Showing posts with label Data analytics. Show all posts
Showing posts with label Data analytics. Show all posts

Saturday, September 04, 2021

Role of SMAC in evolution of Digital India

Introduction:

Digital technologies which include Social, Mobility, Analytics and Cloud applications have emerged as a catalyst for rapid economic growth and citizen empowerment across the globe. This vision is to empower every citizen of the country of Bharat (India) with access to digital services, knowledge and information. Department of Electronics and Information Technology (DeitY) has taken the collaborative approach towards achieving the three visions and 9 pillars of Digital India. DeitY has launched a digitally enabled platform called “MyGov” (mygov.in) to provide collaborative and participating governance.

 

The three visions digital India programs are

· Digital infrastructure as a utility to every citizen (Vision-1)

· Governance and services on demand (Vision-2)

· Digital empowerment of citizen (Vision-3)

 

There are Nine pillars of digital India program. They are as follows.

· Broadband highways

· Universal access to mobile connectivity

· Public internet access program

· e-Governance- Reforming government through technology

· eKranti- Electronic delivery of services

· Information for all

· Electronic manufacturing

· IT for jobs

· Early harvest programs

 

The Role of Social:

Social media like Facebook, Twitter, LinkedIn allows people to connect to share views, likeness, opinions anywhere and anytime without any delay. These interaction benefits corporate and the government analyze the data and make decisions regarding products and services. For this we require high speed internet so that as many as people from rural and urban areas can connect with each other and access various services online. While accessing any service their digital identity will be identify through Aadhar card. Since English is the official language of India accessing any service people from rural and urban areas will face problems. Therefore digital resources/services will be available in Indian languages so that human-machine interaction takes place without language barriers. This will create multilingual knowledge resources. Therefore social media will be basically used for marketing, internal collaboration and data analysis.

 

The Role of Mobility:

Mobility is the critical part of national e-Governance (NeGP) projects in India currently being implemented under Central and State levels. NeGP has performed various works such as stack holder needs analysis, project planning and measurement, process reforms etc. Perform survey and stockholder need analysis involve need of citizens at rural and urban areas, need of business, need of government employees at state and central level.

Based on the above survey and analysis central and state government perform large scale e-Governance project planning of service delivery through mobile phones, making the mobile phone the central of service delivery. This results participation of people from urban and rural areas in digital and financial space through mobile and banking, seamlessly integrated services, single window access to services, services in real time online and mobile platforms, digital transformed services for improving ease of doing business, making financial transactions online through internet banking, Rupay debit card etc. no cash transaction, leveraging GIS for decision support system, universal digital literacy at individual level etc.

Apart from this different services provided in rural and urban areas as mobile as the central point of delivery of all services given as follows-

· m-health (mobile based health and medicine consultancy)

· m-education (mobile based virtual education classrooms in local languages at all levels)

· m-biometric identity authentication (mobile based identity through Aadhar)

· m-agriculture (mobile based monitoring management, agri-extension advice and sale)

· m-elections (mobile based online voting based authentication)

· m-rural development (mobile based various rural development projects based on mobile)

· m-panchayat (mobile based panchayat services delivered on mobile)

 

The Role of Analytics:

Analytics refers to Big data. Big data means data available in both structured and unstructured form integrated with multiple, diverse, dynamic sources of information. In fact big data is defined as data that exhibit the 4V properties- value, volume, velocity and veracity. Analyzing this huge amount of data to get the pattern and relevant useful information is called analytics. Big data based analytics can be used in many of the campaigns and election results.

Availability of digital information in India is growing very fast. Data available in enterprise, the volume of data available by the government is also increasing. There are government funded initiatives such as data portal India or Aadhar which are promising directions to enable big data applications relevant to India.

 

There are many challenges to handle large set of data such as

· Efficient architecture and infrastructure of data capturing, data analytics, data delivery, data visualization and data management

· Making data driven decisions

· Data analytics from specification of e-Health, e-Education, e-Governance etc. are yet to be identified

· Integrating big data platform (such as Hadoop) into existing data warehouses

· Security and privacy issues of data being shared for analysis or public consumption are also important to address

· Discovering patterns, predictive analytics and other insights from big data is a non-trivial problem and provides lots of opportunities to innovate in the algorithm innovation

 

The Role of Cloud:

According to NIST definition Cloud Computing is a model for enabling, convenient, ubiquitous on-demand network access to a shared resources (e.g., networks, servers, storage, applications, and services) that can be gradually provisioned and launched with minimal management and service provider interaction. Cloud has five essential properties like on demand self-service, broad network access, resource pooling, rapid elasticity and measured service.Apart from this Cloud Computing has three cloud service models (IaaS, PaaS, and SaaS), and four cloud deployment models (private, public, hybrid, and community).

Through digital India initiatives sharable public Cloud will be available through digital lockers or Digilocker. It enables the people to digitally keep their important documents like PAN card, passport, mark sheets and degree certificates. Digital locker also provide secure accessibility to Government issued documents. It uses authentication services provided by Aadhaar.

 

Cloud Computing has several challenges in India. They are outlined as follows:

· Achieve global leadership in India in Cloud Computing uses, services, offerings and innovation.

· Accelerate national adoption in Cloud Computing technologies, driven by local expertise.

· Develop an innovative framework for Cloud Computing initiatives in India.

· Different other aspects like interoperability, privacy and security.

· Create an environment for multi-stack holder partnership and joint progress.

 

There are also six trends of Cloud Computing.

1. Multinational companies are looking for new business growth opportunities using modern information technology solution. The SMAC has created interesting use cases for businesses. Therefore business growth and IT cost reduction is the ultimate goal.

2. Many leading IT industries in different fields are taking the entire business like Amazon- the World’s largest book store, iTune- the World’s largest music company, Facebook- the World’s largest social site etc.

3. Cloud is becoming a major evolution step in IT market. Its adoption basically depends upon client cost, service, multi-tenant technology and multi-shared delivery model.

4. Enterprise boundaries are getting redefined. Cloud based IT solutions integrated with social media and analytics bring higher value. Therefore IT companies need to integrate with their partners, suppliers and other areas of ecosystem.

5. Make in India initiatives will drive innovation relevant to India Cloud market. Since 2010 70% of India software is developed based on Cloud platform. These products can provide globalize solutions.

6. The combined Cloud service market (public and private) was $0.9 billion in 2011 while in 2015 it has increased up-to U.S $4.5 billion accounting to more than 3% of the global market.

 

Conclusion:

SMAC based IT solutions are identified as a multi-billion dollar prospect for the IT sectors in the world. The corporate and governments are increasingly adopting these technologies, as they become more agile with resource sharing within organization and seek more awareness about their customers to serve them better. Global IT market is being flourishing hugely with SMAC strategies fulfilling the needs in a well-organized manner and promising the prospects of the future of Digital India program. Last but not the list it is just the beginning of a digital revolution, and it will create more job opportunities in IT sector in next 5 years in India.

Monday, August 30, 2021

Python Programming Language in Data Science

Introduction

Python Programming is one of the object-oriented (based around data), high-level (easy to understand) programming language. First released in 1992, it is developed in a way that it is relevantly intuitive to write and understand. As such, it is an ideal coding language for those who want to speed-up the development.

If you are thinking about the uses of Python Programming, you will find that most of the big companies in the world implement it in some form. NASA, Google, Netflix, Spotify, etc. uses the Python programming language to improve their services.

Why Python Programming is becoming popular?

According to the TIOBE index, which measures the popularity of programming languages, Python Programming is the third most popular programming language in the world, behind only Java and C. There are many reasons for the Python Programming to get famous;

• It is ease of use. Those who are new at development using coding and programming, Python Programming can be an excellent first step. It is comparatively easy to learn, making it a great deal to start developing your own programming.

• It is simple syntax. Python Programming is comparatively easy to read and understandable, as its syntax is more like English language. It is straightforward layout that you can figure out what each line of code is doing.

• It is thriving community. As it is an open-source language, anyone can use Python Programming to code. There is a community which supports and develops the environment, adding their own contributions and libraries.

• It is versatility. As we’ll explore in more detail, there are many uses for Python Programming. Whether you are interested in data visualization, artificial intelligence or web development, you can find a use for the language.

Why should we learn Python Programming?

We know why Python Programming is very famous now a days, but why should we learn and how to use it? Aside from the ease of use and versatility mentioned above, there are several good reasons to learn Python Programming:

• Python Programming developers are in demand. Across a wide range of area, there is jobs and vacancies for those with Python Programming skills. If you are looking to start or change your career, it could be a vital skill to help you.

• It could lead to a well-paid career. Data suggests that the median annual salary for those with Python Programming skills is around £65,000 in the UK.

• There will be many job opportunities. Python Programming language used in most of the emerging technologies, such as AI, machine learning, and data analytics, it is likely that it is a future-proof skill. Learning Python Programming now could benefit you across your career.

What is Python Programming used for?

Python Programming is a famous and on-demand programming language to learn. But what is Python Programming used for? We’ve already seen some of the areas it can be applied to, and we’ve expanded on these and more Python Programming examples below. Python Programming can be used for:

1. AI and machine learning

Because Python Programming is such a stable, flexible, and simple programming language, it is perfect for various machine learning (ML) and artificial intelligence (AI) projects. In fact, Python Programming is among the favorite languages among data scientists, and there are many Python Programming machine learning and AI libraries and packages available.

If you are interested in this application of Python Programming, our Deep Learning and Python Programming for AI with Microsoft Azure ExpertTrack can help you develop your skills in these areas. You can discover the uses of Python Programming and deep learning while boosting your career in AI.

2. Data analytics

Much like AI and machine learning, data analytics is another rapidly developing field that utilizes Python Programming. At a time when we’re creating more data than ever before, there is a need for those who can collect, manipulate and organize the information.

Python Programming for data science and analytics makes sense. The language is easy-to-learn, flexible, and well-supported, meaning it is relatively quick and easy to use for analyzing data. When working with large amounts of information, it is useful for manipulating data and carrying out repetitive tasks.

You can learn about data analytics using Python Programming with our ExpertTrack, which will help you develop practical data analytics skills.

3. Data visualization

Data visualization is another popular and developing area of interest. Again, it has many strengths of Python Programming. Also, it is flexible and it is open-source, Python Programming provides a variety of graphing libraries with all kinds of features.

Whether you are looking to create a simple graphical representation or a more interactive plot, you can find a library to match your needs. Examples include Pandas Visualization. The possibilities are various, allowing you to convert data into meaningful forms.

If data visualization with Python Programming sounds appealing. You will learn how to leverage Python Programming libraries to interpret and analyze data sets.

4. Programming applications

You can program all kinds of applications using Python Programming. The other programming language can be used to read and create file directories, create GUIs and APIs, and more. Even if it is blockchain applications, audio and video apps, or machine learning applications, you can develop them all with Python Programming.

5. Web development

Python Programming is a great choice for web development. This is largely due to the fact that there are many Python Programming web development frameworks to choose from, such as Django, Pyramid, and Flask. These development frameworks have been used to create sites and services such as Spotify, Reddit and Mozilla.

Very grateful to the updated libraries and modules which comes with Python Programming language, functions like access to databases, content management, and authorization are all possible and easily retrievable. Given the versatility, it is very surprising that Python Programming is so widely used in web development.

6. Game development

Python Programming does have its uses in the industry for gaming development. It is possible to develop simple games using the programming language, which means it can be a useful tool for a rapid development a prototype. Similarly, certain function like dialogue tree development is possible in Python Programming.

If you are newbie in game development using Python Programming, then you can also find out how to make a text-based game in Python Programming. In doing so, you can work on various of skills and improve your knowledge in various areas.

7. Language development

The simple and elegant framework of Python Programming and its syntax convention that it has inspired the creation of new programming languages. Languages such as CoffeeScript, Cobra, and Go all use a similar syntax conventions to Python Programming.

This fact also means that Python Programming is a useful language. So, if you are totally new to programming, understanding Python Programming can help you determine other areas more easily.

8. Finance

Python Programming is rapidly being utilized in the world of finance and banking, often in fields like where quantitative and qualitative analysis is required. It can be a useful tool in finding out asset price trends and predictions, as well as in automating workflows across various data sources.

As mentioned already, Python Programming is an ideal tool for working with big data sets, and there are many libraries available to help with compiling and processing information. As such, it is one of the preferred languages in the finance industry.

9. SEO

Python Programming uses is in the field of search engine optimization (SEO). It is an area that often benefits from automation for web crawler and search engine robots, which is certainly possible through Python Programming. If it is implementing changes across multiple pages or categorizing keywords, Python Programming can guide.

Emerging technologies such as natural language processing (NLP) are also likely to be relative to those working in SEO. Python Programming is a powerful tool in developing these NLP skills and understanding how people search and how search engines return results.

10. Design

When asking ‘what is Python Programming used for?’ you probably were not expecting design to feature on the list. However, Python Programming is used to develop graphical design applications. The language is used in various 2D imaging software, such as Paint Shop Pro and Gimp.

Python Programming is even used in 3D animation software such as Lightwave, Blender, and Cinema 4D, showing just how versatile the language is.

Use of Python Programming Language in Data Science

The programming requirements of data science wants a very versatile yet flexible language which is easy and simple to write the code but can handle highly complex mathematical operations. Python is most suitable for such requirements as it has already established itself both as a language for general computing as well as scientific computing. More over it is being regularly upgraded in form of new addition to its libraries aimed at different programming need.

Mostly Python has got a very large collection of libraries which serve as special purpose analysis tools. For example – the NumPy package deals with scientific computing and its array needs much less memory than the conventional python list for managing numerical data. And the number of such packages is continuously growing.

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