Analytics MIDTERM

Surrender response to the big data identity threat

"you have zero privacy anyways,. get over it" -Scott McNealy; give in and accept your data will be taken from you

What are 2 conditions necessary for data mining?

1. clean and consistent data data 2. events in the data must reflect current and future trends

Two main problems of the privacy vs convenience dilemma

1. digital slavery 2. identity prison

The lifecycle of predictive models: 1. 2. 3.

1. historical data-data from past collected and prepped to use 2. predictive algorithms-applied on top of the data acquired 3. Model-model is built and when possible embedded into system to optimize performance

Machine learning is a subset of ....

Artificial intelligence, they are no synonymous

AI Subsets: Artificial Intelligence Machine Learning Deep Learning

Artificial intelligence-software that automates and mimics/improves upon tasks that would otherwise require human intel Machine learning- subset of AI results improved without explicit programming Deep Learning-type of ML, includes several layers of analysis between input data and output results

Data collection organizations

Census, BLS, NOAA

Describe the chain that leads from data to a decision Data Information Knowledge Wisdsom Decision

Data: raw numbers Information: contextualized raw numbers knowledge: patterns, trends, insights wisdom: breaking of a knowledge shield decision: leads to some action by managers

What form of analytics does hindsight match with? what are some examples of hindsight?

Descriptive analytics-dashboards, scorecards, data warehouses

Data is a datawarehouse has already forgone the _____ process

ETL

ETL aka

Extraction-taking only important/relevant data Transformation-cleaning data for missing, repeated, incomplete data, take 70% of time Loading-once done, ready to load it into data warehouse

What is the evolution of buisness analytics?

From descriptive analytics, to predictive, and to prescriptive analytics

Types of AI: ___________ Learning on the outside ring and _________ Learning on the inside ring

Machine; Deep

What is a common database for data/public data?

NoSQL, used to query database, does not have a rigid structure like relational databases, can take in a verity and massive amounts of data that is less structured ex: documents

What are concerns with public data

Privacy concerns and accuracy concerns

Reclusive response to the big data identity threat

Protect privacy and control over your identity by avoiding the conveniences of the data gatherers, meaning you dont buy from Amazon, Uber, check WebMS, use AirBNB, Canvas etc. this is impossible to do in todays world

Great leaders ask great _________

Questions

True strategic asset data is when its...

Rare, Valuable, imperfectly imitable, and lacking in substitute

T or F: data by itself can be a source of competitive advantage if used properly

True

T or F: technology by itself is not a source of competitive advantage

True

Describe the 4 V's of Big data

Volume-huge amount, need a better level of IT infrastructure to store information that is much bigger than a laptop could hold Variety-so many different types of data is collected in so many different forms, for example image data, video data, canvas data, biometric data Velocity-constantly coming in at such high volumes in specific directions that are hard to keep up with Veracity-the degree of uncertainty in the data that is used to make a decision; we must make sense of the data even though there is veracity/uncertainty

report

a collection of visualizations and contain much more detailed information than dashboards, created with descriptive analytics

Data Analytics

a comprehensive process to analyze data and produce outputs that can inform decision-making

Dashboards

a visual representation of company performance, use Key Performance Indicators KPI, created with descriptive analytics

you can create new catagories from public data, like what?

ability to afford products, for example: thrifty elders, new age/organiza life style adherents, people who do a lot of medical googling

Data mining has roots in ___________ __________

artificial intelligence

91% of Fortune 1000 senior executives surveyed said ______ _________ initiatives were planned and underway, however many organizations lack skills required to exploit big data, there is a talent shortfall of data analysts/scientists

big data

Privacy Convenience Dilemma

big data is a threat to our privacy because companies use the collection of data for problems like digital slavery and an identity prison

Data Warehouses

central repository of info that can be analyzed to make more informed decisions; data inflows into a warehouse from transactional systems, regional databases, etc. on a regular cadence

Data aggregators

combine data from various sources and package it for resale ex: Carnival Cruise lines integrated their customer data with SES data to target limited marketing dollars to past customers who are likely to afford to use a cruise line again

Descriptive analytics use infrastructure needed tools used disadavantage

commonly known as buisness intelligence, used to create dashboards/reports to show past/current events, need data warehouses for them. Use SQL, PowerBI, Tableau, and Qlik. It is disadvanatged in the fact that it does not explore root causes behind observed trends and can also predict future outcomes, based on historical data analysis

Big data helps track and predict this form of privacy concern

consumer targeting

Privacy is the critical ability to evolve, to adopt a new identity, and _________ robs us of that opportunity

convenience

Dynamic response to the big data identity threat

create a rhizome identity, accept the big data convenicne but rethink how we generate our identify that that we retain control over our information and anatomy, even while submitting to the invasion of the data platforms. Do not give in to the convenient "buy now" or "recommended tabs" instead search for your things on your own, and continuously evolve your identity as you should as a person

rhizome identities conceive privacy as ________, not preserved

created

enterprise software

customer relationship management systems, supply chain management systems, enterprise resource planning systems

Capitalizing on _____ helps firms dominate their markets

data

Buisness Analytics

data analytics applied in the context of buisness

data mart

data is organized into a specific predetermmined and acessible structure, easier for end-users who expect to have regular access to data in a specific format for reporting and standard analysis; contains a subset of data warehouse information, you can take a few bits out of the data warehouse onto a harddrive and taking it with you in your job or office to make it less and more portable

data warehouse

data is organized into a specific predetermmined and acessible structure, easier for end-users who expect to have regular access to data in a specific format for reporting and standard analysis; it has a strong folder structure and is a central hub of all information that is organized logically and cleaned up. They would sort music, documentsm, pictures etc

Predictive analytics are performed by...

data scientists or simpler models by data analysts

surveys and focus groups

data that cant be captured during transactions

Data Scientists toolkit

data visualization ex: GGplot Programming, ex: Python/R Statistics Data mining: machine learning, deep learning, neural networks Non-technical skills (buisness acumen, comm skills, data intuition

What are hard skills required for a data analyst?

data visualization, excel, databases and SQL, foundation of machine learning, knowledge in analytical and stat techniques

Buisness analysts, data engineers, data scientists, and decision makers access ____________ with buisness intelligence tools

data warehouses

what kind of infrastructure does predictive analytics use? tools?

data warehouses and machine learning; Hadoop, R, Python

Predictive analytics applications

demand forecasting, workforce planning, churn analysis, fleet or equipment maintenance, modeling credit/financial risk

Buisness Intelligence (BI) is an alternative name for...

descriptive analytics

forms of response to data threats that require labor/effort

dynamic (adopt rhizome) and reclusive

predictive analytics application: churn analysis

evaluation of a company's customer loss rate in order to reduce it

Big Data tracks you __________

everywhere, when you use a website, excel, a phone, car, laptop, antivirus software, symtpomchecker, tinder, netflix, watches, doctor

Convenience gives us please, but ________ convenience is corruptive, for example:

extreme; a highly automated car robs you of your driving experience; you lose experience of shopping, learning, growing, exploring

Big Data

extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.; has 4 components: velocity, volume, veracity, variety

Computer vision

field of study that seeks to develop techniques to help computers "see" and understand content of Digital images ex: pics and videos It would be able to classify, verify, identify, detect, landmark detect, and recognize objects

rhizome identities locate identity in the ______, not the past, and begin with _______, not nouns

future; verbs

Examples of AI in action

image recognition, computer vision, robo journalists, language translations

Why using data as a strategic asset is difficult:

inconsistent, imcomplete, too little data not enough ppl with right skill set change management and resistance to use of data illegal/unethical issues from machine learning

Transparent data pools

information pool of data derived from explcity exchanges of personal info for services; explicit in the sense you that knowingly hand over personal details and you get a technological convenience; usually in the form of informed consent/terms of agreement

What are the benefits of using data warehouses?

informed decision making, consolidated data, historical data analysis, the data is quality, consistent, and accurate, and separation of analytics processing from transactional databases which improves performance of both systems

When is data an asset?

it can capture, store, and analyze data along with managing change and resistance, digitize and automating the buisness processes, and complement the other existing processes and tech that cant be digitized

Challenges with Databases

just because its collected doesnt mean it can be used as info, legacy systems (outdated and incompatible), most transactional databases not set up for large amounts of data, need to get data into systems that support analytics

Data lake

large amounts of raw; unstructured and structured data, a pool of data for free-form exploration often requires more specialized skills; often people request data from lakes to be extracted in more structured formats, some dont have data lakes but have warehouse or marts directly

Challenges of predictive analytics

large and comprehensive datasets, adaptibility of old models to new problems, data organization and hygiene, data privacy and security

data swamp

like a data lake but with unorganized files all over the place that leads you to dig through them and waste time

Artificial intelligence is created by computer programmers and software developers who apply what tools?

machine learning, deep learning, neural networks, computer vision, natural language processing

Examples of the application of analytics in buisness

marketing analytics, supply chain analytics, HR analytics, healthcare analytics, financial analytics, sports analytics

predictive analytics

more complex and trendy than descriptive analytics, many companies invest heavily in this technology.

object classification- object identification- object verification- object detection- object landmark detection- object recognition-

object classification-what category of object, dog or cat? object identification-what type of a given object is this picture, what kind of dog is this? object verification-is the object in this picture a cat? ex: CAPTCHA or face verification object detection-what are the objects in this pic? ex: cat, dog, human? object landmark detection-what are the key points in this object in the pic? ex: animated effects in picture or video calls object recognition-what objects are in this picture and where are they? ex: this is a coke can

Identity Prison

one isolated mistake in ones past, at one time, was something you could outgrow move away or out from, but now one episode could become escapable and you will be trapped with this mistake/identity forever

Transaction processing systems

point of sale systems, mobile apps, ecommerce

What form of analytics does insight match with? what are some examples of insight?

predictive analytics-data mining, regression analysis, time series, hazard, discriminant

Examples of Data Mining roots in AI

predictive test: predict next word in a sentence FaceID: 30,000 indiscernable infrared dots on your face to identify you, take face image, saves it

What form of analytics does foresight match with? what are some examples of foresight?

prescriptive analytics-optimization, simulation, decision modeling

Dilemma: we want both HIGH _________ and HIGH ___________

privacy; convenience

Data Mining

process of using computers to identify hidden patterns in, and to, build models from, large data sets; applied in: -customer segmentation (healthy eatsers vs junk food eaters), -market basket analyses (those who purchase product x also purchase product y) -fraud detection (uncovering patterns consistent with criminal activity) -hiring and promotion (ID characteristics consistent with employee success in the firms various roles

predictive modeling

process of using known results to create, process, and validate a model that can be used to forecast future outcomes-it analyzes fixed historical data to increase probability of a forecast event happening

Data analysts toolkil (buisness intelligence)

query tools, ex: excel and SQL Programming, ex: Python/R Statistics Data visualization tools: Tableau, PowerBI, Excel, Pivot Tables in Excel Planned Adhoc reporting tools Dashboards

Natural Language Processing

read, decipher, understand and make sense of human languages in a manner that is valuable applied in personal digital assistants like Alexa, Cortana, and Siri, Word processors (grammerly), translation devices/apps, ChatGPT, interactive voice response, Dalle2

An example of predictive analytics

recommendation systems—Netflix telling you what to watch! 75% of what consumers watch comes from recommender systems Preventative maintenance-predict when machines will need to be fixed/updated to be able to account for loss of machinery ex: finnish railway operator

Artificial Intelligence

references to the general ability of computers to emulate human thought and perform tasks in real world environments; used in prescriptive analytics

Predictive analytics practices

regression, neural networks, random forests

Rhizome-Identity response to big data identity threat

renders gathered data inapplicable by disassociating from the past; recognize your identity doesn't stem form what youve done in the past but also from what you WILL do in the future; we must continuously reform our tastes, aspiration, behaviors deep into us, then data platforms wont ahve enough info to predict us and data does not describe the person we are EFFORT AND LABOR IS NEEDED

effort and labor is needed to adapt the ____________ identity

rhizome

Rhizome personality/identity

rhizome: a continuously growing horizontal underground stem which puts out lateral shoots and adventitious roots at intervals. You want to be continuously growing and evolving, when you do this it makes it impossible for AI to predict where youre going/what you want and doesn't let big data keep hold of you; you want to adopt this identity when it comes to privacy versus convenience, this would be called being a dynamic person

Digital slavery

robs you of freedom of creating your own identify, it predicts what you want before you know you want it; who you are/what you want is determined by an app—so would we rather save on time and be convenienced or expend effort by browsing and not clicking suggestions

There are 3 responses to the big data identity threat:

surrender, reclusive, dynamic

Computer vision applications

tesla autopilot, healthcare, industry 4.0, plant care apps, retail

Privacy

the ability to control access to ourselves; ability to decide what remains secret and from whom

Prescriptive analytics

the most advanced and sophisticated more of data analytics, makes use of artificial intelligence (AI) and machine learning (ML) to tell you what you should do

Machine Learning

the technologies and algorithms that enable systems to identify patterns, make decisions, and improve themselves through experience and data; used in predictive and prescriptive analytics; subset of AI

How does data help gain competitive advantage?

theres no monopoly on math, but based on formula, algorithms, and data

How does amazon use descriptive analytics?

they anticipate shopper purchase and cut down on shipping time by starting the process of shipping products to users before they even make a purchase, leveraging past data, behavioral information, and finding patterns.

How do data warehouses work?

they contain multiple databases, within each data is organized in tables and columns and in each column you define a description of data, like integer, data field, or strings, Tables can be organized inside of schemas, which you can think of as folders, when data is ingested its stored in various tables described by the scheme and queery tools use the schema to determine which tables to access and analyze.

Dark Data Pools

third party vendors accumulate and manipulate information without consent from original providers; for example data traded from Tinder (romance), Enolytics (wine), and SYmptomChecker(health) may be purchased by a dat broker Acxiom, then combined with other purchased info before being resold to strategic merchants. By your activity they can see the lifecourse of finding someone, marrying them, and having a baby and then target you with adds the entire way and build an entire life profile

Data is created by...

transaction processing systems, enterprise software that capture operational data, and surveys and focus groups

What kind of data uses informed consent/terms of agreement, and what are the issues with these forms?

transparent data pools; people dont fully understand the extent of their exposure, they dont fully read agreement

What are soft skills required for a data analyst?

understanding goals and problem solving, analytical and critical thinking, presentation and communication skills, foundational knowledge in some particular buisness field

How does Big Data enable the dilemma of privacy versus convenience?

unites surveillance and artificial intelligence; amplified by technology and AI machines; one specific example is with CONSUMER TARGETING

just like Nozick's experience machine in the opium den

we are addicted to pleasure and convenience in data, just like drug addicts are, but you begin to lose your identity when those are provided for you, you dont get to adapt or grow your personal identity yourself instead a machine does this for you

Public data

weatlh, employment stats, gas prices, household income, name, address, SSN

how is data created?

well reputed organizations (ex: Census, BLS, NOAA) and public data

What does descriptive analytics tell us?

what happened and what is happening

Linear programming

what is the shortest route to deliver a package for each of the house using the least fuel? many variables to take into consideration like speed limits, traffic, time of day

What does predictive analytics tell us?

what will happen and why will it happen

Descriptive analytics gives insights on... W____, W_______, W__, and H__

what, when who, and how

What does prescriptive analytics tell us?

why should we do it

Biometric Data

you fingerprints, skin cells, hair, and saliva