AWS solution to build Real-time Data processing Application using Kinesis, Lambda, DynamoDB, S3

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A Capstone Project by Amit Bajaj and Sathya Guruprasad


Cloud Computing has become very popular due to the multiple benefits it provides and is being adopted by businesses worldwide. Flexibility to scale up or down as per the business needs, faster and efficient disaster recovery, subscription-based models which reduce the high cost of hardware, and flexible working for employees are some of the benefits of cloud that attracts businesses. Similar to cloud, Data Analytics is another crucial area which businesses are exploring for their growth. With the exponential rise in the amount of data available on the internet is a result of the boom in the usage of social media, mobile apps, IoT devices, sensors and so on. It has become imperative for the organisations to analyse this data to get insights into their businesses and take appropriate action.

AWS provides a reliable platform for solving complex problems where cost-effective infrastructure can be built with great ease at low cost. AWS provides a wide range of managed services, including computing, storage, networking, database, analytics, application services and many more. 

Problem Statement:

We have analysed multiple software solutions which perform analysis on data collected from the market and provide information as well as suggestions and provide better customer experience. This includes trade application providing stock price, taxi companies providing locations of nearby taxis, journey plan applications providing live updates on the different transport media and many more.

We have considered a “server-less” platform / “Server-less Computing Execution Model” to build the real-time data-processing app. Architecture is based on managed services provided by AWS.

What is “Server-less”?

A cloud-based execution model in which the cloud provider dynamically allocates and runs the server. This is a consumption-based model where pricing is directly proportional to consumer use. AWS takes complete ownership of operational responsibilities eliminating infrastructure management and availability with higher uptime. 

Services Consumed:

  1. Kinesis – Kinesis Data Stream- Kinesis Data Analytics- Kinesis Firehose
  2. Athena
  3. Lambda
  4. Dynamo DB
  5. Amazon S3
  6. AWS CLI


AWS solution to build Real-time Data processing Application - cloud computing

Without building a sizable infrastructure, how to receive data from different sources for cloud-based infrastructure?

Kinesis, a managed service by AWS, Amazon Kinesis makes it easy to collect, process, and analyse real-time, streaming data so you can get timely insights and react quickly to new information. Kinesis Datastream allows user to receive data from data generation source. We have created amazon kinesis data stream using AWS CLI commands which is expected to consume data from the data source.

Technical + Functional Flow 

Create Kinesis data streams: 

      1. Create a stream in Kinesis using AWS Console or AWS CLI Commands; one to receive data from Data generator and another to write post processing. Data generator will produce the data which will be read and written to input/source data stream. Kinesis Analytics App will process and write data to Output/destination stream.
      2. We have created a program to generate data, and with the help of AWS SDKs and AWS CLI commands transmitted to Kinesis Data Streams. Data can be generated in various fashion:
        1. Using IoT devices
        2. Live trackers
        3. GPS trackers
        4. API
        5. Data generator tools (in case of Analysis)

Create a Kinesis Analytics App to Aggregate data

      1. Build a Kinesis Data Analytics application to read from the input/source data stream and write to output/destination data stream in formatted fashion in a specified time interval.
      2. It is very important to stop the application when not in use to save unwanted cost.

Data Storage and Processing:

      1. Lambda, another managed service by AWS processes data from trigger data stream and write to dynamo DB
      2. Lambda function works on trigger basis and cost model is strictly driven by consumption. No cost is incurred from user when function is not running. Data is stored in Dynamo DB and can be accessed in standard fashion.

Kinesis Firehose, S3 and Athena:

    1. Kinesis Firehose acts as mediator between Kinesis Datastream and S3 where Data received from Kinesis Datastream will be predefined S3 bucket in specified format
    2. Amazon Athena is server-less interactive query service which enables user to glorify data stored in S3 Bucket for analysis. 

Amazon CLI, AWS Cloud formation and AWS IAM also plays a very important role in building Cloud based infrastructure and ensure secure connectivity within and outside AWS cloud world. 


Using AWS services, we were able to create a real-time data processing application based on serverless architecture which is capable of accepting data through Kinesis data streams, processing through Kinesis Data Analytics, triggering Lambda Function and storing in DynamoDB. The architecture can be reused for multiple data types from various data sources and formats with minor modifications. We have used all the managed services provided by AWS which led to zero infrastructure management efforts. 

Capstone project has helped us in building practical expertise on AWS services like Kinesis, Lambda, Dynamo DB, Athena, S3, Identity and Access Management, Serverless Architecture and Managed Services. We have also learnt the Go programming language to build pseudo data producer programs. AWS CLI has helped us to connect on-premise infrastructure with cloud services.  

This project is a part of Great Learning’s post graduate program in Cloud Computing. 

Amit Bajaj – Project Manager at Cognizant
Sathya Guruprasad – Infrastructure Specialist at IBM Pvt Ltd

Setting up a hospitality business model on AWS

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A capstone project by Sajal Biswas and Shreya Sharma

Use Case: Accommodation options in the travel industry are not limited to hotels and resorts. People often look for homestay options as this model benefits both the parties. Tourists can enjoy home-like comfort while owners can earn reasonable revenues on the rent.


We have taken the Airbnb business model as a reference, and we have analyzed how to utilize AWS cloud services so that business only need to focus on their model.

We are following ‘server-less architecture’ for our proposed solution. Serverless architectures help in significantly reducing operational cost, complexity, and engineering lead time, at the price of increased reliance on the vendor. 

Architecture:cloud computing capstone project

CICD Architecture:

cloud computing capstone project

Tech stack used:

– ReactJs for creating the web application using AWS AMPLIFY

– Profile Management using AWS COGNITO

– ChatBot using AWS LEX and AWS AMPLIFY

– Static website hosting on S3 bucket


– Code repository in CODECOMMIT

– Backend API’s using Lambda functions(in Python) which will be triggered via API Gateway

– AWS ElastiCache for efficient Search functionality

– DynamoDB database for storing data in key-value pairs

– Static files like images are kept in an S3 bucket

– CloudWatch Alarms are being used for monitoring purpose

– AWS SES service to send emails to customers

– AWS Pinpoint and Athena for analytics purpose

Case Studies:

  1. Without provisioning Infrastructure, load balancing and less cost, how can we develop API, as fast as business needs to launch in the market?

For this requirement, Serverless architecture is the best choice. So, we have implemented the same so that business need not worry about Infrastructure changes and management.

  1. What if a user wants to track email user communication and process the data based on reply?

Enterprise solutions not only want the business to send promotional emails, contact services but also interested in user replies and track user communication as well. AWS SES is implemented for this feature, though we have integrated only sending email using Lambda function, other features can also be explored.

  1. The design approach for Search and Listing Properties on website

We have considered that a large amount of data will be generated, hence transaction would be huge as well, so we have chosen Dynamo DB. We are maintaining property list by partition key as <propertyCode>_<stateCode>_<pinCode> so that we can easily search, and whenever a huge request comes in, then it should split up in such a way that hot partition key issue does not arise.

  1. Efficient Search functionality using AWS ElasticSearch.

We are using AWS ElasticSearch for saving a record along with DynamoDB. We have also created Lambda function for collecting transaction data from DynamoDb and create a CSV file in S3 bucket which will be used from Athena for analytics purpose.

  1. Is it possible to increase customer interaction, instantly? 

We have integrated LEX ChatBot with basic functionalities.

  1. What would be a good approach for User Profile Management?

The initial thought was to use AWS RDS service for this, but later we used managed service for this which is AWS Cognito.

  1. Analytics from Business Perspective.

Currently, we have used below services for analytics purpose:

– Aws pinpoint

– Athena Query 

Technical Details:

Website hosting with API integration:

We have developed a static website using React Js and AWS Amplify. This website is hosted on S3 bucket and Cloudfront is integrated for caching and CDN.

– User Registration, Login, Password Management, Logout and Session management using AWS Cognito.

– LEX Chatbot for basic functionalities

– Integration with backend API’s deployed on API Gateway. We have consistent response JSON format i.e. ArrayList of objects

– AWS pinpoint for tracking user activity on the website


Repository Management: Website repository is maintained using AWS Code Commit.

CI/CD: We have used AWS Code Pipeline for website deployment

API deployment: All Backend API’s are deployed in API gateway integrated with AWS Lambda and we have created the dev stage environment for the same.

Monitoring and Metrics:

We have used Cloud Watch logs and Metrics for debugging and monitoring purpose using various tags.API’s and Database:

We have created API’s using AWS Lambda as backend. All functions are written in the Python environment. 

Although neither of us has expertise in Python, we learnt about it in the PGPCC course. 


We have used PIP package manager for installing boto3 for python.

API Endpoints:

All Lambda functions are exposed through API gateway as a POST request, wherein we have used “action” field in the body so that based on this field, API can respond accordingly.

Services details: 

We have created the following services:

Product Management Service:

We have created 3 functionalities by querying DynamoDb database/ ElasticSearch

– Create product

– Get All product

– Get all product by state

For the same functionality, based on the “es_service” flag in the body, we decide whether to call DynamoDb or ElasticSearch

Transaction Management Service:

We have created 3 functionalities by querying DynamoDb

– Create Transaction

– Get All transaction and by UserID

– Transaction by date for a particular UserId.

Transaction Analytics service which will gather all transaction data and dump into s3 as CSV file where we can query the data using Athena.


Serverless computing offers several advantages over traditional cloud-based or server-centric infrastructure. For many developers, serverless architectures offer greater scalability, more flexibility, and quicker time to release, all at a reduced cost. With serverless architectures, developers do not need to worry about purchasing, provisioning, and managing backend servers.

We have observed the following advantages while working on this capstone project:

– No server management is necessary

– Developers are only charged for the server space they use, reducing cost

– Serverless architectures are inherently scalable

– Quick deployments and updates are possible

– Code can run closer to the end-user, decreasing latency

Authors’ Bio:

Shreya Sharma – Shreya is an AWS Certified Solutions Architect and is currently working as Senior Software Developer with Hexaware Technologies Pvt Ltd. in Mumbai. She has a particular interest in all things related to AWS Cloud, migration from on-premise to Cloud & Backend API. She has 8 years of extensive work experience in designing and developing Full Stack Applications on cloud and on-premise both.

Sajal Biswas – Sajal is passionate about cloud computing development and architecting cloud migration projects with backend API development. He is an OCA 7(java), CSM, Mule ESB certified professional and is currently working with Capgemini as a software consultant in Mule ESB technology. He has a total experience of 6.7 years including extensive experience in API integration.


10 Easy Ways to Boost Productivity using AI & ML in 2019

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Artificial intelligence is expected to grow at a CAGR of 52 percent between 2017 and 2025, owing to the strides in the innovation and application of AI.

Recent advancements in cloud computing and big data have allowed for this growth of AI in all industries. Improving efficiency and productivity also brings better performance. AI also improves decision-making within an organization by providing critical information.

For some organizations, leveraging AI means exploring select parts of their enterprise to craft AI use cases. While this approach can help you follow trends quickly, it is not the roadmap to AI authority.

To become a true AI-fueled organization, you might need to rethink processes and human-machine interactions within your working environment.

Top-level executives should also be vested in the idea of deploying machine learning and other cognitive technologies across the organization’s core processes to adopt insight-driven decision-making across the enterprise.

Enhance Productivity Across Organizational Teams

Here are ten specific ways organizations can improve overall productivity with the applied science of AI.

  1. Automate Hiring – Employer branding as a major effort for organizations these days. This is the reason why they need to be proactive at hiring and make the process seamless. AI and ML can help do that by automating part of the process to improve recruiters’ productivity and help them sort relevant applications in lesser time. With AI and ML in hiring, recruiters will not have to read one CV again and still be able to shortlist the right talent for their enterprise.
  2. Track on-screen time – Companies can improve the productivity of employees by implementing an AI and ML enabled time tracker that automatically detects their work hours and helps them keep track of billable hours. In the professional services space, timesheets are hard to maintain and track. With AI and ML, no more hindered productivity from noting down effective hours on each project.
  3. Investigate frauds – Within the financial institutions of today, there is a growing concern toward scams and similar attacks. Intelligent automation using robots can help finance and banking companies to detect fraudsters and prevent revenue loss due to malicious intent.
  4. Employee Onboarding – Since all onboarding activities remain almost the same year after year, companies are now shifting these from employees to robots. Several emails and repetitive tasks can be automated with the efficient use of technology. This application of AI and ML can significantly improve employee productivity by freeing them from low-value services.
  5. Customer Engagement – The widespread use of AI and ML-powered chatbots is not unknown to anyone. Chatbots are helping enterprises automate parts of their conversation with customers, allowing for 24/7 presence at reduced costs. Conversational marketing is gaining ground and companies are able to address global clientele with a multi-linguistic chatbot- improving employee productivity and allowing them to interject into interactions when the need be.
  6. Sales and Conversions – Within sales, teams have been traditionally picking up customers for getting on a call depending on logic, but also guesswork. AI and ML can take the guesswork out of this equation by telling sales reps what they should prioritize in order to gain maximum leverage. As a result, sales teams are becoming more productive and converting leads faster.
  7. Maintenance – Equipment manufacturers and suppliers are now offering assets-as-a-service, delivering outcomes instead of machinery only. These companies are using AI and ML in the form of sensors embedded into equipment to detect defects before time. Where uptime is mission-critical, equipment manufacturers need to predict the need for maintenance. By scheduling and predicting maintenance in advance, companies are achieving improved productivity by minimizing downtime and saving cost and time on unnecessary maintenance activities.
  8. Employee Engagement – To keep employees encouraged and productive, companies are planning solutions geared by AI and ML to manage their workforce- both in-house and remote. With AI and ML, companies are monitoring employees in real-time, streamlining conflict resolution, accelerating learning and development activities, and providing continuous support and encouragement to employees.
  9. Demand ForecastingMcKinsey says that inventory reductions of 20% to 50% are possible with machine learning. With AI and ML, we can test models of production and outcome possibilities and precisely analyze data when adapting to new products, disrupting supply chains, and spikes or lows in demand. Sophisticated drones can accomplish so much in less time than a human within a warehouse.
  10. Regulatory Compliances – A lot of industries face stringent compliances that are critical for them to follow. Since compliances remain a moving target, companies are looking at AI and ML to help them navigate changes in regulations and ease compliances for them. By intelligently automating compliance in IT systems, organizations can leave them to the robots without bias, mood, and subjectivity- which is ideal.


Artificial intelligence and machine learning are creating a personalized experience for everyone involved with a business. These technologies are fast-forwarding us to the future where the customer is the centric objective and businesses base decisions on facts rather than on guesswork.

Since AI initiatives juggle with a lot of data, that is one of the top three greatest issues with AI adoption companies face, according to Deloitte’s second annual State of AI survey respondents.

Training machine learning is another challenge that can be solved with sophisticated algorithms, neural networks, and clean, relevant, massive data. Defining the ethics of AI and balancing convenience with security also remains a top challenge for AI and ML implementation.

Nevertheless, enterprises are excited about the avenues that open up for them to improve productivity across the board with applied artificial intelligence and machine learning.

How is AI Disrupting Education?

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Education is rapidly changing around the world. The new generation of learners are born with digital acumen and the ability to adopt technologies quickly.  Software solutions and advanced devices are facilitating smart classrooms. Smart solutions for education have begun a wave of transformation in this space.

Traditionally, schools and higher-education institutions carried out tests and compared the scores of each student against their peers’. We are now beginning to understand that the world of learning is so much wider than classroom tests.

There is so much that kids and adults can learn on their own. To accommodate these shifts, education is transforming, thanks to AI.

The Challenges with Legacy Education Processes

Today, all educational institutions grapple with the following critical challenges:

  • Providing quality education at scale – Often, educational institutions remain within the confines of their walls. They don’t have the right infrastructure to make education available to larger groups of people beyond their geographies. Also, imparting quality education is a challenge when the knowledge of your teachers is limited.
  • Making education more accessible – Helping students in rural areas access education has always been a challenge. With infrastructure constraints, there is a need to find out ways we can make education available to remote areas of the world.
  • Reducing costs of delivery – While making quality education available at scale, institutions might need to invest a lot. This is an issue for institutions with finite resources!
  • Optimizing teachers’ time – Teachers are burdened with administrative tasks such as planning teaching materials, marking and grading assessments, checking facts and the sources of the submitted assignments, and so on. This takes time away from teaching and renders the job less efficient.

Many edutech solutions are hitting the market every day, but the most exciting avenues of disruption come from AI. Artificial Intelligence promises to solve the pressing challenges in the educational space.

As AI techniques such as Natural Language Processing, Machine Learning, and Voice and Speech recognition become more and more sophisticated, they are set to transform education for its instruction and administration capabilities.

But, what exactly can AI do for Education?

Let’s explore!

Grading and Assessment Management

Teachers spend the majority of their time working on grading and marking assessments. That means a lot of their fruitful, efficient hours are wasted on an activity that can easily be automated.

In an effort to reduce this burden, institutions are using artificial intelligence-led solutions for automatic essay scoring, reducing the reliance on multiple choice-based questions. These solutions are adding to the holistic learning patterns and ensuring better student comprehension.

Resolving In-class Queries

As classes get more and more crowded, teachers have little time to address individual questions students might have. Using AI-powered virtual assistants in classrooms can resolve this issue. Using virtual assistants (VA), students can check their own answers freeing the teacher from repetitive questions that can be simply looked up on the internet.

This method also empowers teachers to record and analyze the kind of questions students ask the virtual assistants. This way, teachers can identify weaknesses in comprehension and learning, course-correcting their strategy for teaching.

Personalizing Communication

As the scale of education grows, personalizing communication with students and their guardians becomes increasingly difficult. Giving students, parents, and teachers access to the right information at any time from anywhere is an added challenge.

AI-fueled chatbots can tackle both gaps head-on. With chatbots, information can be accessed from anywhere by anyone at reduced costs. A chatbot could do the work of 10 recruited staff saving you thousands of dollars and improving overall efficiency.

Chatbots can record conversations with each individual, personalizing the experience more and more every time.

One-on-one Customized Guidance

University education mostly happens in lectures with a lot of students. Therefore, dedicating time to individuals or even small groups can be tricky. Personal virtual tutors powered by AI and ML can do the job!

A private virtual tutor can customize learning for each individual, taking into account their speed of learning and comprehension- providing the necessary support where needed.

Student Enrolment

A lot of the student enrolment activities remain the same year after year. Automating these tasks with AI makes a lot of sense for educational institutions. Personalized communication with students can help them enroll in universities with ease.

A round-the-clock, integrated chatbot can answer their many queries before admissions and streamline the entire process of application and enrolment. This would free teachers and other staff from administrative and repetitive work that deserves to be automated.

Plagiarism and Authorship Detection

Graduate and undergrad students often succumb to malpractices such as plagiarism to attempt and win a degree with no effort. Since it is cumbersome for teachers to check each submission for originality, AI can help!

AI-powered software can help detect plagiarism and assert authorship based on the writing style, grammar, punctuation, and many other factors. By automating this part of education, degree allotment and assessment checking can be made more efficient.

There are still challenges AI and ML have to face before they can be commercialized for use in educational institutions.

Here are a few examples of the above:

  • Teacher’s resistance to change in the wake of the fear of losing their jobs.
  • Challenges in adopting AI technologies at scale after getting buy-in from stakeholders.
  • Lack of easy access to funds to set up smart teaching within schools and universities.
  • Ensuring the security of AI-based solutions so that users are comfortable providing all the data these systems need in order to get the right ROI.

Even though there are challenges down the road, a few companies are taking leaps and strides in making AI accessible, plausible, and affordable to institutions.

Educational organizations willing to take the plunge into AI will gain a massive competitive edge in the market and attract both students and teachers- thereby improving educational standards.

How Content Marketing Helped Modi Win the 2019 Elections

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After 5 long years, India witnessed its 17th Lok Sabha elections from 11th April to 19th May 2019. This edition of the elections came with a lot of hype and curiosity among the country’s citizens. Everyone had one single thought in their minds. Can Narendra Modi and the Bharatiya Janata Party (BJP) repeat their glorious victory of 2014? Or will the Congress storm back into power with a resounding win?

The election results were declared on 23 May with the BJP winning a crushing victory over their opposition. Out of 543 seats, the party won an incredible 303 seats sealing a remarkable win for Modi for the second consecutive time. How did Modi and the BJP accomplish this feat? Did content marketing play any major role here? Let’s find out.

India’s Internet Penetration and Social Media Usage

India’s internet penetration has drastically increased over the past two years. This is mainly due to the easy affordability of the smartphone and 4G internet services. As of 2019, half of the country’s population has access to the World Wide Web. Last year, the number of mobile phone users in India was 430 million, as per research by Statista. As a result of all this, an average Indian internet user has accounts in all popular content sharing platforms such as Facebook, Twitter, and WhatsApp.

India currently has 200 million active WhatsApp users, 300 million active Facebook users, and 34 million active Twitter users. These figures are more than any other democracy in the world. Most of the users consume news and other pieces of information from these platforms on a daily basis. A political party that is able to engage and attract these users to their cause through these platforms is bound to emerge as the winner during the election period.

Ever since the 2014 Lok Sabha elections, the BJP has been the front runner in using innovative digital strategies to win over Indian voters.

Content Marketing: Leveraging the Online Advantage

Marketing expert Doug Kessler famously said “Traditional marketing talks at people. Content marketing talks with them.” This is exactly what the BJP had in mind for Indian voters and executed it to full fruition.

The party had started building its online presence much before their win in 2014. Due to the effective use of the online medium, the party emerged victorious in 2014 as well as in 2019. Today, the BJP is the largest Indian party with an enormous online fan following in the world.

BJP and Narendra Modi together have around 58.6 million followers on Twitter which is four times more than the rival Congress party. Narendra Modi alone has 47.5 million Twitter followers and 43 million Facebook followers globally. After former US President Barack Obama and current US President Donald Trump, he is the third-most followed politician on Twitter.

Using this immense social media advantage, Modi and the BJP crafted a number of innovative content strategies on various digital platforms to attract voters.

Let’s take a look at some of their popular content marketing strategies which led to their massive win in the 2019 Lok Sabha elections:

  1. Social Media Pages – The BJP created a number of pages in platforms such as Facebook that appealed to various segments of voters. These pages shared content that attracted voters to engage with them. The various topics that were discussed on these pages were the BJP party’s accomplishments with respect to women empowerment, career opportunities, etc. The party also used the pages to deploy strategic online campaigns which included quizzes and contests with attractive prizes.

Popular supporters and influencers were endorsed on the pages to maximize its reach among voters. Some of the party’s most popular Facebook pages are My Gov India, Nation with Namo, and Bharat Ke Mann Ki Baat.  The best aspect of these pages was that they were created in the local languages of all 29 states of the country. Along with the primary languages, English and Hindi, each post on social media platforms was made in local languages for all regional pages.

All posts were made in various content formats such as images, videos, infographics, live videos, comic strips, and memes. The posts were also perfectly laced with the BJP branding for high impact messaging.

  1. Twitter – Modi and the BJP made maximum use of Twitter to engage and attract voters to their cause. The content marketing team of the party ensured that atleast one hashtag such as #ModiHiAyega was trending every day. This feat was not achieved by any of the BJP’s rivals.

The party launched online campaigns such as the #MaiBhiChowkidar Twitter campaign which became a rage among the youth. The campaign was praised by experts as a marketing masterstroke by the BJP.  The party scored a major win here as the topic appealed immensely with the masses.

  1. WhatsApp – WhatsApp is one of the most popular apps that grace the smartphone of every voter in the country. The BJP used this popular messaging app to create thousands of groups that shared content about Modi and itself. The party intelligently used the app by sending content from known users to increase the interest level and attention.
  2. YouTube – A YouTube channel in Narendra Modi’s name was created to attract the average Indian voter. The channel videos covered every minute activity done by Modi and the BJP. This included rallies, election campaigns, interviews, live videos, events, and even an animated series. Today, the channel has garnered close to 2.6 M subscribers and half a million views.
  3. Sponsored Ads – The BJP has been a huge spender when it came to sponsored ads. Facebook’s Ad Library Report claimed that the BJP spent over 10 crores for 50,000+ ads between February and March alone in 2019. The page that spent maximum money was “Bharat Ke Mann Ki Baat”. It burned a whopping Rs 1 crore per week in Facebook ads. The ads typically contained content that highlighted the party’s achievements.
  4. NaMo TV – Apart from social media marketing, the BJP launched its own TV channel called NaMo TV to ensure maximum coverage. The channel covered Modi’s election campaign in real-time with plenty of content targeted at various types of voter segments. One of NaMo TV’s popular programs was Modi’s interaction with security guards which was watched by over 10 million people.
  5. Narendra Modi Mobile App – Modi launched a mobile app a year after his win in 2014 to directly interact with people. Using hundreds of volunteer teams, the app was made popular among people. The Android version of the app has garnered over 10 million downloads. Modi and his aides could also use the app to communicate with booth-level workers. For the 2019 elections, the mobile app was pivotal in increasing direct user engagement by sending customized messages to users based on their preferences.
  6. Entertainment Industry – Another effort to gain mass popularity by the party was through the entertainment industry. The BJP released an exclusive biopic on the life of Narendra Modi. The trailer of the movie gained a good response from the public and it became viral in no time. Apart from the movie, the party also released a 10-part web series on Modi’s life on Eros Now.


Content is always the King

The above content strategies adopted by Modi and the BJP highlight how crucial content is to connect, engage, and attract voters. The BJP made sure that it understood and segmented its target audience to deliver customized messages. This helped them increase their reach on an exponential basis among the country’s citizens. They ensured that they hit all the right chords of the content marketing realm which in turn culminated in a mammoth victory for generations to remember.

Why Working Professionals are Opting for E-learning

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In this hyper-competitive world, working professionals are valued with respect to the number of job skills that they possess. An individual’s income and career growth are highly dependent on these skills. The greater the number of skills, the higher is the income and career progression. If the number is less, the professional would mostly be side-lined in his/her current role. It would also be difficult for him/her to climb up the career ladder.

The Demand for Skills Development

As new technologies are continuously foraying into the market, working professionals are expected to be up-to-date with the latest skill set. Nowadays, employers themselves are asking their employees to build and upgrade their skills. Some employers even provide funding to achieve the same. Working professionals are therefore bestowed with two options. Either develop the skills on their own via self-learning or join some specialist institute to learn the skills.

In the past, professionals who opted for self-learning had to be heavily reliant on educational books. This method demanded a lot of dedication and research in finding the right content to gain expertise.

People who opted for joining some specialist institute mostly choose the part-time option. Classes would be held at the institute after office hours or on weekends. This method of learning is expensive as the institutions typically demand a hefty fee. They might also take a sabbatical leave from their company (if they allow it) and pursue a regular course from a prominent institution. Once the course is over, they immediately return back to the company.

The Rise of E-learning

With the internet becoming more affordable over the years, e-learning has started to become popular. E-learning is similar to the above-mentioned second method where professionals opt for a course offered by some institute. The difference here is that the learning is done completely over the internet.

The candidate who has opted for the course needs to login to an online portal provided by the institute. All course materials are made available through the portal. Teachers assigned to the course conduct classes via web conferencing or pre-recorded videos. The candidate can easily interact digitally with teachers through the portal. All questions or doubts about various topics can be asked just like a normal classroom environment.

As a result, most working professionals are opting for e-learning than the other two methods. E-learning has enabled them to study at their own pace. They aren’t disconnected from the workplace and can apply whatever new skills they are learning on-the-job.

Benefits of E-learning

Let’s take a look at some of the important benefits of e-learning that has won over most of the working professionals:

  1. Anytime, Anywhere On-demand Access

This is the biggest advantage of e-learning. Students who register for online courses get on-demand access to course materials. This allows them to study on their own time and get a perfect work and home life balance. Some e-learning programs don’t even have course completion deadlines. This gives professionals who are hard-pressed at work to slowly learn on their free time rather than scrambling to meet a course deadline date.

  1. One-on-one Learning

Unlike a traditional classroom environment where getting individual attention from a teacher is difficult, e-learning courses specialize in one-on-one learning. Every student gets individual attention from their teachers. This method helps the student in understanding each concept under the guidance of a mentor. Any doubts/questions can be communicated online and they give prompt answers in detail for the benefit of the students.

  1. Different Learning Methods

All professionals have their own preferred style of learning. E-learning uses various pedagogical design patterns and delivery methods to engage better with each student. It supports the needs of different learners and helps them to understand the topics better. This is a huge plus over the traditional classroom model where only one type of delivery model is used.

  1. Gives Credibility to a Resume

Successful course completion certificates always look good on a resume. A recruiter scouting for worthy candidates is bound to be impressed by the number of certificates mentioned in a resume. It conveys the message that the candidate has put in efforts to develop his skills.

Hiring managers don’t differentiate between traditional and online degrees. If the online degree is taken from some reputed institution, managers consider the candidate to be perfect for recruitment. For those professionals who are looking to be promoted, the online certifications are an added-advantage to send them high on their career paths.

  1. Low Costs

Online programs are always less expensive than their traditional counterparts. For example, a Post Graduate Program in Data Science and Engineering from Great Learning costs only Rs 3,00,000/-. The same course if done from a reputed institution or college costs more than triple this amount. Another great aspect of these online course providers is that they provide financial aid to those professionals who cannot afford the fee.


Working professionals, graduates, and employers want to build skills through cost and time efficient programs. The option of going to an institution or college to pursue a regular course widens the skills gap rather than closing it. This is because these professionals aren’t connected to the work environment for a prolonged period of time.

E-learning gives them flexibility along with increasing their skills gap and marketability. Through one-on-one learning, it has taken student-teacher interaction to a whole new level. It also helps working professionals remain competitive and evolve professionally.

The recent surge in e-learning programs has created a higher demand for specialized, skills-savvy employees. According to research from Arizton, by 2023, the global e-learning market is expected to generate revenue of $65.41 billion. As more companies are incentivizing professional development through e-learning, working professionals are all the more eager to don the double role of a student and a professional.