Emerging Technology BIG DATA CONCEPT,IOT

this topic give clue of emerging technology as a concept
used for educational purpose

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UNIT 2
EMERGING TECHNOLOGIE S
@Emerging Technologies
- Introduction:
- Rapid advancements in technology
- Emerging technologies shaping the future
Artificial Intelligence (AI)
- AI:
- Simulation of human intelligence in machines
- Machine learning, natural language processing, computer vision
- Applications in various industries: healthcare, finance,
transportation
Internet of Things (IoT)
- IoT:
- Interconnected devices and objects
- Sensor technology, data exchange, automation
- Smart homes, industrial automation, healthcare monitoring
@Blockchain
- Blockchain:
- Distributed ledger technology
- Secure and transparent transactions
- Applications in finance, supply chain, voting systems
@Augmented Reality (AR) and Virtual Reality (VR)
- AR and VR:
- AR: Overlaying digital information on the real world
- VR: Immersive virtual environments
- Applications in gaming, training, architecture, tourism
2.1. Introduction to Bigdata
- Introduction:
- Living in a digital world
- Tremendous amount of data generated by digital services
- Increasing data sizes
- Big Data:
- Definition: Collection of massive and complex data sources
- Challenges in processing using typical software or database tools
- Exponential explosion of data since the digital age
- Computers, the Internet, and technology enabling data capture and
conversion
@Sources and Collection of Big Data
- Organizational Sources:
- Identification of data-generating sources
- Examples: business firms, IoT ecosystems, marketing firms, social media
- Additional sources: smartphone locational data, surveys
- Data Source Identification:
- Start of the Big Data collection process
- Building a pipeline to move data to enterprise locations
- Data storage for organizational use
@Big Data in Action - Google Example
- Google and Big Data:
- Global company leveraging Big Data
- Understanding user preferences and needs
- Parameters for Understanding Users:
- Search history analysis
- Location-based data
- Trends and patterns
- Benefits and Applications:
- Improving user experience
- Personalized recommendations
- Enhanced business strategies
@Characteristics of Big Data
- Introduction:

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- Big Data defined by 5V characteristics
- Additional features evolving through research
1. Variety
- Variety of Big Data:
- Structured, unstructured, and semi-structured data
- Data collection from spreadsheets to diverse forms
- Examples: emails, PDFs, photos, videos, social media posts

2. Velocity
- Velocity:
- Real-time creation of data
- Speed at which data is generated
- Importance of capturing and processing data in real-time
3. Volume
- Volume:
- Huge volumes of data generated daily
- Sources: social media platforms, business processes, machines, networks,
human interactions
- Scale of data generation and storage
4. Veracity:
- Degree of reliability of data
- Challenges of filtering unstructured data
-5. Value:
- Focus on valuable, reliable, and trustworthy data
- Importance of storing, processing, and analyzing data to find insights
@Benefits of Big Data
- Introduction:
- Big Data projects and their impact on various domains
- Initiatives in Ethiopia leveraging Big Data
1. Customer Acquisition and Retention
- Customer satisfaction:
- Utilizing consumer data for marketing efforts
- Acting on trends to increase customer satisfaction
- Examples: personalization engines for Amazon, Netflix, Spotify
2. Targeted Advertisements (Ads)
- Personalization data:
- Past purchases, interaction patterns, product page viewing histories
- Compelling targeted advertising campaigns
- Individual-level and large-scale targeting
2. Product Development and Price Optimization
- Product development:
- Updating existing products/services and innovating new ones
- Meeting evolving customer needs and preferences
- Price optimization:
- Minimizing manual work and reducing errors
- Dynamic pricing strategies based on real-time data
3. Risk Management and Improved Decision-making
- Risk management:
- Big Data analytics for identifying new risks from data patterns
- Effective risk management strategies
- Improved decision-making:
- Extracting business insights from relevant data
- Quicker and better decision-making processes
Application of Big Data
- Introduction:
- Big Data's value generation in various sectors
- Examples of sectors benefiting from Big Data
Healthcare
- Impact in healthcare:
- Informing health prevention, intervention, and management
- Improving patient experience, care efficiency, and quality
- Reducing healthcare costs
- Examples: patient records, medical exam findings, AI-powered devices,
telemedicine
Education
- Improving education:
- Tailoring learning plans based on student data
- Blended learning opportunities

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- Evaluating applications and selection process
- Enhancing student experience and evidence-based decision-making
Banking
- Banking sector benefits:
- Real-time fraud detection
- Compliance verification and auditing
- Simplifying processes and reducing costs
- Customer feedback and social media analysis
Agriculture, Manufacturing, and Retail
- Agriculture:
- Smart farming and precision agriculture
- Maximizing agricultural outputs and cost savings
- Manufacturing:
- Creating transparent infrastructure
- Predicting uncertainties and improving efficiency
- Retail:
- Personalized customer experiences
- Boosting sales, revenue, and customer service
Transportation and Other Industries
- Transportation:
- Optimizing route planning and traffic management
- Improving services in the transportation sector
- Other industries:
- Media and entertainment, energy and utilities, government-related
activities
Challenges of Big Data
- Introduction:
- Despite the benefits, Big Data poses challenges
- Current major challenges in managing and utilizing Big Data
Managing Big Data Growth
- Data storage:
- Proper handling of large data volumes
- Data centers and databases constantly expanding
- Growing Big Data sets make management more difficult
Lack of Data Professionals
- Skilled workforce:
- Demand for data scientists, analysts, and engineers
- Shortage of professionals experienced in Big Data
- Importance of studying and practicing data science concepts
Securing Data
- Data security challenges:
- Ensuring the protection of large data sets
- Focus on understanding, storing, and analyzing data
- Need for attention to prevent data breaches
Integrating Data from Various Sources
- Multiple data sources:
- Social media, software products, log files, financial data, emails,
etc.
- Determining relevant data and optimizing resources
- Saving time and cost for organizations
Conclusion
- Evolving challenges:
- Dynamic nature of Big Data technologies
- Ongoing advancements and changes in challenges

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Slides: Cloud Computing
---
@Introduction to Cloud Computing
 Definition of cloud computing
 Storing and accessing data and computing services
over the Internet
 No data stored on personal computers
---
@Computing Services in the Cloud
 On-demand availability of computing services
 Servers, data storage, networking, databases, etc.
 Accessible from a single data center
---
@Advantages of Cloud Computing
 Accessible to many users without limitations
 Easy and flexible access to computing resources
 Access to IT services without hardware and
software constraints
---
@Cloud Computing in Our Lives
 Personal experience with cloud computing
 Importance of cloud computing in various aspects
of life
---
@Cloud-Based Services
 Examples of cloud-based services
 Gmail, Google Maps, Amazon, Netflix, PayPal,
Spotify, Adobe Creative Cloud, Kindle, etc.
---
@Use Cases of Cloud Computing

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 Email communications
 Document management
 Entertainment services
 E-commerce services
---
@Components of Cloud Computing
 Hardware and software components required for
cloud computing
 Infrastructure, platform, and software as a service
(IaaS, PaaS, SaaS)
---
@Cloud Computing Providers
 Leading providers in the cloud computing industry
 AWS, Microsoft Azure, Google Cloud, IBM Cloud,
etc.
---
@Future of Cloud Computing
 Emerging trends and technologies in cloud
computing
 Impact on businesses and individuals
---
@Conclusion
 Recap of cloud computing benefits
 Importance in our daily lives
 Potential for future advancements
Slides: Benefits of Cloud Computing
 Accessibility and mobility
 Data backup and recovery
 Support for inclusive education
---
@Accessibility and Mobility
 Access tools from anywhere, at any time, and on
any device
 Rapid storage and retrieval of resources from
distant servers
 Seamless communication and collaboration
---
@Data Backup and Recovery
 Cloud service provider backs up user data
 No loss of data even if services fail
 Ensures data integrity and availability

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---
@Support for Inclusive Education
 Cloud-based services facilitate inclusive
technologies
 Voice recognition, mind mapping, word prediction,
etc.
 Accommodates special needs learners
---
@Flexibility
 Services are highly adaptable and can be changed
as needed
 Resources can be restricted or enhanced based on
requirements
 Real-time collaboration on the same content
---
@Updating and Scalability
 Service provider handles maintenance and updates
 Users can focus on work and increase efficiency
 Scalable resources to meet evolving needs
---
@Optimized Security
 Enhanced security compared to traditional
infrastructures
 Cloud Computing provides robust security
measures
 Relieves companies from the burden of securing IT
systems
---
@Controlled Costs
 Greater control of IT infrastructure costs
 Adjust resources based on needs
 Pay-as-you-go model eliminates upfront
investments
---
@Cost Optimization
 No maintenance or equipment renewal costs
 Reduced IT investments and operational costs
 Optimized business expenses
---
@Conclusion
 Recap of the benefits of cloud computing

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 Accessibility, data backup, inclusive education
support, flexibility, scalability, security, and cost
control
 Emphasize the impact and value of cloud
computing in various domains

---
@Example of Website Hosting
 Introduction to hosting a website
 Two options: Physical server vs. Cloud-based
service
---
@Option 1 - Physical Server
 Buying a physical server
 Hosting it in your data room
 Getting a public IP address from your service
provider
---
@Challenges of Option 1
 Investment of time and money
 Buying server hardware and setting up the data
center
 Installing an operating system and web services
---
@Alternative - Option 2: Cloud-based Service
 Cloud-based website hosting
 No need to buy new server hardware
 Borrow resources from a cloud service provider
---
@Benefits of Option 2
 Cost and time savings
 No need to manage operating systems and web
services
 Easy upload of website content
---
@Cost and Time Savings
 No upfront investment in server hardware
 Lower costs compared to physical server hosting
 Quick setup in minutes instead of weeks or months
---
@Easy Website Management

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 Cloud service provider manages operating systems
and web services
 Simple upload process for website content
 Accessibility and availability to the public
---
@Understanding the Benefits of Cloud Computing
 Example of website hosting highlights cloud
computing advantages
 Cost savings, time efficiency, and simplified
management
---
@Conclusion
 Recap of the example of hosting a website
 Benefits of cloud-based services
 Introduction to the next section on various cloud
services

@Limitations of Cloud Computing

 Server downtime
 Security and privacy issues
 Data ownership and transparency
---
@Server Downtime

Service interruptions can occur, preventing access to data or files
Dependency on Internet connection
Impact on cloud services during network outages.
Server downtime refers to the period when a server or a network
service is unavailable or inaccessible to users. In the context of cloud
computing, server downtime can have a significant impact on cloud
services, especially during network outages. Here's a further
explanation of the impact:

Unavailability of Cloud Services: During network outages, if
the Internet connection between the user and the cloud service
provider is disrupted, it can result in the unavailability of cloud
services. Users may not be able to access their applications,
data, or files stored in the cloud. This can cause disruptions in
business operations, loss of productivity, and frustration
among users.

Disrupted Data Access and Collaboration: Cloud services
often involve real-time collaboration and data sharing among
multiple users. When server downtime occurs due to network
outages, it hampers the ability of users to access and
collaborate on shared data. This can delay important tasks,
hinder communication, and impact teamwork.

Service Degradation and Performance Issues: Network outages can
lead to service degradation and performance issues in cloud services.
Users may experience slow response times, increased latency, or
intermittent connectivity. This can affect the overall user experience
and productivity, especially for applications that require real-time
interactions or large data transfers.

Data Synchronization and Data Loss Risks: In cloud computing,
data is often stored and synchronized across multiple servers or data
centers for redundancy and data protection. However, during network
outages and server downtime, the synchronization process may be

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interrupted. This can result in data inconsistencies, potential data loss,
or delays in data backup and recovery operations.

Service Level Agreement (SLA) Violations: Cloud service providers
typically offer Service Level Agreements (SLAs) that define the
guaranteed uptime and availability of their services. Network outages
and server downtime can lead to violations of these SLAs, causing the
provider to be in breach of their service commitments. This may result
in financial penalties or compensation claims from users.

To mitigate the impact of server downtime during network outages,
cloud service providers employ various strategies such as
implementing redundant network connections, using backup servers,
and distributing data across multiple data centers. Additionally, users
can also consider implementing backup plans, data replication, and
disaster recovery solutions to minimize the impact of server downtime
on their cloud services.
---
@Security and Privacy Issues

Concerns about the safety and privacy of sensitive data
Risk of intruders despite security processes
Constant evolving threats in the digital world
---
@Data Ownership and Transparency

Lack of transparency regarding data ownership
Questions about how data is managed and compromised
Uncertainty about the control and ownership of uploaded data
---
@Inflexibility

Cloud providers may restrict the usage of specific applications or
formats
Limited control over data handling by the cloud provider
Potential constraints and limitations on data management
---
@Lack of Support

Minimal to no customer assistance compared to other hosting services
Limited communication channels with cloud providers
Reliance on Internet forums for support and answers
---
@Cost

Unknown fees and potential cost variability
Need to ensure payment for required features
Possibility of high costs associated with cloud services
---
@Considerations and Mitigation

Weighing the benefits and limitations of cloud computing
Implementing additional security measures to enhance data protection
Ensuring clear understanding of data ownership and management



Types of Cloud Computing
 Public Cloud
 Private Cloud
 Hybrid Cloud
 Community Cloud

1. Public Cloud
- Standard cloud computing model.
- Public cloud refers to cloud computing services provided by third-
party providers over the internet.
- Service provider's resources shared across different clients.
Comment [p1]: Third part are like companies
or organizations

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- Shared storage capacity from a logically divided storage device.
-It offers scalability, cost-effectiveness, and flexibility.
-Examples: Amazon Web Services (AWS), Microsoft Azure,
Google Cloud Platform (GCP).(for figure refer your text book)
Question1 how resources are shared? List at least two resources?

2. Private Cloud
- Dedicated resources for your application
- Can be from a cloud service provider or your company's data center
- Offers complete control over data security and privacy.
-The infrastructure and resources are exclusive to the organization,
providing greater control and security.
-It offers more customization and can meet specific compliance or
regulatory requirements. .(for figure refer your text book)
Examples: VMware vCloud, OpenStack.

Question1 how resources are shared? List at least two resources?
3. Hybrid Cloud
- Combination of public and private cloud
- Host public services in the public cloud and confidential/data-related
services in the private cloud.
- Provides flexibility and benefits from both models.
-It allows organizations to use both on-premises infrastructure and
public cloud services.
-Organizations can move workloads and data between the public and
private clouds as needed. .(for figure refer your text book)
-Examples: AWS Outposts, Azure Stack, Google Anthos.

4. Community Cloud
- Collaborative, multi-tenant platform for distinct organizations.
- Shared applications within the same industry or field.
- Common concerns regarding security, compliance, and performance
- Functions like a private cloud, but managed privately
- Used by governmental institutions, healthcare facilities, financial
services companies, and professional communities).(for figure refer
your text book)





Cloud Computing Services
o Three major cloud computing services:
- Software as a Service (SaaS)
- Platform as a Service (PaaS)
- Infrastructure as a Service (IaaS)

 Software as a Service (SaaS)
-Definition:- Software distribution model hosted by a vendor and
accessed over a network or the Internet
- Benefits: Availability from anywhere, subscription-based,
compatible with all Internet-enabled devices.
- Examples: Google Workspace, Dropbox, Microsoft Office 365,
Slack, Cisco WebEx, Concur, GoToMeeting, etc.
 Platform as a Service (PaaS)
- Definition: Platform and environment for developers to build
applications and services
- Benefits: Supports application development, software support and
management services, collaboration, hosting, etc.
- Examples: Windows Azure, Heroku, Force.com, Google App
Engine, Apache Stratos, OpenShift, etc.

 Infrastructure as a Service (IaaS)
- Definition: Access to computing resources in a virtualized
environment over the Internet
- Benefits: Cost-effective solution for IT infrastructure, scalability,
flexibility
- Examples: Amazon Web Services (AWS), Cisco Metapod,
Microsoft Azure, Google Compute Engine (GCE), etc.

- Summary of Cloud Computing Services
- Different businesses utilize different components based on their
requirements
Comment [p2]: Is third party?
Comment [p3]: Means on-premises
infrastructure" refers to the computing
resources, such as servers, storage systems, and
networking equipment, that are owned,
maintained, and operated by an organization
within its own physical premises or data
centers.
Comment [p4]: are computing resources and
services that are provided by third-party cloud
service providers over the internet.
Comment [p5]: EXPLAIN THE CONCEPT
VIRTUALIZATION ENVIRONMENT

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- SaaS for software distribution and accessibility
- PaaS for application development and support
- IaaS for computing resources and infrastructure
- Cloud computing services offer various benefits to businesses
- SaaS, PaaS, and IaaS cater to different needs
- Choose the appropriate cloud computing service based on specific
requirements.

Fog Computing

-Fog computing is Extension of cloud computing
- Overcoming limitations of cloud computing

 Cloud Computing Challenges
- Congestion due to high data processing, sending, and receiving.
- Reliance on network service provider's bandwidth capacity
 What is Fog Computing?
- Introduction to fog nodes
- Closer proximity to data source
- Higher processing and storage capability
- Advantages of Fog Computing
o Local data analysis at the edge.
o Quicker data processing compared to centralized cloud
processing.
o Improved quality of service and reduced latency.
o Enhanced user experience.

 Fog Computing and End-users
- Closer proximity to small end-users
- Wider consumer reach
- Better mobility and direct device-to-destination connections
 Fog Computing and IoT (Internet of Things)
- Support for IoT devices embedded with sensors.
- Real-time, Big Data operations.
- Ability to support billions of nodes in dynamic and diverse
environments.
 Application of Fog Computing:
- Video Surveillance.
- Challenges of transferring large video streams across networks.
- Use of fog computing to process videos locally and reduce network
congestion.



Conclusion
- Fog computing extends cloud computing with closer proximity and
better mobility
- Benefits include improved user experience, reduced latency, and
support for IoT
- Application examples include video surveillance and other real-time,
data-intensive operations
Internet of Things (IoT)
- Internet created in the late 1990s, over 30 years old
- Definition of IoT: A network of physical objects or people equipped
with software, electronics, networks, and sensors to collect and
exchange data
- IoT extends internet connectivity to devices beyond computers and
smartphones
- Enables remote control and automation of devices.
- Makes things smarter through AI algorithms, data collection, and
networks.

Examples of IoT
- Animal tracking devices.
- Diabetes monitors.
- AC sensors for temperature adjustment.
- Smart wearable’s

Advantages of IoT

1. Efficiency:
- Trustworthy and secure real-time data collection.
Comment [p6]: Assume that you are the website
developer and you want to host your website to the
cloud so which cloud service provider is suitable for
your work please neatly describe your evidence?
Comment [p7]: Differentiate fog computing vs
cloud computing
Comment [p8]: What are the limitation of cloud
computing list down?

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- Translated into useful information for enterprises.
- Reduces resource consumption and improves productivity.
- Voice assistants for quick information retrieval.

2. Technical optimization:
- Control multiple devices using a single device (e.g., smartphone)
- Control TV volumes, thermostats, lighting, etc.

3. Convenience:
- Provides quick and quality solutions.
- Improves customer experience.
- Understands customer pain points and offers personalized solutions.

4. Conservation:
- Monitors traffic, water/electricity usage, air quality.
- Assists in finding solutions for smart cities.

5. Personalization:
- IoT devices collect user data.
- Triggers personalized services based on user preferences.

Limitations of IoT

1. Security and privacy:
- Difficulty in securing and protecting data.
- Concerns in sensitive industries (healthcare, banking).
- Compliance with global information privacy regulations.

2. Connectivity and power dependence:
- Internet and constant power required for successful operation.
- Disruptions affect connected devices.

3. Complexity and Integration:
- Complicated design, maintenance, and deployment.
- Lack of standardized protocols and compatibility.
- Challenges in integrating with different hardware setups.

4. Higher cost:
- Significant time and financial investment for device deployment.
- Purchasing, setup, and installation by professionals.
- Exponential cost increase with numerous devices.
- IoT enables the interconnection of devices and people for data
exchange.
- Offers advantages such as efficiency, technical optimization,
convenience, improved customer experience, conservation, and
personalization.
- Faces challenges in security, connectivity, complexity, and cost.
- Despite limitations, IoT presents significant opportunities for linking
the digital and physical worlds.



How Does IoT Work?

- A complete IoT system integrates four components
1. Sensors/devices.
2. Connectivity.
3. Data Processing.
4. User Interface.

1. Sensors/Devices
- Sensors or devices collect data from the environment.
- Examples: temperature sensors, proximity sensors, humidity sensors,
smoke sensors, water quality sensors, infrared sensors, motion sensors.
- Sensors can be bundled together or part of a multi-functional device
(e.g., smartphones)

2. Connectivity

- Collected data is sent to the cloud.
- Connectivity options include cellular, satellite, Wi-Fi, Bluetooth, or
Ethernet.
- Choice of connectivity depends on the specific IoT application.

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3. Data Processing

- Data is processed in the cloud.
- Simple processing: ensuring data is within permissible limits.
- Complex processing: utilizing computer vision for video analysis.
- Users may intervene or take action based on processed data.

4. User Interface

- Information is made available to the end-user.
- Alerts can be sent via email, text, notifications, etc.
- Users can remotely control or adjust parameters through an app.
- System can also take automatic actions based on predefined rules.




@Application of Internet of Things

- IoT has applications in various sectors:
- Healthcare
- Economy
- Marketing
- Finance and banking
- Government sectors

IoT Application Examples

Smart Home:
- Smoke detector, light bulbs, appliances, door and window locks, pet
monitoring camera, smart thermostat

Smart City:
- Traffic management, waste management, water distribution

Supply Chain:
- Real-time goods tracking, inventory information

Connected Health:
- Patient care, calorie expenditure, heart rate monitoring, activity
levels

Connected Cars:
- Automatic billing, insurance, parking management

Smart Outlets:
- Remote device control, energy tracking

Impact of IoT

- IoT affects many areas of day-to-day life.
- Solves social and technical issues through applications.
- Offers automation, connectivity, and customization.