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E20-065 - Advanced Analytics Specialist Exam for Data Scientists - Dump Information

Vendor	:	EMC
Exam Code	:	E20-065
Exam Name	:	Advanced Analytics Specialist Exam for Data Scientists
Questions and Answers	:	66 Q & A
Updated On	:	October 30, 2017
PDF Download Mirror	:	E20-065 Brain Dump
Get Full Version	:	Pass4sure E20-065 Full Version

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E20-065 Questions and Answers

E20-065 Advanced Analytics Specialist Exam for Data Scientists Download Full Version : http://killexams.com/pass4sure/exam-detail/E20-065 QUESTION: 56 Which representation is most suitable for a small and highly connected network? A. Edge list B. Adjacency matrix C. Eigenvector centrality D. Adjacency list Answer: B QUESTION: 57 What is a characteristic of spark? A. Unable to run map -> reduce execution plans B. Supports applications written in Python, Java, and Scala C. Less efficient processing small files than Hadoop MapReduce D. Supports workflows that can return to previous work steps Answer: B QUESTION: 58 If two of the communities are re-designated to be one community, how does that change the network characteristics? Refer to the exhibit. A. Neighborhood overlap would increase B. Network diameter would decrease C. Modularity would increase D. Modularity would decrease Answer: B QUESTION: 59 What is the maximum degree of a node in an undirected graph with 50 nodes'? A. 49 B. 50 C. 1250 D. 2500 Answer: A QUESTION: 60 What best describes the meaning behind the phrase "Six Degrees of Separation'"? A. Ability to use about six hops to reach any other node in an extremely large social network B. Erdos number of all scholars having written papers with Paul Erdos C. Maximum number of edges between nodes in a graph with a diameter of six D. Typical distance between nodes that are connected by triadic closure Answer: A QUESTION: 61 What do first-order and second-order Markov processes have in common concerning next word prediction? A. Both use WordNet to model the probability of the next word B. Both are unsupervised methods C. Both provide the foundation to build a trigram language model D. Neither makes assumptions about the probability of the next word Answer: C QUESTION: 62 A marketing team creates a graph using a square for each data point, where the length of each side is set to the data value. The data values are 10 and 20. What is the lie factor of the graph? A. 1 B. 2 C. 3 D. 6 Answer: B QUESTION: 63 You are analyzing written transcripts of focus groups conducted on product X. You approach is to use TF-IDF for your analysis. What combination of TF-IDF scores should you examine to ensure you only report on the most important terms? A. High TF score and high DF score B. High TF score and high IDF score C. High TF score and low IDF score D. Low TF score and low DF score Answer: C QUESTION: 64 What does YARN provide over and above MapReduce? A. Separate cluster and resource management B. Parallelized processing C. Serialized processing D. Access to HDFS data Answer: A QUESTION: 65 What is an intended application of the MapReduce framework? A. Processing can be broken into smaller pieces B. Processing a large number of small files C. Processing in real time is required D. Processing a small subset of data Answer: A QUESTION: 66 What do lemmatization and stemming have in common? A. Use WordNet B. Remove common words in a natural language C. Reduce the high dimensionality in text D. Use a set of heuristics Answer: C 'PS .PSF FYBNT WJTJU IUUQ LJMMFYBNT DPN .LOO \RXU H[DP DW )LUVW $WWHPSW *XDUDQWHHG

EMC E20-065 Exam (Advanced Analytics Specialist Exam for Data Scientists) Detailed Information

E20-065 - Advanced Analytics Specialist Exam for Data Scientists

EMC Education Services

Data Scientist, Advanced Analytics Specialist Version 1.0 (EMCDS)

Certification Description

Proven Professional Website

Proven Professional Community

Certification Overview

This certification is designed to build on the skills developed in the Associate level course in Data Science (Data Science & Big Data Analytics) and help aspiring Data

Scientists continue to evolve and expand their skill sets. The main growth areas include advanced analytical methods, Hadoop (and Pig, Hive, HBase), Social Network Analysis, Natural Language Processing, and Visualization methods. The development

of these skills and the use of these methods provide the data scientist the ability to identify and communicate conclusions and recommendations in order to solve business challenges across many domains.

Certification Requirements

To complete the requirements for this certification you must:

Achieve the following Associate level certification:

Data Science Associate (EMCDSA)

Pass the following Specialist exam on or after May 1, 2015:

E20-065 Advanced Analytics Specialist Exam for Data Scientists

Note: These details reflect certification requirements as of May 1, 2015.

The Proven Professional Program periodically updates certification requirements.

*Please check the Proven Professional CertTracker website regularly for the latest information and for other options to meet the Associate level requirement.

EMC Education Services

E20-065 Advanced Analytics Specialist Exam for Data Scientists

Exam Description

Overview

This exam is a qualifying exam for the Data Scientist, Advanced Analytics Specialist certification.

This exam focuses on MapReduce, the Hadoop Ecosystem, NoSQL, Natural Language Processing, Social Network Analysis, Data Science Theory and Methods, and Data Visualization.

Duration

90 Minutes

(60 Questions)

Pass Score: 63

EMC provides free practice tests to assess your knowledge in preparation for the exam. Practice tests allow you to become familiar with the topics and question types you will

find on the proctored exam. Your results on a practice test offer one indication of how prepared you are for the proctored exam and can highlight topics on which you need to study and train further. A passing score on the practice test does not guarantee a passing score on the certification exam.

Exam Topics

Topics likely to be covered on this exam include:

MapReduce (15%)

MapReduce framework and its implementation in Hadoop

Practice Test

Exam - E20-065



Hadoop Distributed File System (HDFS) Yet Another Resource Negotiator (YARN)



Hadoop Ecosystem and NoSQL (15%)
Pig
Hive
NoSQL
HBase
Spark

Natural Language Processing (NLP) (20%)
NLP and the four main categories of ambiguity
TextPreprocessing Language Modeling



Social Network Analysis (SNA) (23%)
SNA and Graph Theory
Communities

Network Problems and SNA Tools



Data Science Theory and Methods (15%)
Simulation
Random Forests

Multinomial Logistic Regression and Maximum Entropy



Data Visualization (12%)
- Perception and Visualization Visualization of Multivariate Data

The percentages after each topic above reflects the approximate distribution of the total question set across the exam.

Recommended Training

Course Title	Course Number	Mode	Available
Advanced Methods in Data Science and Big Data Analytics	MR-1CP-ETAAMUSD	Instructor-Led	4/6/15
Advanced Methods in Data Science and Big Data Analytics - Video ILT	MR-1TP-ETAAMUSD-966	Video ILT-Stream	5/11/16
Advanced Methods in Data Science and Big Data Analytics - Online ILT	MR-1LP-ETAAMUSD	Online ILT	4/19/16

The following curriculum is recommended for candidates preparing to take this exam. Please complete one of the following courses

Note: These exam description details reflect contents as of May 1, 2015.

The Proven Professional Program periodically updates exams to reflect technical currency and relevance. Please check the Proven Professional website regularly for the latest information.

EMC2, EMC, EMC Proven, and the EMC logo are registered trademarks or trademarks of EMC Corporation in the United States and other countries. VMware is a registered trademark or trademark of VMware, Inc., in the United States and other jurisdictions. © Copyright 2015 EMC Corporation. All rights reserved. Published in the USA. 5/15 Exam Description

EMC believes the information in this document is accurate as of its publication date. The information is subject to change without notice.

References:

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