Information Technology & Data Analytics
jenny2000000
10-Lesson_10.pdf
Lesson 10: Big Data, Cryptocurrency, Internet of Things
Information Technology & Data Analytics
December 6, 2021
Information Technology & Data Analytics
Lesson 10
Big Data, Cryptocurrency,
Internet of Things
6
Information Technology & Data Analytics
1. Understand Big Data and how does it compare to other data management solutions.
2. Define cryptocurrencies and analyze their future in the global economy.
3. Define what the Internet of Things is, and how can it shape the future of business.
4. Understand trending concepts such as Fintech, Devops and Digital Transformation
STUDENT LEARNING OUTCOMES
7
Information Technology & Data Analytics
Introduction
8
Information Technology & Data Analytics
Introduction: Hype Cycle 2015
9
Information Technology & Data Analytics
Introduction: Hype Cycle 2016
10
Information Technology & Data Analytics
Introduction
11
Information Technology & Data Analytics
Introduction
12
Information Technology & Data Analytics
Introduction
13
Information Technology & Data Analytics
Introduction
14
Information Technology & Data Analytics
Introduction
15
Information Technology & Data Analytics
Introduction
16
Hyper Cycle for Emerging Technologies 2021
Information Technology & Data Analytics
Big Data
17
Information Technology & Data Analytics
➢ Information management strategy which integrates vast amounts of many different types of data regular databases cannot handle
Big data
18
• Relational databases
• Media
• Social media feeds
• Business transactions
• Click streams
• Searches
• Sensor information
• Network traffic
• Mobile app data
• Network connected devices
• Internet of Things (IoT)
• Any other information
Information Technology & Data Analytics
The Three V’s
19TechTarget Big Data
Information Technology & Data Analytics
➢ Volume – Amount of data, usually in high-volumes and unstructured
➢ Velocity – Fast rate at which data is received and processed. Some even may need to be real time
➢ Variety – Diverse data sets. Date may be structured, semi- structured or unstructured • Certain data types rely on metadata, such as media
➢ Value – All data has value, but it needs to be discovered
➢ Variability – Data flows can be very inconsistent
➢ Veracity – Data quality can also vary, making analysis challenging
The Three V’s (Or More?)
20
Information Technology & Data Analytics
➢ Volume of Data – Data-generation has exponentially grown
➢ Storage – It has grown faster, and cheaper
➢ Computing power – It has grown faster, and cheaper
➢ Cloud – Storage and computer power are ubiquitous
➢ Connected Devices – New devices generate more data than ever before
➢ Advanced analytic techniques – including, but not limited to: • Artificial Intelligence (AI) • Machine Learning • Data Mining • Language Processing
What Triggered It?
21
Information Technology & Data Analytics
➢ Many data streams
➢ Data stored across multiple systems
➢ How to analyze all that information?
• We are now taking about terabytes, petabytes, and exabytes
➢ Quality of information
➢ How do we make sense of it to help us make decisions?
➢ Lack of skillful data scientists
What are the Challenges?
22
Information Technology & Data Analytics
➢ To make more informed, better and faster decisions with data that was not available or accessible before
➢ Gain new insights
➢ Discover hidden patterns, and unknown correlations
➢ Real-time analytics (for example, weather forecasts)
➢ Predictive analysis
What are the Goals?
23
Information Technology & Data Analytics
➢ The key for Big Data. Without it, we mainly have useless data
➢ Artificial Intelligence leads the charge
➢ Data visualizations are critical for success
➢ Requires specialized programming languages data science libraries
Big Data Analytics
24
Information Technology & Data Analytics
➢ Hadoop
oApache framework for distributed processing or large data sets across clusters.
• Works at the application layer and it is scalable
• HDFS (Hadoop Distributed File System)
➢ Spark – Apache’s general engine for large-scale data processing
• It enhanced Hadoop
➢ NoSQL databases – More flexible structures than relational ones
• ArangDB, AWS Dynamo, Oracle NoSQL Database, Cassandra
Big Data Tools
25
Information Technology & Data Analytics
➢ Data Science Libraries
oProvide robustness to programming languages to mine and analyze data
• Pandas – Among the most popular, includes features to create large data frames and provide visualizations
• Agate – Newer set. Good visualization abilities
➢ Programming languages
oPython and R are the most used ones for data analysis
• R is more oriented towards data analysis
• Python is also good for general purpose programming
• Others: SAS, Scala (for JVM), Julia
Big Data Tools
26
Information Technology & Data Analytics
➢ Data Lake
• Storage space where heterogeneous data can be kept
• Raw data is stored
• Unstructured, semi structured and structured can live in the same ecosystem
• Tagging suggested
• Avoid swamps
• Schema on Read
• Data Warehouse:
oSchema on Write
Data Lakes
27
Information Technology & Data Analytics
➢ Big data is a reality in today’s business environment, with the major software vendors offering products specialized on it:
• EMC – Big Data
• HP – Vertica Analytics Platform
• IBM – Big Data Analytics
• Microsoft – HDInsights
• Oracle – Big Data Appliance
• SAP – HANA
• Teradata – Unified Data Architecture
Big Data: A Mature Concept
28
Information Technology & Data Analytics
Cryptocurrencies and Blockchain
29
Information Technology & Data Analytics
➢ Digital currency
➢ Uses cryptography for security purposes
Cryptocurrency
30 Huffington Post
Information Technology & Data Analytics
➢ Proposed in 2008 by Satoshi Nakamoto
• No one knows who he is
➢ Developed in 2009
➢ First decentralized digital currency
• Uses peer-to-peer technology to operate with no central authority
➢ According to bitcoin.org: “Bitcoin is a consensus network that enables a new payment system and a completely digital money”
➢ Protocol and software are open
Bitcoin
31
Information Technology & Data Analytics
➢ Uses a public ledger called blockchain
➢ Such ledger contains every transaction ever processed
• The validity of each transaction can be easily verified
➢ Each transaction includes a digital signature corresponding to the sending address
➢ The transaction can bee seen (unencrypted), but the specifics of it are not (encrypted)
➢ Want to know all the details? Read Bitcoin: A Peer-to-Peer Electronic Cash System
Bitcoin: How does it work?
32
Information Technology & Data Analytics
➢ It is a distributed environment
➢ A blockchain database is installed on every computer of every user
➢ There is special software which includes the transactional algorithms
➢ It is known as a trust protocol
Blockchain
33
Information Technology & Data Analytics
➢ If something is changed in one copy, all other repositories receive the transaction and have to agree the change is allowed (consensus)
• If it is allowed, then the transaction goes through
• The transaction gets replicated in all the copies
➢ If someone wanted to hack a single node, then the integrity of all other copies would not allow the change to happen. (immutability)
➢ There are no changes or deletions. Blocks are just added to the ledger
➢ There is some delay on applying the transaction, due to the operations needed and the copies made
Blockchain
34
Information Technology & Data Analytics
➢ Computing power and energy
➢ Transaction speed
➢ Verification
➢ Data Management
➢ Security and Privacy
➢ Integration (Remember standards, SoA, and APIs?)
➢ Transactions are anonymous and irreversible
➢ Cultural adoption
➢ Resistance to Change
➢ Regulations
➢ Insurance
➢ Scalability
Blockchain: Challenges
35
Information Technology & Data Analytics
➢ Democracy Earth – Tested in Colombian voting from abroad in 2016
➢ Everledger – Tracks diamonds around the world
➢ Slock.it – German company already investing in blockchain solutions
• Supply chain, Maritime contracts, Smart homes
➢ R3’s Corda – Frictionless commerce
• Open source hyperledger project
• Not thousands of copies
• Doorman, notary and oracle roles
• So, is it a blockchain?
• Partners: Accenture, Intel, Microsoft, among others
Blockchain: Other Uses Today
36
Information Technology & Data Analytics
Blockchain: Ethereum
37
➢ Developed by the Swiss profit Ethereum Foundation
➢ Decentralized platform that runs smart contracts
➢ Applications run exactly as programmed without downtime, censorship, fraud or third party interference.
➢ Apps run on a custom built blockchain
➢ Allows to: create markets, store registries of debts or promises, move funds in accordance with instructions given long in the past (like a will or a futures contract) and many other things
➢ Ethereum wallet and Solidity (allows to create your own currency or virtual shares
Information Technology & Data Analytics
Blockchain: Other Concepts
38
➢ Interledger – Open protocol for sending payments across different ledgers
➢ Consensys – Blockchain software developer over Ethereum
➢ uPort – Decentralized identity management system over Ethereum
➢ BaaS –
• Block Chain as a Service
Information Technology & Data Analytics
➢ Register digital ownership in a blockchain (Art, pictures, etcetera)
➢ Contracts, property titles, legal certificates, credit ratings • Smart contracts – Buying products or services
➢ Shipping transactions (supply chain) • Maersk working with IBM • Dubai will require blockchain transactions by 2020
➢ Elections
➢ Financial transactions
➢ Smart cars
➢ World Bank’s Bond-I bonds
Blockchain in the Future Today
39
Information Technology & Data Analytics
➢ It has all the properties that are desirable for a currency to have:
➢ Only 21 million bitcoins will ever be available (Scarcity)
• 17.3 million in circulation as of today
➢ Compare it to gold or diamonds: They are scarce and difficult to mine
➢ Its value and trust relies on mathematics
Bitcoin: Why is it safe?
40 Bitcoin Wiki
• Portable
• Durable
• Divisible
• Recognizable
• Fungible
• Scarce
• Difficult to counterfeit
Information Technology & Data Analytics
➢ As a payment
➢ Purchase them at a place such as Bitcoin Exchange
➢ Exchange them with someone near your location
➢ Earn them through
mining
Bitcoin: How do you get one?
41
Information Technology & Data Analytics
➢ Miners share their computing power to mine
• Used to be computers, then switched to graphic cards, as they have faster processing. However, they require more energy
• Now, there are specific ASICs (Application Specific Integrated Circuit) designed for mining.
➢ Miners use special software to solve math problems
➢ Proof-of-Work – When a miner validates adding blocks
Bitcoin: Mining
42
Information Technology & Data Analytics
Bitcoin: Mining
43www.bitcoinmining.com
Information Technology & Data Analytics
➢ Payment freedom
➢ Choose your own fees
➢ Fewer risks for merchants
➢ Security and control
➢ Transparent and neutral
➢ Degree of acceptance
➢ Volatility
➢ Ongoing development
Advantages and Disadvantages
44Governments and ICOs
Information Technology & Data Analytics
➢ Initial Coin Offering (ICO) presents challenges for governments which have different approaches:
• Forbidden city – Illegal until I know what to do
• In the works – Working on legislation around it
• Warning – Might be a security, might not. Follow existing regulations
• Sandbox – Lets try this out and test it
• Jack-of-all-trades – Token sales unregulated, so far…
Bitcoin: and the Governments?
45Governments and ICOs
Information Technology & Data Analytics
Bitcoin over the Years
46Coindesk
Information Technology & Data Analytics
➢ November 18th - 20th, 2013 - U.S. Senate has a hearing on bitcoin, People’s Bank of China endorses it • Value increases from $685.75 to $1,072.83 ten days later
➢ December 5th, 2013 – Chinese government banks bank from using it • Value decreases from $1,022.37 to $839.93 ten days later
➢ April 1st, 2017 – Japan declares it legal tender • Value increases from $1,085.03 to $1,215.69 ten days later
➢ In 2017: • It has become mainstream and celebrities have endorsed it • CME (Chicago Mercantile Exchange) confirmed it would launch
bitcoin future products this year • Hard forks (Bitcoin Cash, Bitcoin Gold, Bitcoin Diamond)
Bitcoin’s Key Events
47
Information Technology & Data Analytics
➢ November 18th - 20th, 2013 - U.S. Senate has a hearing on bitcoin, People’s Bank of China endorses it • Value increases from $685.75 to $1,072.83 ten days later
➢ December 5th, 2013 – Chinese government banks bank from using it • Value decreases from $1,022.37 to $839.93 ten days later
➢ April 1st, 2017 – Japan declares it legal tender • Value increases from $1,085.03 to $1,215.69 ten days later
➢ In 2017: • It has become mainstream and celebrities have endorsed it • CME (Chicago Mercantile Exchange) confirmed it would launch
bitcoin future products this year • Hard forks (Bitcoin Cash, Bitcoin Gold, Bitcoin Diamond) • By December, its value went up to almost $ 20,000 USD
Bitcoin’s Key Events
48
Information Technology & Data Analytics
➢ In 2018:
• January 11 – Bitcoin plummets become South Korea plans to ban cryptocurrency trading
• January 17 – Goes below $10,000 USD
• February 5 – Drops below $6,000 USD
• May 24 – USA investigates if bitcoin prices are manipulated
• August 9 – Australia and the World Bank announce the first blockchain bond, called Bondi.
• September 4- Tsukuba in Japan to use a blockchain-based voting system
• December – 0.5% of world’s electricity used for Bitcoin mining
➢ Many banks and countries planning on releasing blockchain currencies and financial instruments
Bitcoin’s Key Events
49
Information Technology & Data Analytics
➢ Big investors participating of the Bitcoin market
➢ Mainstream adopting digital money
➢ Means of payment
➢ Number of vendors accepting it has increased
➢ Inflation
➢ Central banks embracing cryptocurrencies
➢ Rising cost of bitcoin production
Bitcoin’s Price Jump
50
Information Technology & Data Analytics
➢ The Winklevoss twins invested $11 million back in 2013 • Bitcoin’s value was about $120 back then
➢ Current price per bitcoin as of December 4, 2017: $ 11,637.93 USD
➢ Current price per bitcoin as of December 4, 2018: $ 3,894.13 USD
➢ Current price per bitcoin as of December 2, 2019: $ 7,345.37 USD
➢ Current price per bitcoin as of November 29, 2020: $ 18,091.18 USD
➢ Current price per bitcoin as of November 30, 2021: $ 57,167.45 USD
Bitcoin’s Current Value
51
Information Technology & Data Analytics
Other Digital Currencies
52G
➢ Litecoin – 84 million coin limit • Current value as of November 30, 2021: $213.92 USD
➢ Ethereum – Capped at 18 million ether per year • Current value as of November 30, 2021: $4,758.41 USD
➢ Zcash – 21 million limit • Current value as of November 30, 2021: $222.11 USD
➢ Dashcoin – • Current value as of November 30, 2021 $178 USD
➢ Dogecoin – • Current value as of November 30, 2021: $0.22 USD
Information Technology & Data Analytics
➢ China is promoting Blockchain now (after 5G, AI, and Fintech)
• DC/EP – Digital Currency Electronic Payments system
• Will launch stated-backed cryptocurrency
oCBDC (Chinese Central Bank Digital Currency)
oChinese banks, Alibaba, Tencent and others are key members
• New cryptographic law in effect on January 1st, 2020
oOperational by 2022?
• Announcement made BitCoin rise from $7,500 to $10,000
• Anonymous point-to-point, but not to the state
China’s DC/EP
54
Information Technology & Data Analytics
What is ?
55G
➢ It is a Payment Protocol, called Ripple Transaction Protocol (RTXP)
➢ Its digital currency is called XRP
➢ Provides a frictionless experience to send money globally using the power of blockchain (decentralized)
➢ Can exchange bitcoin, euros, U.S. dollars, yen, yuan, rupees, gold
➢ Users specify who they trust and up to what amount
➢ Rippling – Exchange between users who do not trust each other through paths of trust
➢ Bank of America, Royal Bank of Canada, UBS, Mitsubishi and Santander
Information Technology & Data Analytics
Internet of Things (IoT)
56
Information Technology & Data Analytics
➢ The world is becoming more interconnected every day
➢ It started with computer networks
• Then joined by other devices such as smartphones and tablets
• Televisions and other every day devices with internet access joined shortly after
• Any device with a computer can join as well
• Appliances are now joining
• Anything traceable can be part of it too
• Also animals are being invited
• And humans are being integrated into it now
Internet of Things (IoT)
57
Information Technology & Data Analytics
➢ Internet of Things – System or network of physical devices entities or things which are capable of connecting to each other and transfer data between them
• Each thing has a unique identifier
• Each thing can communique without human intervention
• Can work in a coherent system to solve problems
• Can seamlessly connect and talk to each other
Internet of Things (IoT)
58
Information Technology & Data Analytics
➢ Wireless communications (Wi-Fi, NFC, Bluetooth)
➢ IPv6 – 128-bit addresses (2128) versus IPv4 32 bit addresses (232)
➢ Artificial intelligence
➢ Natural language processing
IoT Enablers
59
Information Technology & Data Analytics
➢ MTA bus and subway tracker
➢ Copenhagen smart city
➢ Smart thermostat (ConEd promotes its use in NYC)
➢ Smart Locks
➢ Smart Houses
➢ Smart Pet Feeders
➢ Package tracking
IoT Currently in Action
60
Information Technology & Data Analytics
➢ Volume of information generated
➢ Seamless communication between things
➢ Improve data analytic tools
➢ Privacy and security
➢ Consequences of possible hacking
IoT Concerns and Challenges
61
Information Technology & Data Analytics
➢ Google Assistant
➢ Amazon Echo
➢ The regular players: Hitachi, Intel, Microsoft, Oracle, Samsung
➢ Skyworks Solutions (manufactures chips for Apple, Amazon, Samsung, Cisco, among others)
➢ Broadband providers
➢ Cisco
➢ GE
➢ Huawei
IoT Main Players
62
Information Technology & Data Analytics
➢ Find my keys!
➢ Controlling house appliances from afar
➢ Gas tank contacting the gas supplier when it reached a threshold
➢ Pacemaker letting the hospital know it is about to fail
➢ Fridge contacting the supermarket to order products
➢ Sheep herders easily locating a lost animal
➢ Parents knowing where their kids are
➢ Alarm clock letting the coffee machine know it has to work
IoT Possibilities are Limitless
63
Information Technology & Data Analytics
➢ Volumes of data will become huge
• Businesses will know more about their customers than ever
➢ Will be able to make better decisions
➢ Will be able to further segment markets
➢ Will react faster to address customer needs
➢ Supply chains will become even more efficient
IoT in the Business World
64
Information Technology & Data Analytics
IoT Forecast
65Statista
IoT Connected Devices Worldwide
Information Technology & Data Analytics
IoT Endpoint Spending Worldwide by Category
IoT Forecast
66Statista
Information Technology & Data Analytics
Fintech
67
Information Technology & Data Analytics
➢ Technology that improves or automates the delivery of financial services
➢ Started at the back-end, now in the forefront
Fintech
68
❑ Cryptocurrency and blockchain
❑ Payment services
❑ Banking Applications
❑ Loan services
❑ FICO scores
❑ E-Trades
❑ Insurance
❑ Financial advisors
❑ AI trading
❑ Regtech (regulations)
Information Technology & Data Analytics
Edge Computing
69
Information Technology & Data Analytics
➢ “a part of a distributed computing topology in which information processing is located close to the edge – where things and people produce or consume that information.” (Gartner)
➢ In English, it means that computing is done at or near the source of data.
➢ Why? • Speed • Bandwidth • Latency • Privacy • Security
➢ Why not? • Control
Edge Computing
70
Information Technology & Data Analytics
Devops
71
Information Technology & Data Analytics
➢ DevOps is a set of practices that automates the processes between software development and IT teams, in order that they can build, test, and release software faster and more reliably
➢ In English, it brings the development and operations teams closer together
➢ Looks for better integration and collaboration
➢ Includes, but it is not limited to: • Agile • Continuous delivery • Automation • AI
Devops
72
Information Technology & Data Analytics
Digital Transformation
73
Information Technology & Data Analytics
➢ Digital transformation is the process of using digital technologies to create new — or modify existing — business processes, culture, and customer experiences to meet changing business and market requirements. This reimagining of business in the digital age is digital transformation.
➢ Precursors: • Digitization - Analog to Digital • Digitalization – Do things faster and better once data is easily
accessible
➢ What is the focus? • To improve, simplify, change processes • To create efficiencies and automation • To lead into better customer experiences
➢ It is all about the customer: adding value to customer interactions
Digital Transformation
74
Information Technology & Data Analytics
➢ In today’s world, it usually means:
• Moving to the cloud
• As-a-Service
• Using Social Media to go look for your customers
• Revamping organizations and processes (devops included)
• Embracing new technologies
Digital Transformation
75
Information Technology & Data Analytics
➢ Recommendations
• Do not buy into the hype
• Do not stay static
• Get the buy in from the top, and set goals
• Plan to scale
• Focus on a market-oriented business model
• Openness and innovation
• Plan less, do more
• Do not forget about people: focus on a culture of change
Digital Transformation
76
Information Technology & Data Analytics
➢ What is Next?
• The Self-Driving Enterprise
oAI-Driven
oAutomated
oBI at hand
Digital Transformation
77
Questions?
Thank you!
