Chapter 7 Study guide
A job _____ is a node in a Hadoop cluster that initiates and coordinates MapReduce jobs, or the processing of the data
tracker
In open source databases, the most important performance enhancement to date is the cost-based __________
optimizer
All of the following statements about MapReduce are truce except
MapReduce runs without fault tolerance
HBase is nonrelational _______ that allows for low latency, quick lookups in Hadoop
database
In the Alternative Data for Market Analysis or Forecasts case study, satellite data was NOT used for
monitoring indivudual customer patterns
A newly popular unit of data in the Big Data era is the petabyte which is
10^15 bytes
List and describe four of the most crtiical success factors for Big Data
A clear business need: there must be a valid reason for a business to invest in Big Data analytics that would result in financial benefits, not investing in it to try new technology Strong, committed sponsorship: It is difficult to succeed without this. Sponsorship for it can be at a department level Alignment between the business and IT strategy: The analytics work is always supporting business strategy. It should be helping the business be successful A strong data Infrastructure: This requires marrying the old with the new for a holistic infrastructure that works together
What is Big Datas relationship to the cloud?
Amazon and Google have working Hadoop Cloud offerings
How does Hadoop work?
It breaks up big data into multiple parts so each part can be processed and analyzed at the same time on multiple computers
What is NoSQL as used for big data? describe its major downsides
It is a style of the database that processes large volumes of multi-structured data. It is made for serving up discrete data stored in large volumes of data to end user and Big Data applications that are automated The downside is that many lack mature management and monitoring tools
Define MapReduce
It is a technique that was popularized by Google. It distributes the processing of very large multi structured data files across a large cluster of machines
Describe data stream mining and how it is used
It is the process of extracting novel patterns and knowledge structures from continous flows of ordered sequence of instances that can be read a small number of times using limited computing and storage
In the world of Big Data, ________ aids organizations in processing and analyzing large volumes of multistructure data. Examples include indexing and search, graph analysis
MapReduce
HBase, Cassandra, MongoDB, and Accumulo are examples of _____ databases
NoSQL
Which of the following sources is likely to produce Big Data the fastest?
RFID Tags
What are the differences between stream analyics and perpetual analytics? When would you use one or the other?
Stream analytics applies transaction level logic to real time observations Perpetual analytics evaluates every incoming observations against all prior observations, wehere this is not window size You would use stream analytics when the volume of transactions is high and the time to decision is short. For perpetual you would use when the volume is able to be managed in real time
Why are some portions of tape backup workloads being redirected to Hadoop clusters today?
They are being redirected to Hadoop clusters because of the difficulty to retrieve the data, it also takes a long time to retrieve it and data is often lost
There is a clear difference between the type of information support provided by influential users versus the others on Twitter
True
List and describe the three main "V's" that characterize big data
Volume: the amount of data being produced, social media, sensor data, and GPS data Variety: the different types of data, they can be structured, semi structured, or unstructured Velocity: How fast the data is being produced and how fast it is being processed
In a Hadoop "stack", what is a slave node?
a node where data is stored and processed
The problem of forecasting economic activity or microclimates based on a variety of data beyond the usual retail data is a very recent phenomenon and has led to another buzzword: ____
altnernative data
using data to understand customer/clients and business operations to sustain and foster growth and pofitability is
an increasingly challenging task for today's enterprises
In motion ___________ is often overlooked today in the world of BI and Big data
analytics
___________ bring together hardware and software in a physical unit that is not only fast but also scalable on an as-needed basis
appliances
In the financial services industry, Big Data can be used to improve
both A and B Regulatory oversight Decision making
As volumes of Big Data arrive from multiple sources such as sensors, machines, social media, and clickstream interactions, the first step is to ________ all the data reliably and cost effectively
capture
In the Analyzing Disease Patterns from a Electronic Medical Records Data Warehouse case study, what was the analytic goal?
determine differences in rates of disease in urban and rural populations
Hadoop is primarily a(n) ________ file system and lacks capabilities we'd associate with a DBMS, such as indexing, random access to data, and support for SQL.
distributed
In network analysis, what connects nodes?
edges
As the size and the complexity of analytical systems increase, the need for more __________ analytical systems is also increasing to obtain the best performance
efficient
Big data comes from__________
everywhere
In the Salesforce case study, streaming data is used to identify services that customers use most
falce
Big Data uses commodity hardware, which is expensive, specialized hardware that is custom built for a client or applicationq
false
Big data simplifies data governance issues, espeically for global firms
false
Hadoop and MapReduce require each other to work
false
In most cases, Hadoop is used to replace data warehouses
false
Which Big Data approach promotes efficiency, lower cost, and better performance by processing jobs in a shared, centrally managed pool of IT resources
grid computing
__________ speeds time to insights and enables better data governance by performing data integration and analytic functions inside the database
in database analytics
Allowing Big Data to be processed in memory and distributed across a dedicated set of nodes can solve complex problems in near real time with highly accurate insights. What is this process call?
in memory analytics
________ of data provides business value; pulling of data from multiple subject areas and numerous applications into repository is the raison d'etre for data warehouses
integration
The ____ Node in a Hadoop cluster provides client information on where in the cluster particular data is stored and if any nodes fail
name
In the Twitter case study, how did influential users support their tweets?
objective data
Big Data employs __________ processing techniques and nonrelational data storage capabilities in order to process unstructured and semistructured data
parallel
In a Hadoop "stack", what node periodically replicates and stores data from the Name Node should it fail?
secondary node
In the energy industry, _____________ grids are one of the most impactful applications of stream analytics
smart
Companies with the largest revenues from Big Data tend to be
the largest computer and IT services firms
Traditional data warehouses have not been able to keep up with
the variety and complexity of data
Current total storage capacity lags behind the digital information being generated in the world
true
Despite their potential, many current NoSQL tools lack mature management and monitoring tools
true
Dig Data is being drive by the exponetial growth, avaialbiilty, and use of information
true
For low latency, interactive reports, a data warehouse is preferable to Hadoop
true
Hadoop was designed to handle petabytes and exabytes of data distributed over multiple nodes in parallel
true
If you have many flexible programming languages running in parallel, Hadoop is preferable to a data warehouse
true
In application case 7.6 analyzing disease patterns from an electronic medical records data warehouse, it was found tha turban individuals have a higher numer of diagnosed disease conditions
true
In the opening vignette, the Access Telecom, built a system to better visualize custoemrs who were unhappy before they canceled their service
true
It is important for Big Data and self service business intelligence to go hand in hand to get maximum value from analytics
true
MapReduce can be easily understood by skilled programmers due to its procedural nature
true
Satellite data can be used to evaluate the activity at retail locations as a source of alternative data
true
Social media mentions can be used to chart and predict flu outbreaks
true
The quality and objectivity of information disseminated by influential users of Twitter is higher than the disseminated by noninfluential users
true
The term "Big Data" is relative as it depends on the size of the using organization
true
Under which of the following requirements would it be more approiate to use Hadoop over a data warehouse?
unrestricted, ungoverned, and sandbox explorations
What is the Hadoop Distributed File system designed to handle?
unstructured and semistructured non-relational sata
The _________ of Big Data is its potential to contain more useful patterns and interesting anomalies than "small" data
value proposition
Data flows can be highly inconsistent, with periodic peaks, making data loads hard to manage. What is this feature of Big Data called?
variability
Organizations are working with data that meets the three V's variety, volume, and __________ chracterizations
velocity
___________ refers to the comformity to fact: accuracy, quality, truthfulness, or trustworthiness of the data
veracity
When considering Big Data projects and architecture, list and describe five challenges designers should be mindful of in other to make the journey to analytics competency less stressful
Data integration: the ability to combine different types of data and to do so quick and cheap Data volume: being able to collect, store, and process the massive amounts of data at a good speed Processing capabilitites: being able to process the data that was captured quickly Data governance: being able to keep up with security, privacy, ownership, and quality issues Skills availability: it is being harnessed with new tools and looked at in new ways
List and briefly discuss the three characteristics that define and make the case for data warehousing
Data warehouse performance ,the cost based optimizer Integrating data that provides business value which answers business questions Interactive BI tools provide acess to data warehouse insights
In the opening vignette, why was the Telecom company so concerned about the loss of customers, if customer churn is common in that industry?
Even though it is common, they were losing customers at a very high rate which was concerning. They were hoping that by analyzing this trend they could control it and reduce the number of customers leaving
