Trends in Information Technology | Management Optional Notes for UPSC PDF Download

Introduction

In the contemporary era, there is a surge in the application and advancement of information technology, playing a vital role in our daily lives. The Information Technology Association of America defines information technology as "the study, design, development, application, implementation, support, or management of computer-based information systems." Information technology has sparked a revolution in business and society, serving as a catalyst for change and addressing various economic and social issues. Throughout history, information and information technology have been crucial for human growth and development, helping in the collection, processing, storage, and utilization of information.
As information spread globally and advancements were made in information technology, the cost of information and its distribution decreased, leading to several noticeable changes. Key elements like the Internet of Things, big data, cloud computing, and cybersecurity continue to dominate the information technology landscape.
The evolution and application of information technology are dynamic and constantly evolving. Several recent trends in information technology include:

Cloud Computing

• Cloud computing is a predominant concept in information technology, encompassing the utilization of computing services, both software and hardware, as a service over a network, typically the internet. It can be visualized as Internet Computing, often represented by clouds. In the realm of cloud computing, users can access database resources through the internet from any location, for any duration needed, without the concern for maintenance or management of the actual resources. It provides an independent platform for computing, and a common example is Google Apps, where applications can be accessed via a browser and deployed on thousands of computers through the internet.
• Cloud computing operates on a pattern where a large pool of systems is connected in private or public networks to offer dynamically scalable infrastructure for applications, data, and file storage. This technology contributes to reducing the costs associated with computation, application hosting, content storage, and delivery. It is a practical approach for experiencing direct cost benefits, transforming data centers from capital-intensive setups to variable-priced environments.
• The core principle of cloud computing is based on the reusability of IT capabilities. What sets cloud computing apart from traditional concepts like "grid computing," "distributed computing," "utility computing," or "autonomic computing" is its ability to broaden horizons across organizational boundaries. According to Forrester, cloud computing is defined as "A pool of abstracted, highly scalable, and managed compute infrastructure capable of hosting end customer applications and billed by consumption."

Cloud computing

Historical review of cloud computing

The concept of an "intergalactic computer network" was introduced in the 1960s by J.C.R. Licklider, an American computer scientist credited with laying the groundwork for ARPANET (Advanced Research Projects Agency Network) in 1969. The evolution of cloud computing has gone through various stages, including grid and utility computing, application service provision (ASP), and Software as a Service (SaaS). While cloud computing has developed along different lines since the 1960s, it only gained significant momentum in the 1990s when the internet started providing substantial bandwidth.

The Principles of Cloud Computing

Cloud computing differs from traditional web services in its fundamental principles, which encompass:

• Resource Pooling: Cloud computing providers achieve significant economies of scale through resource pooling, assembling a vast network of servers and hard drives. They apply a uniform set of configurations and security measures across this pooled infrastructure.
• Virtualization: Users are relieved of concerns about the physical state of their hardware and compatibility issues. Cloud computing leverages virtualization to abstract and manage the underlying physical infrastructure.
• Elasticity: The addition of more hard disk space or server bandwidth can be easily accomplished with just a few clicks, allowing users to scale resources on-demand. Geographical scalability is also available, enabling users to replicate data across multiple data centers worldwide.
• Automatic/Easy Resource Deployment: Users only need to specify the types and specifications of the required resources, and the cloud computing provider will automatically configure and set them up.
• Metered Billing: Users are billed for the specific resources they utilize, following a metered billing model that ensures they pay only for what they use.

General features of cloud computing

Cloud computing is characterized by the following features:

• High Scalability: Cloud environments are designed to cater to the business needs of larger audiences, providing high scalability to handle varying workloads effectively.
• Agility: Operating in a distributed environment, the cloud shares resources among users and tasks, enhancing efficiency and responsiveness. This agility is crucial for adapting to changing demands.
• High Availability and Reliability: Cloud services offer high availability and reliability as the chances of infrastructure failure are minimal. The distributed nature of the cloud infrastructure contributes to this enhanced dependability.
• Multi-Sharing: By working in a distributed and shared mode, the cloud allows multiple users and applications to operate more efficiently. This shared infrastructure leads to cost reductions and improved resource utilization.
• Services in Pay-Per-Use Mode: Cloud services often operate on a pay-per-use model, where users are billed based on their actual usage. Service Level Agreements (SLAs) between the provider and user define the terms of this pay-per-use mode, considering the complexity of the services offered. Application Programming Interfaces (APIs) may be provided to enable users to access cloud services seamlessly.

Types of cloud computing environments

The cloud computing environment encompasses several types of clouds:

• Public Clouds: Public clouds are accessible to the general public, including individuals, corporations, and various organizations. Typically governed by third parties or vendors over the Internet, public clouds provide services on a pay-per-use basis.
• Private Clouds: Private clouds are hosted within an organization's boundaries and are exclusively used for the organization's internal purposes. These clouds are not shared with external entities.
• External Clouds: External clouds exist outside the organization's boundaries. While some external clouds may extend their infrastructure to specific organizations, they are not open to the general public. These clouds may be operated by third-party providers.
• Hybrid Clouds: Hybrid clouds represent a combination of both private (internal) and public (external) cloud computing environments. Users in a hybrid cloud setup can utilize services from third-party cloud providers, either fully or partially. This approach enhances the flexibility of computing by allowing organizations to tailor their cloud strategy to their specific needs.

Models of cloud computing

Cloud computing offers three primary services: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).

• Software as a Service (SaaS): In SaaS, the provider delivers a complete application as a service on demand. A single instance of the service runs on the cloud, serving multiple end users. Customers don't need upfront investments in servers or software licenses, reducing costs for both parties. Major SaaS providers include Google, Salesforce, Microsoft, and Zoho.
• Platform as a Service (PaaS): PaaS encapsulates a layer of software or a development environment as a service, allowing users to build higher-level services. Customers can shape their own applications on the provider's infrastructure, which includes predefined combinations of OS and application servers. Examples include Google's App Engine and Force.com.
• Infrastructure as a Service (IaaS): IaaS provides basic storage and computing capabilities as standardized services over the network. It involves pooled servers, storage systems, networking equipment, and data center space made available for handling workloads. Examples of IaaS providers include Amazon, GoGrid, and 3 Tera.

Advantages of cloud computing include cost reduction, support for virtualization, and simplified maintenance. However, there are concerns related to privacy, compliance, security, legal issues, abuse, and IT governance. Security is a major issue, as adopting cloud technology involves entrusting sensitive information to third-party providers, making companies vulnerable to external threats and hack attacks.
Cloud computing allows access to shared resources and infrastructure over the network to meet changing business requirements. It leverages the Internet for remote computing, providing on-demand hardware and software resources. The physical location of resources is typically unknown to end users, and it enables operators to develop, deploy, and manage applications on the cloud, incorporating virtualization for self-maintenance.

Mobile Application

• Mobile applications, commonly known as mobile apps, have become a significant trend in information technology, especially with the rise of smartphones and tablets. These apps run on mobile devices, providing various functionalities and services to users. The mobile app market is rapidly growing, with a wide range of applications available for download on platforms like Apple, Blackberry, and Nokia.
• Mobile apps serve diverse functions, ranging from basic telephone and messaging services to more advanced features. They are developed by a multitude of mobile app developers, publishers, and providers. The global market for mobile applications is expected to witness significant growth in the coming years, according to various research reports.
• Mobile apps are designed to operate on smartphones, tablets, and other mobile devices. They can be downloaded from different mobile operating systems, with some apps available for free and others incurring a download cost. The revenue generated is typically shared between the app distributor and the app developer. From a technical standpoint, mobile apps can be categorized based on the runtime environment in which they operate, including native platforms, mobile web/browser runtimes, and other managed platforms and virtual machines.
• Notable mobile platforms contributing to the growth of mobile applications include the iPhone, Windows Mobile, Android, and BlackBerry. The iPhone, known for its multi-touch interface and various features, has significantly impacted mobile computing. Windows Mobile allows users to manage various business tasks on their mobile devices, while Android offers a unique technical interface and direct application delivery to end-users. BlackBerry smartphones are renowned for their integrated communication capabilities, serving both individuals and entire enterprises. The continuous evolution of mobile applications is transforming the way users interact with technology and access services on the go.

User Interfaces

The user interface (UI) of an application encompasses the elements visible and interactive on the screen, including document space, menus, dialog boxes, icons, images, and animations. It is the means by which users interact with a computer system, involving both hardware and software components. While the UI is a significant part of the overall user experience, other aspects, such as start-up time, latency, error handling, and automated tasks, also contribute to usability.

There are two primary types of user interfaces:

• Text-Based User Interface or Command-Line Interface (CLI): In a text-based interface, input and output consist of characters, and users interact through the keyboard. No graphics are displayed, and commands are entered via text. Examples include UNIX and DOS-based programs. While CLI allows for more powerful tasks and customization options, it relies heavily on recall rather than recognition, making navigation more challenging.
• Graphical User Interface (GUI): GUI relies on graphical elements and typically uses a mouse for input. Initially developed in the 1970s at Xerox Corporation's Palo Alto Research Center, GUI gained popularity with the success of Apple's Macintosh. Windows Operating System is a popular example of GUI. GUI is known for its user-friendly nature, requiring less expert knowledge and offering easier navigation. Currently, GUIs are dominant, and users generally prefer them over text-based interfaces.

Interfaces today often incorporate variations or combinations of these two types. Web-Based Interfaces and Touchscreens, for example, are variations of GUIs. Touchscreens, in particular, have revolutionized user interaction by allowing direct manipulation of displayed elements without the need for intermediary devices like a mouse. This capability is widely used in smartphones, tablets, information kiosks, and various information appliances.
The development process of a user interface involves several phases, and with the advent of touchscreens, there has been a significant transformation in the way users interact with applications. Touchscreens have become integral in devices such as smartphones, tablets, and information kiosks, offering a more direct and intuitive form of interaction.

Analytics

Recently, the field of analytics has experienced significant growth, evolving into a multifaceted domain that incorporates statistics, computer programming, and operations research. Analytics plays a crucial role in various areas, including data analytics, predictive analytics, and social analytics.

• Data Analytics: Data analytics is a process designed to support decision-making by transforming raw data into meaningful information. It is widely applied in organizations to facilitate informed business decisions and in scientific fields to validate or challenge existing models and theories. The primary focus of data analytics is on inference, where conclusions are drawn based on the knowledge of the researcher.
• Predictive Analytics: Predictive analytics, a subset of data mining, is concerned with forecasting probabilities. This technique involves utilizing measurable variables to predict the future behavior of individuals or entities. Multiple predictors are combined into a predictive model, which is refined as additional data becomes available. Predictive analytics is a tool used to forecast future events based on current and historical information. An example is credit scoring, where models predict the risk of financial loss based on information from loan applications. These models play essential roles in credit decisions, utilizing statistical techniques like linear regression and neural networks to identify predictors and formulate accurate models.
• Social media analytics has emerged as a powerful tool for companies seeking to understand and respond to customer needs. This tool enables businesses to decipher customer sentiment by analyzing vast amounts of data from numerous online sources. Companies leverage the potential of social media to enhance their comprehension of markets. However, extracting actionable insights from this vast pool of data, often referred to as "Big Data," requires advanced analytics expertise. 

Applications of social media analytics

• Find the social strengths and shortcomings of your company and competitors.
• Identify the networks of influential supporters, detractors, and major players, and determine the best ways to reach out to them.
• Perform social research on a company before entering into a venture.
• Identify combustibles, or minor issues with low volume but high intensity that could grow in impact if not addressed early.
• Monitor new developments in industry and in other related industries.

Challenges of social media analytics

• Huge amounts of data require lots of storage space and processing.
• Shifting social media platforms.

Software development life cycle

The Software Development Life Cycle (SDLC) is a systematic process followed in software development projects within software companies. It encompasses a detailed plan outlining the steps to develop, maintain, replace, or enhance specific software. The life cycle serves as a methodology to enhance the overall development process and ensure the quality of the software.
Graphical representation of the various stages of a typical SDLC

The Agile development methodology is a recent model in the Software Development Life Cycle (SDLC).
A classic SDLC comprises several stages:

• Stage 1: Planning and Requirement Analysis: This stage involves senior team members gathering inputs from customers, sales, market surveys, and domain experts to plan the project approach and conduct a feasibility study. Quality assurance requirements and project risks are also identified.
• Stage 2: Defining Requirements: Clear and documented product requirements are crucial, and they are defined in a Software Requirement Specification (SRS) document. Approval from the customer or market analysts is obtained during this stage.
• Stage 3: Designing the Product Architecture: The SRS serves as a reference for product architects to design the best architecture. Multiple design approaches are considered, and the chosen architecture is documented in a Design Document Specification (DDS). This document is reviewed by stakeholders, and the final design approach is selected.
• Stage 4: Building or Developing the Product: Actual development begins in this stage, and the product is generated based on the DDS. Programming code is written following coding guidelines, and programming tools are utilized. Various high-level programming languages such as C, C++, Pascal, Java, and PHP can be employed.
• Stage 5: Testing the Product: Testing activities are integrated into all stages of modern SDLC models. However, this stage specifically refers to the testing phase, where product defects are reported, tracked, fixed, and retested until the product meets the quality standards defined in the SRS.
• Stage 6: Deployment in the Market and Maintenance: Once testing is complete, the product is formally released in the market. Deployment may occur in stages, and the product might be released in a limited segment initially to be tested in a real business environment. Ongoing maintenance follows the deployment phase.

There are several models for SDLC:

• Waterfall Model: The Waterfall model is a traditional, linear, and sequential software life cycle model. It was the initial model widely adopted in the software industry. This approach follows a successive development path, where the development progresses steadily through the phases of requirements analysis, design, implementation, testing (validation), integration, and maintenance. In the Waterfall model, each phase commences only after the completion of the previous one. This sequential nature ensures that each phase is well-defined and precise. The term "waterfall" is derived from the analogy that the phases fall from a higher level to a lower level, resembling the flow of a waterfall. 
  Classical waterfall model
  
• V-Shaped SDLC Model: The V-Shaped SDLC (Software Development Life Cycle) model illustrates the relationship between testing activities and analysis and design phases. It is an extension of the waterfall model, incorporating a structured approach to testing activities with a focus on refining previous development steps and facilitating fallback or correction.
• In the V-Shaped model, each development phase has an associated testing phase, emphasizing a parallel planning of verification and validation activities. The model follows a highly disciplined approach, ensuring that the next phase starts only after the completion of the preceding one.
• The V-Model is characterized by Verification phases on one side of the "V" and Validation phases on the other side. The coding phase connects the two sides of the V-Model. This model is particularly suitable for scenarios where requirements are well-defined, stable, and clearly documented. It is applied when the product definition is fixed, technology is well-understood, there are no ambiguous requirements, and the project duration is relatively short. Industries such as medical development, with strict discipline requirements, often find the V-Model applicable.
• V-Model of SDLC

• Iterative model of SDLC: The Iterative model in SDLC initiates with the implementation of a basic set of software requirements and progressively refines the evolving versions until the entire system is developed and prepared for deployment. Unlike a full specification of requirements at the beginning, the iterative life cycle model commences with the specification and implementation of a partial software, subject to review to identify additional requirements. This cyclic process continues, resulting in a new software version after each iteration in the model.
  
• Prototype: Software prototyping is an approach in software development that involves creating incomplete versions of the software program to address specific requirements or design elements. During prototyping, developers generate the minimum amount of code necessary to illustrate the targeted aspects. This process does not focus on adhering to coding standards, implementing robust error management, or integrating with other database tables or modules. Retrofitting a prototype with the essential elements to create a production module is typically more expensive than developing the module from scratch using the final system design document. For this reason, prototypes are not intended for business use and are often intentionally restricted to prevent inadvertent use as production modules by end-users.
  Prototype model

N tier architecture

N-Tier architecture is a contemporary trend in information technology, characterized as a proven software architecture model suitable for supporting enterprise-level client/server applications and addressing challenges such as scalability, security, and fault tolerance. While .NET offers numerous tools and features, it lacks predefined methods for implementing N-Tier architecture. Consequently, to achieve a well-designed and implemented N-Tier architecture in .NET, a comprehensive understanding of its concepts is essential. Despite being employed for many years, the notion of N-Tier architecture remains somewhat ambiguous.
N tier architecture

Technical documentation defines N-tier data applications as those divided into multiple tiers, also referred to as "distributed applications" and "multitier applications." In these applications, processing is segregated into distinct tiers distributed between the client and the server. When developers create applications that interact with data, it is crucial to establish a clear separation between the different tiers constituting the application.
A standard N-tier application comprises a presentation tier, a middle tier, and a data tier. The most straightforward method to segregate these tiers in an N-tier application is to create separate projects for each tier included in the application. For instance, the presentation tier might be a Windows Forms application, while the data access logic could be a class library situated in the middle tier. Additionally, the presentation layer may communicate with the data access logic in the middle tier through a service. The separation of application components into distinct tiers enhances maintainability and scalability by facilitating the implementation of new technologies in a single tier without necessitating an overhaul of the entire solution. Moreover, N-tier applications typically secure sensitive information in the middle tier, maintaining isolation from the presentation tier.

Advantages of N tier technology are as under:

• More powerful applications
• Many services to, many clients
• Enhanced security, scalability and availability

Disadvantages: There are some drawbacks of this technology:

• Software is more complex (effects design, reliability, maintainability)
• More complicated to design and model
• Performance risks
• Not sure how to achieve reliability
• Software maintenance is very different

Challenges of N Tier technology

• Communication and distribution is usually handled by third-party middleware (CORBA, EJB, DCOM, etc)
• Software becomes heterogeneous and parallel
• A lot of new technologies to learn
• Designing truly reusable objects is difficult
• The design must be high quality
• They may not satisfy the needs of future systems

Conclusion

In the past decade, the field of information technology has undergone significant progress and transformations. As of 2015, the IT industry is experiencing rapid growth marked by increased demand, investments, and technological advancements. This surge is attributed to the adoption of new technologies and applications aimed at enhancing daily business operations. Notably, the substantial impact on businesses is anticipated to improve customer service. Information technology has now become an integral part of society.