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P2-Modulo 2 : Big data analysis y technology concepts
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Questions in this quiz (89)
1Text analytics generally involves two steps:
- AParsing text within documents to extract
- Bbased-content
- Ccategorization of documents using these extracted antities and facts
2Parsing text within documents to extract
- Anamed entities (person, group, place, company)
- Bpattern-based entities (social insurance number, zip code)
- Cprofile
- Dconcepts - an abstract representation of an entity
- EFacts - relationship between entities
3the extracted information can be used to perform a context-specific search on entities, based on the type of relationship that exists between the entities.
- Anatural language processing
- Btext analytics
- Csentiment analysis
4How can i identify cintracts that contain confidential company information?
- Anatural language processing
- Bsentiment analysis
- Ctext analytcs
5is a specialized from of text analysis that focuses on determining the bias o emotions of individuals
- Anatural language processing
- Bsentiment analysis
- Ctext analytics
6this form of analysis determines the attitude of the author by analyzing the text within the context of the natural language
- Atext analytics
- Bsentiment analysis
- Cnatural language processing
7sentimente analysis not only proveides information about how individuals feel, but also the intensity of their feeling
- ATrue
- BFalse
8sentiment analysis can be integrated into decision-making process
- ATrue
- BFalse
9common applications for sentiment analysis include early identification of customer satisfaction or dissatisfaction, gauging product success or failure and spotting new trends
- Asentiment analysis
- Bnatural language processing
- Ctext analytics
10which contestant is a likely winner of a singing contest
- Atext analytics
- Bsentiment analysis
- Cnatural language processing
11Correlation and regression are exmaple, A/B testing can make use of ________________ techniques for results comparision
- AQualitative analysis
- BQuantitative analysis
- CData mining
12NLP, text analytics and sentiment analysis can be used in suport of qualitative analysis
- Aquantitative analysis
- Bqualitative analysis
- Cdata mining
13can be carried out via the use of supported by correlation, heat maps, time series anlysis, network analysis, spatial data analysis, clustering, outlier detection, natural language processing and text analytics
- Adata mining
- BQuantitative analysis
- Cqualitative analysis
14A/B testing, heat maps and spatial data analysis are considered forms of ____________ analytics
- Aqualitative analysis
- Bdescriptive analytics
- Cdiagnostic analytics
15Correlation, regression, time series analysis, network analysis and spatial data analysis are considered forms of _____________ analytics
- Apredictive analytics
- BQualitative analysis
- Cdiagnostic analytics
16Correlation , regression, time series analysis, classification, clustering, outlier detection, filtering, natural language processing, text analytics and sentiment analysis
- Adescriptive analytics
- Bpredictive analytics
- Cdiagnostic analysis
17area based on predictive analytics techniques and therefore are associated wth the same analysis tecniques as predictive analytics. Additionally, may utilize heat maps, network analysis and spatial data analysis to graphically show various outcomes
- Apredictive analytics
- Bsupervised learning
- Cpreescriptive analytics
18Classification, outlier detection, filtering, natural language processing, text analytics and sentiment analysis
- Asupervised learning
- Bunsupervised learning
19clustering, outlier detection, filtering, natural language processing, text analytics and sentiment analysis can utilize unsupervised learning
- Aunsupervised learning
- Bsupervised learning
20is a tightly coupled collection of servers, or nodes. These servers usually have the same hardware specifications and are connected together via a network to work as a single unit
- Afile sistems & distributed file system
- Bclusters
- Ccloud computing
21Each node in the cluster has its own dedicated resources such as memory and harda drive, ans runs its own operating system just like a desktop computer
- ATrue
- BFalse
22_______________ is used to execute a task based on distributed/parallel data processing frameworks
- Afile systems
- Bswitch
- Ccluster
23is a method of storing and organizing data on a storage medium, such as hard drives. DVDs and flash drives
- Aclusters
- Bfile systems
- Cdistributed data processing
24Is an atomic unit os storage used by the file system to store data.___ are organized inside of a directory
- Afile
- Bclusters
- Cprocessing workloads
25provides a logical view of the data stored on the storage medium as a tree structure of files and directories
- Acluster
- BFile systems
- CFile
26Operating systems employ ____________ for data storage. Each operating system provides support for one or more file systems like ntfs for windows and ext for Linux
- AFile systems
- Bclusters
- CNoSql
27is a file system that can store large files spread across a cluster
- Afile systems
- BDistributed File System
- Ccluster
28to the client a file appears local and can be accessed via multiple locations
- ATrue
- BFalse
29is a non relational database that is highly scalable, fault-tolerant and specifically designed to house unstructured data
- Acluster
- BNoSQL
- Cfile systems
30________ database generally provides an API-based query interface, rather than the SQL interface
- Acluster
- Bfile systems
- CNoSQL
31Some NoSQL databases may also provide a SQL-like query interface
- ATrue
- BFalse
32involves the simultaneous execution of multiple sub-tasks that collectively comprise a larger tsk
- Adistributed fyle system
- Bparallel data processing
- Cdistributed data processing
33can be achieved through multiple networked machines, it is more typically achieved within the confines of a single machine
- ADistributed data processing
- Bparallel data processing
- Ccluster
34A task is divided into three sub-tasks that are executed in _____________ on three different processors within the same machine
- Adistributed file systems
- Bparallel Data processing
- CNoSQL
35is always achieved through physically separate machines that are networked together as a cluster
- Aparallel data processing
- Bdistributed data processing
- Cdistributed file systems
36__________ in big data is defined as rhe amount and nature of data that is processed within a certain amount of time
- Adistributed data processing
- Bprocessing workloads
- Cparallel data processing
37______are usually divided into two types:
batch
transactional- Adata
- Bworkloads
- Cfile systems
38Also know as oflifline processing, _______ workload processing involves processing data that usually imposes delays (resulting in high-latency responses)
- Abatch
- Btransactional
39typically involve large quantities of data with sequential read/writes and comprises a group of read or write queries
- Atransactional
- Bbatch
40Queries can be complex and involve multiple joins (OLAP systems commonly process workloads___________)
- Atransactional
- Bbatch
41strategic BI and analytics fall in this category, since they are highly read-intensive tasks involving large volumes of data
- Abatch
- Btransactional
42a batch workload comprises grouped read/writes, with a larger data footprint consisting of complex joins and high-latency responses
- ATrue
- BFalse
43Also know as online processing, transactional workload processing follows an approach whereby data is processed interactively, without delay (resulting in low-latency responses)
- Atransactional
- Bbatch
44involve small amounts of data with random read/writes
- Atransactional
- Bbatch
45OLTP and operational systems (write-intensive) as well as operational BI and analytics (read-intensive), both fall within this category
- Atransactional
- Bbatch
46Contain a mix of read/write queries, they are generalle more write-intensive than read-intensive
- Abatch
- Btransactional
47Comprise random read/writes that involve fewer joins and require low-latency responses, with a smaller data footprint
- Atransactional
- Bbatch
48is a specialized form of distributed computed that introduces utilization models for remotely provisioning scalable and measures IT resources.
- Acloud computing
- Bcluster
- Cprocessing workload
49Big data solutions can be partially or fully deployed in clouds in order to leverage the storage and computing resources that are available on cloud-based enviroments
- ATrue
- BFalse
50__________ batch -based data processing fully lends itself to the pay-per-use model __________. wich can reduce operational costs since a typical hadoop cluster size can range from a few to a few thousand nodes
- Ahadoop,cluster
- Bhadoop, cloud computing
- Chadoop, processing workload: tansactional
51Cloud computing make sense for enterprises already using cloud cmputing to reuse the cloud for their Big Data initiatives
- AIT already possesses the required cloud computing skills
- Bdata is processed interactively
- Cthe input data already exists in the cloud
52Migrating to the cloud is logical for enterprises planning to run analytics on datasets that are available via data markets as most data markets store their data in the cloud such as amazon S3
- ATrue
- BFalse
53provides the three ingredients required for a Big data solution: input data, computing and storage
- Acloud computing
- Bcluster
- CNoSql
54Big Data solutions require a _________________ enviroment that can accomodate large-scale data volumes, velocity and variety
- Acloud computing
- Bdistributed processing
- Ctransactional workload
55at minimun any given big data solution needs to contain the ______________, __________________and ______________ mechanisms in order to effectivelly process large datasets in support of the Big Data analysis lifecycle
- AProcessing engine
- Bfile systems
- Cstorage device
- Dresource manager
56provide the underlying data storage enviroment for persisting the datasets that are processed by Big Data solutions
- Aoricessing engine
- Bstorage device
- Cquery engine
57Can exist as a distributed file system or a database
- Aquery engine
- Bresource manager
- Cstorage device
58Can be used for persisting immutable data that is intended for streaming access or batch processing
- Adatabase
- Bdistributed file systems
59Can be used for structured and unstructured storage and read/write data acces.
- ADistributed file systems
- Bdatabase, such as NoSQL repositories
60Distributed file systems and databases are both ________ storage devcice mechanisms
- Aon-disk
- Bin-memory
61is responsible for processing data (usually retrieved from storage devices) based on pre-defined logic, in order to produce a result
- Astorage devices
- Bprocessing engine
- Cresource manager
62any data processing that is requested by the big data solution is fulfilled by
- Aprocessing engine
- Bstorage devices
- CQuery engine
63utilizes a distributed parallel programming framework that enables it to process very large amounts of data distributed across multiple nodes
- Astorage device
- Bprocessing engine
- Ccoordinate engine
64processing emgimes generally fall into two categories
- Abatch processing
- Bback-end processing
- Crealtime processing
65Whers can take anywhere from minutes to hours to complete. This type of processing engine is considered to have high latency
- Abatch
- Brealtime
66that provides support for realtime data processing with sub-second response times. This type of processing engine is considered to have low latency
- Abatch
- Brealtime
67acts a scheduler that schedules and priortitizes processing requests according to individual processing workload requirements
- Astorage devices
- Bresource manager
- Cprocessing engine
68essentially acts as a resource arbitrator that manages and allocates available resources
- Astorage devices
- Bprocessing engine
- Cresource manager
69enables data to be moved in or out of big data solution storage devices
- Astorage devices
- Bdata transfer engine
- Cresource manager
- Dprocessing engine
70Data needs to be imported before it cab be processed by the big data
- Adata transfer engine
- Bprocessing engine
- Cresource manager
- Dstorage devices
71A given data transfer engine may support either data ______ or __________function in wich case it can be further qualified
- Adata transfer ingress engine
- Bprocessing engine
- Cdata transfer egress emgine
72data transfer ingress and egress functionality can be further grouped into the following categories
- Aevent
- Bdataset
- Cfile
- Drelational
73________ data transfer ingress engines generally use a publish-subscribe model based on the use of a queue to ensure high reliability and availability
- Afile
- BEvent
- Crelational
74these engines may provide the agent-based processing of infligth data , wich enables various data cleansing and transformtion activities to be performed in realtime
- Aresource manager
- Bdata transfer engine
- Cprocessing engine
- Dstorage devices
75enable the substitution of data that is distributed across a range of sources residing in multiple systems outside of the Big Data solution
- Aresource manager
- Bdata transfer engine
- Cprocessing engine
- Dstorage device
76__________ may internally use a processing engine to process multiple large datasets in parallel
- Aresource manager
- Bdata transfer engine
- Cprocessing engine
- Dstorage device
77note that a workflow engine may provide integration with a data transfer engine to enable the automated import ans export data
- ATrue
- BFalse
78_____________mechanism abstract the processing engine from end -users by providing a front-end user-interface that can be used to query underlying data along with features for creating query execution plans
- Aresource manager
- Bquery engine
- Cstorage device
- Dprocessing engine
- Edata transfer engine
79Languages that are more familiar and easier to work with (such as SQL) can be used by non_technical users to perform ETL tasks and run ad hoc queries for data analysis activities
- Astorage device
- Bquery engine
- Cdata transfer engine
- Dresource manager
- Eprocessing engine
80common processing functions performes by a query engine include
- Aselect
- Bsum
- Cavg
- Dgroup
- Ejoin
- Fsort
81Can reduce development time and enables the manipulation of large datasets without the need to write complex programming logic
- Astorage device
- Bdata transfer engine
- Cprocessing engine
- Dquery engine
- Eresource manager
82is able to process adavanced statistical and machine learning algorithms in support of analytics processing requirementes including the idenification of patterns and correlations
- Astorage device
- Banalytics engine
- Cprocessing engine
- Ddata transfer engine
- Eresorce manager
- Fquery engine
83is employed when the comparatively simple data manipulation functions of a query engine are insufficient
- Astorage device
- Bprocessing engine
- Cdata tranfer engine
- Danalytics engine
- Eresource manager
- Fquery engine
84some propietary analytics engines also provide specialized data analysis features, such as text analytics and machine log analysis processing
- Adata transfer engine
- Banalytics engine
- Cresource manager
- Dquery engine
- Eprocessing engine
- Fstorage device
85the ability to query data and perform ETL operations via the query engine is useful for ad hoc data analysis
- Astorage device
- Bdata transfer engine
- Cworkflow engine
- Dresource manager
- Eprocessing engine
- Fquery engine
- Ganalytics engine
86provides the ability to desing and process a complex sequence of operations that can be triggered either at set time intervals or when data becomes availables
- Astorage device
- Bworkflow engine
- Cquery engine
- Danalytics engine
- Edata transfer engine
- Fresource manager
- Gprocessing engine
87A distributed big data solution that needs to run on multiple servers relies on the coordination engine mechanism to ensure operational consistency across all of the participating servers
- Aquery engine
- Bcoordination engine
- Canalytics engine
- Dresource manager
- Estorage device
- Fdata transfer engine
- Gprocessing engine
88Make it possible to develop highly reliable, highly available distributed Big Data solutions that can be deployed in a cluster
- Aworkflow engine
- Bcoordination engine
- Cresource manager
- Dquery engine
- Eanalytics engine
- Fstorage device
- Gprocessing engine
- Hdata transfer engine
89The coordination engine mechanism can also be used for the following purposes
- Ato support distributed locks
- Bcommon procesing include sum, avg, group by, join and sort
- Cto support distributed queues
- Dto establish a highly available registry for obtainin configuration
- Efor reliable asynchronous communication between process that are running on defferent servers
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- Fundamental Big Data Big Data I (carolina c) (Modulo 2) Quiz on P2-Modulo 2 : Big data analysis y technology concepts, created by Carolina Colorado on 06/03/2017.
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