[SOLVED] Bigdata&Analytics

I’m studying for my Computer Science class and need an explanation.

QUESTION 1

1. Exploiting the Big Data opportunities allow new data architectures, including the following:

   		business solutions, security measures, and performance measures.
   		business opportunities, security measures, and statistical measures.
   		analytic sandboxes, new ways of working, and people with new skill sets.
   		analytic footprints, performance measures, and people with new skill sets.

4 points

QUESTION 2

1. The Data Scientist may have a choice of a dozen or more attributes to use in the clustering analysis. It is more efficient to reduce the number of attributes to the extent possible. Too many attributes can ______________________

   		maximize the impact of the less important variables
   		Maximize the impact of the most important variables
   		minimize the impact of the less important variables
   		minimize the impact of the most important variables

4 points

QUESTION 3

1. Despite the benefits of Enterprise Data Warehouses and Business Intelligent, these systems tend to restrict the ________________________

   		be common for additional systems to emerge only critical data for analytic datasets
   		be uncommon for additional systems to emerge only complex data for analytic datasets
   		flexibility needed to conduct easy data analysis.
   		flexibility needed to perform robust or exploratory data analysis.

4 points

QUESTION 4

1. The following are different ways to evaluate a decision tree except:

   		Evaluate whether the splits of the tree make sense
   		plan for decision measurements and data validation
   		conduct sanity checks by validating the decision rules with domain experts
   		determine if the decision rules are sound

4 points

QUESTION 5

1. Vectors are a basic building block for data in R. The tests for vectors can be done using a generic function of a vector(). A simple R variables are actually vectors, therefore, a vector can only consist of ____________ in the ____________.

   		numeric, record
   		values, same class
   		numeric, same class
   		values, record

4 points

QUESTION 6

1. The R code uses some of the following generic functions except:

   		hist–, plot(), points(), summary()
   		hist(), ploting–, points(), summary()
   		hist(), plot(), points(), summary()
   		hist(), plot(), points–, summarize()

4 points

QUESTION 7

1. The R code uses summary() function to display ________________

   		history of the model
   		summary of the model
   		summary of the report
   		history of the report

4 points

QUESTION 8

1. What is the complexity of data types and structures?

   		When Big Data reflects the variety of data sources such as formats, structures, and digital traces for analysis.
   		When Big Data reflects the high velocity data, with rapid data ingestion and near real time analysis.
   		When Big Data reflects the thousands or millions of rows, Big Data can be billions of rows and millions of columns.
   		When Big Data reflects the only the whose scale, distribution, diversity, and timeliness of new technical architectures

4 points

QUESTION 9

1. The initial step of the Apriori algorithm is to identify the _____________________ by starting with each item in the transactions that meets the _________________________

   		frequent itemsets and predefined minimum support threshold
   		non-frequent itemsets and predefined minimum support threshold
   		frequent itemsets and undefined maximum support threshold
   		non-frequent itemsets and undefined maximum support threshold

4 points

QUESTION 10

1. After identifying a Cluster, it is always efficient to label the clusters in a__________________

   		numeric way
   		alphabetical way
   		descriptive way
   		alphanumeric way

4 points

QUESTION 11

1. Clustering is mainly an exploratory technique to discover hidden structures of the data, possibly as a guide to more focused analysis or decision processes. The k-means analysis can be used to identify objects in the video. Some examples of specific applications of k-means are __________________________

   		image processing, medical, and customer segmentation
   		image processing, data center, and customer segmentation
   		image processing, medical, and advanced analytical
   		image processing, data processing, and customer segmentation

4 points

QUESTION 12

1. In Phase 3 of Model Planning, the data science team identifies the correct models to apply to the data for _____________, _________________, and _________________in the data depending on the goal of the project.

   		regression, modeling, and matching events
   		regression, association, and matching events
   		clustering, modeling, and finding relationships
   		clustering, classifying, and finding relationships

4 points

QUESTION 13

1. The 7 roles that plays a critical part in a successful analytics project include the following:

   		Stakeholders, Project Sponsor, Project Manager, Business Intelligence Analyst, Database Administrator, Data Engineer, and Data Scientist.
   		Business User, Project Sponsor, Project Manager, Business Managers, Database Administrator, Data Engineer, and Data Scientist.
   		Business User, Project Sponsor, Project Manager, Business Intelligence Analyst, Database Administrator, Data Engineer, and Data Scientist.
   		Business User, Project Sponsor, Project Manager, Business Intelligence Analyst, Business Stakeholders, Data Engineer, and Data Scientist.

4 points

QUESTION 14

1. The Output of the classification should include class probabilities in addition to the _______________

   		class models
   		class labels
   		indentifcation labels
   		indentifcation models

4 points

QUESTION 15

1. A confusion matrix is a specific table layout that allows _______________________

   		data entry and performance of a classifier
   		data entry and system integration
   		visualization of the performance of a record
   		visualization of the performance of a classifier

4 points

QUESTION 16

1. As part of the discovery phase in Data Analytics Lifecycle, the team needs to assess the resources available to support the project. Therefore, the resources include the following

   		technology, tools, systems, data, and people.
   		technology, documentation, skills, , data, and people.
   		technology, tools, migration, data, and people.
   		technology, tools, systems, data, and Analytics

4 points

QUESTION 17

1. The success of a data analysis project requires a deep understanding of the data. It also requires a toolbox for mining and presenting the data. The summary() function is an example of a generic function. A generic function is a group of functions sharing the same name but behaving differently depending on the ____________and ___________________

   		number and arguments they receive
   		data and arguments of the data
   		number and arguments of the data
   		data and arguments they provide

4 points

QUESTION 18

1. Using a known input values, a linear regression model provides the expected value of the outcome variable but some uncertainty may remain in predicting any particular outcome. Therefore, a linear regression model is a _________________ one that accounts for the ______________ that can affect any particular _________________.

   		realistic, randomness, outcome
   		realistic, values, outcome
   		probabilistic, randomness, outcome
   		probabilistic, values, outcome

4 points

QUESTION 19

1. For data sources to be loaded into the data warehouse, data needs to be well _________________

   		complex, structured, and normalized with the appropriate data type definitions.
   		understood, unstructured, and normalized with the insufficient data type definitions.
   		understood, structured, and normalized with the appropriate score and metrics.
   		understood, structured, and normalized with the appropriate data type definitions.

4 points

QUESTION 20

1. The Data Analytics Lifecycle as an approach to managing and executing analytical projects described the six phase process in the followig order:

   		Discovery, Data preparation, Model building, Model planning, Communicate results, and Operationalize
   		Discovery, Data preparation, Model planning, Communicate results, Model building, and Operationalize
   		Discovery, Data preparation, Model planning, Model building, Communicate results, and Operationalize
   		Discovery, Data preparation, Model planning, Model building, Operationalize, and Communicate results

4 points

QUESTION 21

1. High-value data is difficult to reach and leverage. Therefore, Enterprise Data Warehouses(EDWs)are designed for ______________________________

   		decentrailized data management and prioritized after operational processes.
   		central data management, snapshot, and prioritized after operational processes.
   		central data management, reporting, and prioritized after operational processes.
   		decentrailized data management, reporting, and unprioritized processes.

4 points

QUESTION 22

1. The Phase 6—Operationalize Overview of Data Analytics Lifecycle requires the team to delivers the following:

   		preliminary reports, log results, code, and technical documents.
   		intial reports, log results, code, and technical documents.
   		initial reports, briefings, code, and final reports.
   		final reports, briefings, code, and technical documents.

4 points

QUESTION 23

1. Clickstream analysis relates to the analytics on data related to web browsing and user clicks, which is stored on the client or the server-side. Apart from market basket analysis, the association rules can be used for ______________________

   		promotional programs and clickstream analysis
   		machine analysis and clickstream analysis
   		integration systems and clickstream analysis
   		recommender systems and clickstream analysis

4 points

QUESTION 24

1. The process of validation and testing requires gathering the input and output rules. The process involves the use of one or more methods to validate the results in the sample dataset. The first approach in establishing a statistical measure includes:

   		confidence, lift, and leverage.
   		confidence, output, and leverage.
   		criteria, output, and leverage.
   		criteria, lift, and leverage.

4 points

QUESTION 25

1. Confidence measures the chance that X and Y appear together in relation to the chance X appears. Hence, confidence can be used to ______________________

   		identify the missing rules
   		identify the interestingness of the rules
   		measure the misisng rules
   		measure the interestingness of the critical rules