data feeding system, it can mimic humans' thought and intelligence. Well, it is only a glimpse of the power of Data Science, there is much more to come! Soon, the future will see the business leaders using the magnificent power of data science to unfold the business possibilities.


Behold, the future of next big thing is here!

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According to a recent survey, which states that about 58% of companies around the world have adopted the AI technologies into their various businesses to expertly manage their operational strategies and business development, where 12% of industries still sticks with the age-old computer systems for their business performance tracking, stock management and development. As being in the middle of an AI transforming era the survey result might have surprised many of us; it also makes us think 'why these businesses still remain unaffected by the digital revolution, where as the use of Artificial Intelligence can unlock many business potentials! Furthermore, it connects several other concerns by many small industrialists like 'Will AI perfectly fit into their business operations, how can an AI transform their business, how AI operation will affect their cyber security and so on'. So let's end your curiosity by giving you an insight on the various upgrade an AI can make when it is embodied into your business; be it small or big, an AI can grow your business wide with its intelligence! 


AI is actively being adopted in the industries like Healthcare, Transportation, Manufacturing, Retail, Wholesale, Logistics, Education, Navigation, Agriculture and even also in Gaming. Moreover, companies like Amazon, Walmart, Target, TCS, IBS, Alibaba, IBM, Century Tech had already leveraged the magnificent power of AI to stay ahead of the curve. But still the only question that persist is 'how AI can bring your slow growing business into action?' Well, let's breakdown the departments where AI is actively incorporated to boost business process, production, performance and to achieve customer satisfaction:


1. Inventory management


It is difficult to keep a track of factors like inventory/stock levels, space optimization, stock movements, demand and supply of stocks, access daily sales report and moreover, it is hard to manage inventory in bulk. This where the new-gen technology steps in; AI will lend you a hand to manage your inventory effectively. With the pre-set algorithms in Artificial Intelligence you can automate the inventory management, which will eliminate the manual need for management. While your AI will be managing your inventory, you staff will be taking care of your customers. With AI change the way industrialists have operated their inventory so far. With AI in your business stop worrying about your stocks!


2. Automation and Logistics


p>It has not been too long since the arrival of Humanoid Robots, and they have already started walking among humans. The introduction of Automated technology in the workforce has escalated the activity and production process, especially in the automobile industries. These AI robots automate the production operations, inventory management and supply chain, which will enhance the efficiency of a company, while optimizing workforce, at the same time preserves energy and time. The predictive analysis of an Artificial Intelligence will revolutionize your industrial's stocking efficiency and business growth. 


3. Business management


Artificial Intelligence is quickly being adopted in business management by industrialist for seamless business process. As we know around 2.5 quintillion bytes of data is being created in every min which is stored at the database. Have you wondered, why these data were collected, how will these data make an impact on your business? Well, the data is useless unless and until it is being processed and extracted to get meaningful insights or patterns. And when it comes to data mining it is almost impossible for humans to analyze a large size data. This is where Machine Learning and Deep Learning algorithms play its significant role in Business management; using AI algorithm analyst finds valuable insights which help in better decision-making. The retailers and other business professionals study these patterns to figure out customer's behavior, interest, habits, and even discover product trends. Thus, with AI predictions many companies like retailers plan their future marketing strategies to enhance their business process and performance.


4. Marketing/Sales


Well, a product's production value and selling price makes a great impact on marketing and sales sectors. And this where AI is mostly used by an industrialist to manage their marketing strategies. The Artificial Intelligence studies the customer behavior and shopping pattern from the transformed data, based on which it figure out an attractive price optimization for one set of customers, while for another set of customers, it provides different combo offers on products, and as for retailers, AI will ensure the profitability with its logistics.


5. HR management


AI is revolutionizing the way companies manage their workforce, and now, every organization is looking for an HR automation; to increase productivity, reduce human effort and employment engagement in general. Infact, for MNC companies, recruiting as well as employee management itself need a large workforce, and for such companies AI HR solutions takes Human resource management to next level. This new-gen technology will not only assist you n seamless employee management, evaluating eligible candidates, workload management and employee recruitment, but also  help you to scan, read and evaluate applicants quickly, save time by generating shortlists of qualified candidates based on the applicant’s profile and also handles the interview scheduling back-and-forth. Many industries, especially MNC companies, embodies AI HR management to make management smarter and work effortless.


6. Virtual assistance


Virtual assistance like AI Chatbots such as Natasha, Alexa, SIRI are some examples of AI application which build to boost customer satisfaction, happiness and experience in shopping. These customers oriented AI personals will assist customers in their shopping, direction and enquiries. With such assistance shopping becomes more approachable and customer-friendly!  


7. Customer assistance


Walmart has developed a Facial recognition software, which will analyse customer's mood as soon as they enter the store. Such AI software analyse the mood and frustration level of a customer to define the level of satisfaction and dissatisfaction at the store. As soon as the AI figures out that the customer's dissatisfaction, it will assign a customer executive to address the customer's issues, so that they can revive their relationship with the store. 


Stay ahead of the curve with AI optimization in Business; be it small or big AI can super-power your Business!

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5 Top AI Trends