Use LEFT and RIGHT arrow keys to navigate between flashcards;
Use UP and DOWN arrow keys to flip the card;
H to show hint;
A reads text to speech;
269 Cards in this Set
- Front
- Back
|
Big Data.... |
Meets Big Science at CERN |
|
|
What are the three V's? |
Volume, velocity, and variety |
|
|
accumulating fast and processed fast |
velocity |
|
|
structured and unstructured |
variety |
|
|
What type of research does CERN do? |
Nuclear |
|
|
Three points for CERN |
generates tons of information sooo much data! cannot do it all themselves |
|
|
DOW... |
enhances reliability with advanced analytics |
|
|
Read online case |
do it. |
|
|
Read Opening Vignette Chapter 6 |
Do it. |
|
|
Challenge for DOW |
To turn data into knowledge that ensures the reliability of products, fosters innovation and informs decisions. |
|
|
Solution for DOW |
Thousands of Dow employees rely on JMP statistical discovery software to gain a competitive edge. JMP is used in many facets of Dow’s operations. |
|
|
Results for DOW |
As Dow transitions from a traditional manufacturer to a solutions provider, JMP has become an essential tool for analyzing and presenting data, sharing it in a collaborative process with colleagues and customers, and using it to project new initiatives |
|
|
Three points for DOW |
-been using jump and six sigma for a LONG time. -not in retail -not about CRM |
|
|
What is CERN? |
the European organization for nuclear research |
|
|
Why is CERN important for the world of science? (2) |
-has been instrumental in many key global innovations and discoveries in theoretical physics -operates the world's largest particle physics laboratory |
|
|
What is the essence of the data challenge at CERN? How significant is it? (3) |
-collisions occur 40 million times per second -CERN doesn't have the capacity to process all data -information discovery is a big challenge |
|
|
What was the solution for CERN? |
CMS's data management and workflow management created a system to provide the ability to search and aggregate information across this complex data landscape. |
|
|
How were the Big Data challenges addressed with this solution for CERN? |
Allows flexible data structures to be stored and indexed. |
|
|
What were the results for CERN? Do you think the current solution is sufficient? (4) |
-DAS is used 24 hours a day, 7 days a week -Performance has been outstanding. -Information lookup without this would've taken much longer -The Current solution is outstanding, but more improvements can be made. |
|
|
Most big data is... |
generated automatically by machines |
|
|
Big data means different things to people with... |
different backgrounds and interests |
|
|
Traditionally, BIG DATA = |
massive volumes of data |
|
|
Where does big data come from? |
Everywhere! |
|
|
What's new about big data? |
the definition and the structure of Big data constantly change. |
|
|
Two points for Big Data |
-it is a misnomer -it is more than just "big" |
|
|
What are the 6 v's that define Big Data? |
Volume variety velocity veracity variability value proposition |
|
|
What kind of system does CERN use? |
distributed server system |
|
|
Two points for volume |
-the most common trait of Big Data -big is a relative term |
|
|
Three points for variety |
-data today comes in all types of formats -ranges from traditional databases to hierachical data stores created by the end users and OLAP systems to text documents -80 to 85% of all data is in some sort of unstructured or semistructured format |
|
|
Three points for velocity |
-how fast data is moving and how fast it must be processed -the most overlooked characteristic of big data -reacting quickly enough to deal with velocity is a challenge to most organizations |
|
|
Three points for Veracity |
-refers to conformity to facts: accuracy, quality, truthfulness, or trustworthiness -term coined by IBM
|
|
|
Two points for Variability |
-data flows can be highly inconsistent with periodic peaks. -Ex: something is trending in social media
|
|
|
points for value proposition |
-big data contains more patterns and interesting anomalies than "small data" -greater insight and better decisions |
|
|
Read Case 6.1 Pg. 283 |
Do it. |
|
|
BigData Analytics... |
helps Luxottica Improvement its Marketing Effectiveness |
|
|
What is Luxottica case about? |
retail and fashion industry |
|
|
What does "big data" mean to Luxotica? (2) |
-includes everything they can find about customer interactions -see this as constituting a massive source of business intelligence |
|
|
What were the main challenges for Luxotica? (3) |
-there was a disconnect between data analytics and marketing execution. -their competitive posture and strategic initiatives were compromised -had an inability to act decisively and consistently on the different types of information generated by each retail channel |
|
|
What were the proposed solution and the obtained results for Luxotica? (3) |
-deployed the customer intelligence applicnce -helps Luxottica highly segment customer behavior and provide a platform and smart database for marketing execution systems -benefits include a 10% improvement in marketing effectiveness, identifying the highest valued customers, and the ability to target customers based on preferences and history |
|
|
Big data, by itself, regardless of the size, type, or speed is... |
useless |
|
|
Big data + big analytics = |
value |
|
|
With the _____ ___________, Big data also brought about ___ __________. |
value proposition big challenges |
|
|
Two points for value proposition and big challenges |
-effectively and efficiently capturing, storing and analyzing Big Data -new breed of technologies needed |
|
|
Big Data Consideration: You can't process the ______ of ____ that you want because of the limitations of your current platform. |
amount of data |
|
|
BDC: You can't include ___/_____________ ____ _______ because it ____ ____ ______ with the ____ _______ ______. |
new/contemporary data sources does not comply data storage schema |
|
|
BDC: You need to integrate data as _______ __ ________ to be current on your analysis. |
quickly as possible |
|
|
BDC: You want to work with a schema-on-demand data storage paradigm because of the _______ __ ____ _____ involved. |
variety of data types |
|
|
BDC: The data is arriving so fast at your organization's doorstep that your _____________ analytics platform cannot handle it. |
traditional |
|
|
Seven Critical Success Factors for Big Data Analytics |
1. a clear business need (alignment with the vision and the strategy 2. Strong, committed sponsorship (executive champion) 3. Alignment between the business and IT strategy 4. A fact-based decision-making culture 5. A strong data infrastructure 6. The right analytics tools 7. Right people with the right skills |
|
|
storing and processing the complete data set in RAM |
In-memory analytics |
|
|
placing analytic procedures close to where data is stored |
in-database analytics |
|
|
use of many machines and processors in parallel |
Grid Computing and Massively Parallel Processing |
|
|
combining hardware, software, and storage in a single unit for performance and scalability |
Appliances |
|
|
the ability to capture, store, and process the huge volume of data in a timely manner |
data volume |
|
|
the ability to combine data quickly and at reasonable cost |
data integration |
|
|
the ability to process the data quickly as it is captured |
processing capabilities |
|
|
Six challenges of big data analytics |
data volume data integration processing capabilities data governance skill availability solution cost |
|
|
Where can big data analytics be used? |
Everywhere |
|
|
Top 5 Investment Bank Achieves... |
Single source of the truth |
|
|
Big data... |
benefits different areas |
|
|
Read Application case 6.2 |
do it. |
|
|
How can Big Data benefit large-scale trading banks? |
potentially handle the high volume, variability and continuously streaming data that trading banks need to deal with. |
|
|
How did MarkLogic Infrastructure help ease the leverage of Big Data? |
MarkLogic was able to meet two needs: 1. upgrading existing Oracle and Sybase platforms and 2. compliance with regulatory requirements. There was better performance, scalability, and faster development for future requirements. Also able to eliminate the need for replicated database servers by providing a single server providing timely access to the data. |
|
|
What were the challenges for MarkLogic? |
the legacy system was not fast enough to respond to growing business needs and requirements. It was unable to deliver real time alerts to manage marker and counterparty credit positions in the desired timeframe |
|
|
What was the proposed solution for MarkLogic? |
Big data offered the scalability to address the problem. |
|
|
What was the obtained result for MarkLogic? |
a new alert feature, less downtime for maintenance, much faster capacity to process complex changes, and reduced operations costs |
|
|
What was the system for marklogic? |
system was old and disparate wanted an integrated system |
|
|
|
|
|
Five Communication characteristics for Big Data Technologies |
1. commodity hardware 2. scale-out and parallel processing 3. non-relational data storage 4. unstructured and semistructured data 5. advanced analytics and data visualization to convey insights to the end user |
|
|
Name three big data technologies |
MapReduce Hadoop NoSQL |
|
|
What does MapReduce do? |
distributes the processing of very large multi-structured data files across a large cluster of ordinary machines/processes |
|
|
What is the goal of MapReduce? |
achieving high performance with simple computers |
|
|
Who developed and popularized MapReduce? |
|
|
|
What is MapReduce good at? |
processing and analyzing large volumes of multi-structured data in a timely manner |
|
|
What are some example tasks for MapReduce? |
indexing the Web for search, graph analysis, text analysis, machine learning |
|
|
What is Hadoop? |
an open source framework for storing and analyzing massive amounts of distributed, unstuctured data |
|
|
Who originally created Hadoop? |
Yahoo |
|
|
Hadoop clusters run on inexpensive commodity hardware so... |
projects can scale-out inexpensively |
|
|
hundreds of contributors continuously improve the core technology |
open source |
|
|
MapReduce + Hadoop = |
Big Data Core Technology |
|
|
Three points for NoSQL |
a new style of database to store and process large volumes of unstructured, semistructured, and multistructured data can handle Big Data better than relational database technology |
|
|
What is hadoop a way to do? |
get the data |
|
|
Read Application Case 6.3 |
Do it. |
|
|
What's the deal with ebay? |
so big, they can't hold it in one place multiple data centers |
|
|
Why did eBay need a Big Data Solution? |
requires the ability to turn the enormous volumes of data it generates into useful insights for customers |
|
|
What was the challenge for eBay? |
was experiencing explosive data growth and needed a solution that did not have the typical issues associated with common relational database approaches. It also needed to perform rapid analysis on a broad assortment of the data |
|
|
What is the solution for eBay? |
A solution that incorporates a scale-out architecture that enables eBay to deploy multiple clusters across several different data centers using commodity hardware. |
|
|
What were the results for eBay? |
can more cost effectively process massive amounts of data at very high speeds. Serves a wide variety of new use cases, and its reliability and fault tolerance has been greatly enhanced |
|
|
one with the skills to investigate Big Data |
data scientist |
|
|
Data scientists have.... |
high salaries and very high expectations |
|
|
What are the three creativity skills that define a data scientist? |
curiosity and creativity Communication and interpersonal domain expertise, problem definition, and decision modeling
|
|
|
What are the three geek skills that define a data scientist? |
data access and management programming, scripting and hacking internet and social media/social networking technologies |
|
|
Read Application Case 6.4 |
Do it. |
|
|
Big Data and Analytics... |
in Politics |
|
|
What is the role of analytics and Big Data in modern day politics? |
can help predict election outcomes as well as targeting potential voters and donors, and have become a critical part of political campaigns. |
|
|
What are the challenges for politics? |
to ensure some sort of reliability in news media coverage of election issues |
|
|
What is the results for politics? |
an ever increasing use of Big Data analytics in politics, both by parties and candidates themselves and by the news media and analysts who cover them. |
|
|
Five Input Data sources for politics |
census data (population specifics, age, race, sex, income) election databases (party affiliations, previous election outcomes, trends and distributions) Market research (polls, recent trends, and movements) Social Media (Facebook, Twitter, LinkedIn, Newsgroups, Blogs) Web (in general) |
|
|
Four points for big data & analytics in politics |
predicting outcomes and trends identifying associations between events and occurences assessing and measuring the sentiments profiling (clustering) groups with similar behavioral patterns |
|
|
Four output goals for politics |
Raise money contributions increase number of volunteers organize movements mobilize voters to get out and vote |
|
|
What is the impact of Big Data on DW? |
Big Data and RDBMS do not go nicely together Will hadoop replace data warehousing/RDBMS? |
|
|
Two Use Cases for Hadoop? |
Hadoop as the repository and refinery Hadoop as the active archive |
|
|
Three Use Cases for Data Warehousing |
data warehouse performance integrating data that provides business value interactive BI tools |
|
|
place to house the data |
repository |
|
|
Read Application case 6.5 |
do it |
|
|
Dubin city council is... |
leveraging big data to reduce traffic congestion |
|
|
Is there a strong case to make for large cities to use Big Data Analytics and related information technologies? |
can be used to ease traffic problems create a better understanding of the traffic network
|
|
|
How can big data analytics help ease the traffic problem in large cities? |
They can help get a better sense of the "traffic health" by identifying traffic congestion in early stages. you can create a digital map of the city operators can drill down to see the number of buses delayed or en route can assist with future planning |
|
|
What was the challenge Dublin City was facing? |
the difficulty in getting a good picture of traffic in the city from a high-level perspective. |
|
|
What was the proposed solution for Dublin City? |
to team up with IBM research, and especially the smarter cities technologies center |
|
|
What was the result for Dublin City? |
gave operators the ability to see the system as a whole gave insight to the operators and managers Could now answer important questions
|
|
|
What is the dublin case about? |
about a way to reduce traffic congestion |
|
|
How to succeed with Big Data? (7) |
simplify coexist visualize empower integrate govern evangelize |
|
|
Perpetual analytics |
grab everything and save everything |
|
|
Analytic process of extracting actionable information... |
from continuously flowing/streaming data |
|
|
Why stream analytics? |
it may not be feasible to store the data, or may lose its value |
|
|
A typical smart grid application for stream analytics is... |
the entire supply power chain |
|
|
What is the biggest potential source of BIG data comes from pattern monitoring |
health services |
|
|
Seven stream analytics applications |
e-commerce telecommunication law enforcement and cyber security power industry financial services health services government |
|
|
Read Application Case 6.7 |
do it. |
|
|
Why is stream analytics becoming more popular? (2) |
time to action has become an ever decreasing value we have the technological means to capture and process the data while it is being created |
|
|
How did the telecommunications company in this case use stream analytics for better business outcomes? |
used stream analytics to improve their service delivery in the following areas: application troubleshooting, operations, compliance, and security |
|
|
What was the challenge for the telecommunications case? |
overwhelming to gather and view this data in one place, and to perform any diagnostics, or hone in on the real-time intelligence that lives in the machine generated data |
|
|
What was the proposed solution for telecommunications? |
decided to work with Splunk, one of the leading stream analytics service providers |
|
|
What was the solution for Telecommunications? |
helped them improve in application troubleshooting, operations, compliance, and security |
|
|
Read Chapter Seven opening Vignette |
do it. |
|
|
Oklahoma gas and electric employs... |
analytics to promote smart energy use |
|
|
What is the oklahoma case not about? |
the corporate levels |
|
|
Two points for oklahoma case |
smart meters want people to stay away from using energy at peak hours |
|
|
Why perform consumer analytics? |
helps a company's customers make better purchasing and usage decisions |
|
|
What is meant by dynamic segmentation? |
refers to real-time or near-real-time customer segmentation analytics that will enhance their understanding about individuals' responses to the price signals and identify the best customers to be targeted |
|
|
How does geospatial mapping help OG&E? |
an easy way to narrow down to the specific customers based on usage |
|
|
What types of incentives might the customers respond to in changing their energy use? |
smart hours plan: attractive summer rates for all hours other than 2-7 provides data to demand-responsive customers |
|
|
Three points for Geospatial analysis |
better granulating trying to get better going toward more and more personalization |
|
|
Three points for geocoding |
visual maps postal codes latitude and longitude |
|
|
Enables aggregate view or a large geographic area; poor granularity |
geocoding |
|
|
One point for Location based analytics |
integrate "where" into customer view |
|
|
used to capture, store, analyze, and maange the data linked to a location |
geographic information system |
|
|
What is the point of chapter seven? |
new technology |
|
|
Retailers - location + demographic details combined with other transactional data can help...(5) |
determine how sales vary by population level assess locational proximity to other competitors and their offerings assess the demand variations and efficiency of supply chain operations analyze customer needs and complaints better target different customer segments |
|
|
Three points for global intelligence |
U.S. Transportation Command Overlaying weather and environmental information not only done locally or domestically |
|
|
Six points for U.S Transportation Command |
1. track the information about the type of aircraft 2. maintenance history 3. complete list of crew 4. equipment and supplies on the aircraft 5. location of the aircraft around the world 6. well-informed decisions for global operations |
|
|
Read Case 7.1 |
do it. |
|
|
Great Clips employs _______ _________ to shave time in ________ _________ |
spatial analytics location decisions |
|
|
What is the great clips case trying to figure out? |
where to locate another great clips |
|
|
How is geospatial analytics employed at Great Clips? |
They use their solution to evaluate each new location based on demographics and consumer behavior data, aligning with existing Great Clips customer profiles and the potential revenue impact of the new site on the existing sites. |
|
|
What criteria should a company consider in evaluating sites for future locations? |
major criteria include potential customer base, demographic trends, and sales impact on existing franchises in the target location |
|
|
Four points for Sabre Airline Solutions' application |
traveler security geospatial enabled dashboard assess risks across global hotspots interactive maps
|
|
|
Two points for interactive maps |
find current travelers respond quickly in the event of any travel disruption |
|
|
What is the Sabre case about? |
re-routing correctly |
|
|
Two points for telecommunications companies |
analysis of failed connections of voice, data, text, or internet analytics can help determine the exact causes based on location and drill down to an individual customer to provide better customer service |
|
|
Many devices are... |
constantly sending out their location information |
|
|
data mining of location based data |
reality mining |
|
|
real-time location information = |
real time insight |
|
|
two points for Path intelligence |
footpath - movement patterns within a city or store how to use such movement information |
|
|
What is footpath doing? |
automatically tracking movement without any cameras recording the movement visually |
|
|
Analysis can help determine... |
the best layout for the store, shopping mall, or public transportation options |
|
|
Real expertise is... |
not just technology, but rather, ability to interpret data |
|
|
Is footpath legal? |
Yes |
|
|
Read Application case 7.2 |
do it. |
|
|
Quiznos targets... |
customers for its sandwiches |
|
|
quiznos... |
used platforms to analyze consumer location trails of mobile users based on geospatial data illustrates the trend of retail space where companies are looking to improve efficiency by employing more sophisticated predictive analytics in real-time |
|
|
What is Quiznos not about? |
People using newspaper coupons. It's about technology! |
|
|
How can location based analytics help retailers in targeting customers? |
can help to narrow the characteristics of users who are most likely to utilize a retailer's services or products |
|
|
One point for real time location intelligence |
targeting right customer based on their behavior over geographic locations |
|
|
Two points for Explosive growth of apps industry |
Directly used by consumers (not businesses) enabling consumers to become more efficient |
|
|
finding a taxi in new york |
Cab Sense |
|
|
Two points for CabSense |
Rating of street corners...interactive maps if for the customers to find the caps |
|
|
ParkPGH |
find a parking spot, but it's not just a parking space reporting app |
|
|
Read application case 7.3 |
do it |
|
|
A life coach... |
in your pocket |
|
|
How can location based analytics help individual consumers? |
If a user on a smart phone enters data, the location sensors of the phone can help find others in that location who are facing similar circumstances, as well as local companies providing services and products that the consumer desires |
|
|
How can smartphone data be used to predict medical conditions? |
an app can create a behavior profile compared with health data from the CDC smartphones have accelerometers and gyroscopes to measure jerk, orientation, and sense motion. Muscle motions may be used to predict the progression of disorders such as Parkinson's disease, as well as tracking exercise activities. |
|
|
How is ParkPGH different from a "parking space-reporting app"? |
capable of predicting future events algorithm uses data on current events around the area to predict an increase in demand for parking spaces later thus saving time |
|
|
One point for productivity |
Cloze - email in-box management |
|
|
one point for cloze |
intelligently prioritizes and categorizes emails |
|
|
The demand and the supply for consumer-oriented analytic apps are... |
increasing |
|
|
Are privacy concerns still important? |
YES |
|
|
What is web 2.0? |
all the new stuff on the web |
|
|
Five points for web 2.0 |
advanced web objective changing the web from passive to active redefining what is on the web as well as how it works companies are adopting and benefiting from it |
|
|
blogs, wikis, RSS, mashups, user-generated content, and social networks |
advanced web |
|
|
enhance creativity, information sharing, and collaboration |
objective |
|
|
Consumer is the one that creates the content |
Changing the web from passive to active |
|
|
Do we care where our data is stored? |
No |
|
|
A style of computing in which dynamically scalable and often virtualized resources are provided over the internet |
cloud computing |
|
|
To use cloud computing, users need not have... |
knowledge of, experience in, or control over the technology infrastructures in the cloud that supports them. |
|
|
utility computing, application service provider grid computing, on-demand computing, software-as-a-service |
cloud computing |
|
|
Two points for cloud computing |
cloud=internet related "as a services" infrastructure |
|
|
Two examples of cloud computing |
web based email web based general application |
|
|
Five points for web-based email |
stores the data Stores the software centralized hardware/software/infrastructure centralized updates/upgrades Access from anywhere via a web browser |
|
|
Two points for web based general application |
google docs, google spreadsheets, google drive amazon.com's web services |
|
|
What is cloud computing used in? |
e-commerce, BI, CRM, SCM |
|
|
Two points for Business Model |
pay-per-use subscribe/pay as you go |
|
|
_______-________ thinking is one of the fastest growing paradigms today. |
service oriented |
|
|
What is cloud computing moving toward? |
building agile data, information, and analytics capabilities as services |
|
|
optimization, data mining, text mining, simulation, automated decision systems |
service orientation + DSS/BI |
|
|
What is service orientation doing? |
helping to make things better |
|
|
Component based service orientation fosters |
reusability, substitutability, extensibility, scalability, customizability, reliability, low cost of ownership, economy of scale (not originality) |
|
|
Two points for data as a service |
accessing data "where it lives" enriching data quality with centralization |
|
|
Four points for information as a service |
information on demand goal is to make information available quickly to people, processes, and applications across the business provides a single version of the truth, make it available 24/7 and by doing so, reduce proliferating redundant data and the time it takes to build and deploy new information services |
|
|
Three points for Analytics as a Service |
Agile analytics AaaS in the cloud has economies of scale, better scalability and higher cost savings Data/text mining + big data --> Cloud Computing |
|
|
Five data/text mining + big data --> Cloud Computing points |
storage and access to big data massively parallel processing in-memory processing in-database processing resouce polling, scaling, cost and time saving |
|
|
Five points for new organizational units |
Analytics departments Restructuring Business Business Processes and Virtual Teams Job satisfaction Job stress and anxiety Impact on Managers' Activities/performance |
|
|
One point for analytics departments |
chief analytics officer, chief knowledge officer |
|
|
definition of business process reengineering |
a major restrucuring of organizational business processes with respect to changes in organizational culture and new information technology intiatives being undertaken by an organization |
|
|
Five points for research into managerial use of dss and expert systems found managers |
1. spent more of their time planning 2. saw their decision making quality enhanced 3. were able to devote less of their time fighting fires 4. spent less time in the office and more in the field 5. gained more power as they gained more information and analysis capabilities |
|
|
Five legal issues to consider |
what is the value of an expert opinion in court when the expertise is encoded in a computer? who is liable for wrong advice provided by an intelligent application? what happens if a manager enters an incorrect judgment value into an analytic application? Who owns the knowledge in a knowledge base? Can management force experts to contribute their expertise? |
|
|
What is privacy? |
the right to be left alone and the right to be free from unreasonable personal intrusions |
|
|
Four points for Privacy |
How much information is too much? Mobile user policy Homeland security and individual privacy recent issues in privacy and analytics |
|
|
data that exceeds the reach of commonly used hardware environments and/or capabilities of software tools to capture, manage, and process it within a tolerable time span |
Big Data |
|
|
information technology infrastructure (hardware, software, applications, and platform) that is available as a service, usually as a virtualized resources |
cloud computing |
|
|
a method of capturing, tracking, and analyzing streams of data to detect certain events (out of normal happenings) that are worthy of the effort |
critical event processing |
|
|
a new role of a job commonly associated with Big Data or data science |
data scientist |
|
|
the process of extracting novel patterns and knowledge structures from continously streaming data records |
data stream mining |
|
|
an open source framework for processing, storing, and analyzing massive amounts of distributed, unstructured data |
Hadoop |
|
|
a hadoop-based data warehousing-like framework originally developed by Facebook |
Hive |
|
|
a technique to distribute the processing of very large multi-structured data files across a large cluster of machines |
MapReduce |
|
|
members converse and connect with one another using cell phones or other mobile devices |
mobile social networking |
|
|
a new paradigm to store and process large volumes of unstructured, semistructured and multi-structured data |
NoSQL |
|
|
a hadoop based query language developed by Yahoo! |
pig |
|
|
data mining of location based data |
reality mining |
|
|
a term commonly used for extracting actionable information from continuously flowing/streaming data sources |
stream analytics |
|
|
the popular term for advanced internet technology and applications, including blogs, wikis, RSS, and social bookmarking |
Web 2.0 |
|
|
Big data means _________ ______ to people with different ___________ and __________. |
different things backgrounds and interests |
|
|
Big data exceeds the reach of commonly used ________ ___________ and/or capabilities of software tools to _______, ______, and _______ it within a _________ time span. |
hardware environments capture manage process tolerable |
|
|
Big data is typically defined by three v's: |
volume, variety, velocity |
|
|
MapReduce is a technique to distribute the processing of ____ _____ _____ _________ ____ files across a _____ _______ of machines. |
very large multistructured data large clusters |
|
|
Hadoop is an open source framework for __________, _______, and _________ massive amounts of distributed, unstructured data. |
processing storing analyzing |
|
|
____ is a Hadoop-based data warehousing-like framework originally developed by ________. |
Hive |
|
|
___ is a Hadoop-based Query language developed by ______. |
Pig Yahoo! |
|
|
NoSQL, which stands for Not only SQL, is a new ________ to store and process large volumes of....... |
paradigm unstructured, semi-structured, and multi-structured data |
|
|
____ ________ is a new role or job commonly associated with Big Data or data science. |
Data scientist |
|
|
Big data and data warehouses are _____________ (not competing) analytics technology. |
complementary |
|
|
As a relatively new area, the Big Data vendor landscape is __________ ____ _______. |
developing very rapidly |
|
|
______ _________ is a term commonly used for extracting actionable information from continuously flowing/streaming data sources. |
Stream analytics |
|
|
_________ ________ evaluates every incoming observation against all prior observations. |
Perpetual analytics |
|
|
________ _____ __________ is a method of capturing, tracking, and analyzing streams of data to detect certain events (out of normal happenings) that are worthy of the effort. |
Critical event processing |
|
|
Data stream mining, as an enabling technology for stream analytics, is the process of __________ _____ ________ and knowledge structures from ___________, _____ data records. |
extracting novel patterns continous rapid |
|
|
__________ ____ can enhance analytics applications by incorporating location information. |
Geospatial data |
|
|
Real-time location information of users can be mined to develop _________ _________ that are targeted at a ________ ____ in ____ ____. |
promotion campaigns specific user real time |
|
|
Location information from ______ ______ and ____ can be used to create profiles of user behavior and movement. Such location information can enable users to ____ _____ ______ with similar interests and advertisers to _________ _____ __________. |
mobile phones pdas find other people customize their promotion |
|
|
________ ______ _________ can also benefit consumers directly rather than just businesses. ______ ____ are being developed to enable such innovative analytics applications |
Location-based analytics Mobile apps |
|
|
___ ___ is about the innovative application of existing technologies. ___ ___ has brought together the contributions of millions of people and has made their ____, ________, and ________ matter. |
Web 2.0 WEb 2.0 work opinions identity |
|
|
____-_______ _______ is a major characteristic of Web 2.0, as is the emergence of social networking |
User-created content |
|
|
Large internet communities enable the sharing of content, including... |
text, videos, and photos, and promote online socialization and interaction |
|
|
Business-oriented social networks concentrate on ________ ______ both in one country and around the world. Business oriented social networks include _______ and ____.L |
business issues |
|
|
Cloud computing offers the possibility of using ________, ________, _______, and ____________, all on a _______-_________ basis. Cloud computing enables a more scalable investment on the part of a user. |
software hardware platform infrastructure service-subscription |
|
|
Cloud-computing--based BI services offer organizations the ______ ___________ without ___________ ________ __________. |
latest technologies significant upfront investment |
|
|
Analytics can affect organizations in many ways, as _____-_____ _______ or integrated among themselves, or with other _________-_____ __________ ________. |
stand-alone systems computer-based information systems |
|
|
The impact of analytics on individuals varies, it can be.... |
positive, neutral, or negative |
|
|
_______ _____ ______ may develop with the introduction of intelligent systems; ________ and ________ are the dominant problem areas. |
serious legal issues liability privacy |
|
|
Many _______ _______ ____________ can be expected from analytics. These range from providing opportunities to disabled people to leading the fights against terrorism. _______ of ____, both at work and at home, is likely to improve as a result of _________. Of course, there are also ________ ______ to be concerned about. |
positive social implications quality of life analytics negative issues |
|
|
The analytics industry consists of many different types of ____________. |
stakeholders |
|
|
READ 6.1 REVIEW |
DO IT |
|
|
READ 6.2 REVIEW |
DO IT |
|
|
READ 6.3 REVIEW |
DO IT |
|
|
READ 6.4 REVIEW |
DO IT |
|
|
READ 6.5 REVIEW |
DO IT |
|
|
READ 6.6 REVIEW |
DO IT |
|
|
READ 6.7 REVIEW |
DO IT |
|
|
READ 7.1 REVIEW |
DO IT |
|
|
READ 7.2 REVIEW |
DO IT |
|
|
READ 7.3 REVIEW |
DO IT |
|
|
READ 7.4 REVIEW |
DO IT |
|
|
READ 7.5 REVIEW |
DO IT |
|
|
READ 7.6 REVIEW |
DO IT |
|
|
READ 7.7 REVIEW |
DO IT |
|
|
READ 7.8 REVIEW |
DO IT |
|
|
READ 7.9 REVIEW |
DO IT |
