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Big Data & Analytics NASSCOM Certification – Big Data Foundation Course by Digital Vidya

  • Velocity
  • Variety
  • Veracity
  • Volume
  • True
  • False
  • Fault Intolerant
  • Concurrent
  • Scalability
  • Centralized System
  • All of them
  • Each worker node has its own storage system in the Big Data Grid
  • There is only one worker node but multiple storage systems in the Big Data Grid
  • Both have master node
  • HDFS, MR, Hive, Pig
  • Heavy Distributed File System, Pig, MR, Solr
  • HDFS, Pig, MR, Solr
  • 2nd and 3rd Option
  • FMCG
  • Health Care
  • Finance
  • Manufacturing
  • All of them
  • ACID(Atomicity, Concurrency, Isolation, Durability)
  • ACID(Atomicity, Concurrency, Isolation, Durability)
  • ACID(Atomicity, Consistency, Integrity, Durability)
  • ACID(Availability, Consistency, Isolation, Durability)
  • ACID(Atomicity, Consistency, Isolation, Durability)
  • True
  • False
  • Business Monitoring, Optimization, Integrity; Data Monetization; Business Metamorphosis
  • Business Monitoring, Consistency, Integrity; Data Monetization; Business Metamorphosis
  • Business Monitoring, Optimization, Insights; Data Monetization; Business Metamorphosis
  • None
  • Discovery
  • Model Building
  • Requirement Gathering
  • Dashboard creation
  • True
  • False
  • Modern Data warehouses are built on Hadoop Distributed File Systems
  • RDBMS cannot co-exist with Hadoop technologies
  • Data warehouses cannot be built on Hadoop systems
  • Report tools can be directly used on Hadoop
  • AP – RDBMS
  • CP – MongoDB, HBase
  • CA – Cassandra, Dynamo
  • None of the above
  • YARN
  • HDFS
  • Tez
  • Spark
  • Oozie – Ambari
  • Zookeeper – Oozie
  • YARN – Zookeeper
  • Oozie – Zookeeper
  • Map Reduce
  • Spark
  • HBase
  • Mahout
  • HBase – Pig
  • Kafka – Hive
  • DRILL – STORM
  • Hive – KAFKA
  • 1.x Limited scaling till 4000 nodes – 2.x Better scalability up to 10000 nodes
  • Manual intervention is not needed in both as both have multiple NameNodes
  • 1.x Limitation in serving as platform for data-related activities – 2.x Can server as a platform
  • None stands
  • Master-NameNode
  • Slave-DataNode
  • NameNode
  • Client
  • Inferring global schema from local tables mapped to it
  • Given a global table, infer which local table it should be ingested into
  • Infer synonyms for data normalization
  • Detect duplication of records
  • Select * from Students where name like “_BAC”;
  • Db.Students.find({“name”:/.*BAC/})
  • Db.Students.findall({“name”:/.*BAC/})
  • None
  • Compute
  • Storage
  • Subscribe
  • Messaging
  • Can store all types of data
  • Highly Agile/flexible
  • Matured
  • All of above
  • HBase
  • Spark
  • YARN
  • None of the above
  • Distributed datasets
  • Immutable
  • Disabled for distributed computations
  • Enabled for distributed computations

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