Big Data and Data Science Training Bangalore
Join for a job-oriented Big Data and Data Science Training Bangalore at SMEC Labs.
What is Big Data/ Data Science
Big data deals with complex data sets. The big data refers to a diverse set of information which grows at an ever-increasing rate. It encompasses 2 Vs and they are
- Volume – the volume of data matters
- Velocity – It is the rate at which the data is received and acted on.
- Variety – variety refers to the types of data which are available
Big data can be of either structured or unstructured format. The data of structured format is easy to get analyzed when compared with the unstructured data. The large chunks of data are collected, stored, processed and analyzed through various means and which can be used by various organizations across the globe to increase their efficiency. When it comes to data science, it can be defined as a multidisciplinary field that uses scientific techniques to extract information from both structured and unstructured data.
Why It’s Great To Make A Career Move In Data Analytics
- Big data is everywhere and therefore big data analytics is in the frontiers of IT
- An ocean of opportunities is waiting for those who are skilled in Big data analytics
- Evolving as one of the most promising career paths for skilled professionals
- Data is useless or waste without the skill to analyze it there comes the role of a big data analyst
- The soaring demand for skilled professionals boosts the wages for qualified experts in the industry.
- The big data analytics is one of the top priorities in most of the organizations.
- There is a wide variety of choices in job roles and types of analytics used like big data
- analyst, analytics associate, metrics and analytics specialist, etc.
How SMEC Bangalore help you?
Join for big data analytics courses in Bangalore at SMEC Labs. The course offered here is the most comprehensive data science learning program in the market. Looking for the best Big Data and Data Science Training Bangalore then you are in the right place. Having the pride of delivering more than 5000 skilled professionals to the industry, SMEC Bangalore makes a successful stand among other big data training institutes in the city. We are also providing internship programs to boost your productivity.
BIG DATA&DATA SCIENCE TRAINING SYLLABUS
- Limitations and Solutions of existing Data Analytics Architecture
- Hadoop Features
- Hadoop Ecosystem
- Hadoop 2.x core components
- Hadoop Storage: HDFS
- Hadoop Processing: MapReduce Framework
- Hadoop Different Distributions
- Hadoop 2.x Cluster Architecture
- Federation and High Availability
- A Typical Production Hadoop Cluster
- Hadoop Cluster Modes
- Common Hadoop Shell Commands
- Hadoop 2.x Configuration Files
- Single node cluster and Multi node cluster set up Hadoop Administration.
- Topics-MapReduce Use Cases
- Hadoop 2.x MapReduce Architecture
- YARN MR Application Execution Flow,
- Anatomy of MapReduce Program
- Input Splits
- Relation between Input Splits and HDFS Blocks
- MapReduce: Combiner & Partitioner
- Counters ,Distributed Cache
- MRunit, Reduce Join
- Custom Input Format
- Sequence Input Format
- Xml file Parsing using MapReduce.
- Hive Background
- Hive Vs Pig
- Hive Architecture and Components
- Metastore in Hive, Limitations of Hive
- Comparison with Traditional Database
- Hive Data Types and Data Models, Partitions and Buckets, Hive Tables(Managed Tables and External Tables), Importing Data, Querying Data, Managing Outputs, Hive Script, Hive UDF, Retail use case in Hive, Hive Demo on Healthcare Data set.
- Hive QL: Joining Tables, Dynamic Partitioning
- Custom Map/Reduce Scripts
- Hive Indexes and views Hive query optimizers
- Hive : Thrift Server, User Defined Functions, HBase: Introduction to NoSQL Databases and HBase, HBase v/s RDBMS, HBase Components, HBase Architecture, Run Modes & Configuration, HBase Cluster Deployment.
- HBase Data Model
- HBase Shell
- HBase Client API
- Data Loading Techniques
- ZooKeeper Data Model
- Zookeeper Service
- Zookeeper, Demos on Bulk Loading
- Getting and Inserting Data, Filters in HBase
- Apache Spark & scala
- What is Apache Spark
- Spark Ecosystem
- Spark Components
- Spark a Polyglot
- Why Scala
- MapReduce Vs Pig
- Programming Structure in Pig
- Pig Running Modes
- Pig components, Pig Execution
- Pig Latin Program, Data Models in Pig
- Pig Data Types, Shell and Utility Commands, Pig Latin : Relational Operators, File Loaders, Group Operator, COGROUP Operator, Joins and COGROUP, Union, Diagnostic Operators, Specialized joins in Pig, Built In Functions ( Eval Function, Load and Store Functions, Math function, String Function, Date Function, Pig UDF, Piggybank, Parameter Substitution ( PIG macros and Pig Parameter substitution ), Pig Streaming, Testing Pig scripts with Punit, Aviation use case in PIG, Pig Demo on Healthcare Data set.
- Flume and Sqoop
- Oozie Components, Oozie Workflow
- Scheduling with Oozie
- Oozie Co-ordinator
- Oozie Commands, Oozie Web Console
- Oozie for MapReduce
- PIG, Hive, and Sqoop, Combine flow of MR, PIG, Hive in Oozie, Hadoop Project Demo, Hadoop Integration with Talent.
Diploma in Bigdata and Data science
Data Science Course in Bangalore at SMEC labs – Key features