Big Data Training System (GT-BDAP7000)

Big Data Training System (GT-BDAP7000)

FEATURES :
  • GT-BDAP7000 is BigData Analytics Platform.
  • BDAP is a data acquisition required for the big data technology / processing / storage / analysis that provides both such as the software platform traditional high-end DW system compared to low TCO and the expected linear performance gain.
  • BDAP is the main key feature of Big Data Hadoop emerging as the global standard technology to standardize & provide the performance, reliability, ease of use and optimized for the enterprise environment. In addition to big data, ranging from installation, user training, technical support, user can minimize the trial and error at the time of big data adoption by provided all services.
  • BigData – for Structured data, Unstructured data
  • Next generation – for the advanced DW system
  • Hadoop Based Platform
  • All-in-one-platform

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Description

TRAINING CONTENTS :
BOOK 1 : BDAP, USER GUIDE

  • Overview
  • Getting Started with BDAP
  • Dashboard
  • Data Transfer 29
  • HFDS Browser
  • Workbench
  • Workflow
  • Document

BOOK 2 : BDAP INSTALLATION GUIDE

  • Overview
  • Preparation for the Installation
  • BDAP Installation
  • BDAP Delete
  • BDAP Upgrade
  • Appendix 1 & 2

BOOK 3 : BDAP ADMINISTRATION GUIDE

  • Overview
  • BDAP Operation
  • BDAP Web Interface
  • Interworking BDAP & R/RHive
  • HFDS Management
  • HBase Management
  • ZooKeeper Management
  • BDAP Configuration Setting

BOOK 4 : BDAP MONITORING GUIDE

  • Overview
  • Node General Metrics
  • Hadoop Metrics
  • HBase Metrics
  • ZooKeeper Metrics
  • Oozie Metrics
  • BDAP Monitoring View

BOOK 5 : BDAP API GUIDE

  • Overview
  • Preparations & Common in API
  • Data Transfer
  • HFDS Browser
  • Workbench
  • Workflow
  • Administration

BOOK 6 : TUTORIAL GUIDE

  • Overview
  • BDAP Practice Preparation
  • Data Collection (File to Hive)
  • Data Collection (Database to Hive)
  • Data Analysis
  • Exporting Data to an External RDB
  • Make Workflow
  • Create Schedule
  • Action Plan when Import/Export, Workflow is Failure

BOOK 7 : BDAP, ADVANCE COURSE

  • Big Data Analysis
  • Hadoop, Big Data Processing
  • DW, Hive
  • Hbase
  • BAP (Big Data Analytic Platform)
  • Analytical Methodology
  • Analytical Methodology
  • RCA Analytical Methodology
  • Unstructured Data Analysis

COMPONENTS :

HARDWARE (SERVER)

  • 6 Unit (HP DL360e Gen8 or Similar)

SOFTWARE PROGRAM

  • 6 Nodes
  • Management & Collecting Node : 2EA
  • Data Node : 3EA
  • Analysis Node : 1EA

MANUAL BOOK

  • 7 Books

SPECIFICATION

SYSTEM

  • A system that the Distributed Parallel Processing-based data collection, storage, processing, management
  • A system that the Distributed Parallel Processing-based the advanced analysis of R function
  • A system that supports the distributed parallel processing for data acquisition, storage, processing, analysis and supports Hadoop for data storage
  • Systems that support all Linux-based x86 servers without hardware dependencies

DATA COLLECTION

  • Remote log file collection function
  • Formal data collection (sqoop, etc.)
  • Unstructured data streaming collection function (Flume etc.)
  • Supports various types of unstructured data
  • Irregular multi-line data collection function
  • Parallel processing collection function for bulk loading
  • File data collection function with SSL / TCP
  • Import to HDFS, Import to Hive, Import to Hbase
  • User pre-confirmation with collection data preview function
  • GUI-based import / export of structured data
  • Agent and agentless data collection function
  • Data collection function through data transmission interval encryption (SSL)

DATA STORAGE & PROCESSING

  • Parallel distributed processing function of big data store
  • Storage features that integrate NoSQL and HDFS
  • Ability to process NoSQL and HDFS based on Hive (using SQL processing)
  • DB data processing function of repository data
  • Storage directory navigation
  • Supports data encryption / decryption of Storage Level (storage & inquiry)
  • GUI-based access control (ACL) processing and storage
  • Process design features for ETL processing
  • R linkage processing function for ETL processing
  • Data consistency check function in ETL processing
  • Support Collection target data mapping function (ETL)
  • Collection data processing / filtering function (ETL)
  • RDBMS interworking function of Oracle, MS-SQL, MySQL etc
  • Provides separate GUI (Workbench) Tool for SQL based processing
  • Unified SQL Engine that can process data in SQL-based
  • Multi-SQL processing in GUI
  • Provides extended UDF for various SQL processing
  • SQL-based DB, table access control processing function (grant processing function)
  • Provides GUI environment for SQL-based DB / Table / View creation
  • Ability to store big data processing results in HDFS, NoSQL, File, RDBMS, etc.
  • Scheduling function for distributed parallel processing jobs
  • GUI-based workflow for data management and batch processing
  • Branch, dependency add-on function in workflow
  • Provide Extension interface with external application / server on workflow

ADVANCED DATA ANALYSIS

  • Formal analysis and atypical analysis
  • Provides the distributed parallel processing for analysis of hundreds of millions of big data
  • Parallel distributed processing function based on SQL by linking R to Hive
  • Provides separate advanced analysis functions when execute Parallel distributed processing by linking with R to Hive
  • Provide a separate working area for analysts to use
  • Provides compatibility with various analysis / BI tools Including R for securing upgrading and expandability of analysis results.

BIG DATA PLATFORM H/W SPECIFICATION

  • Managed node & Collection node (2 EA)
  • Data node (3 EA)
  • Analysis node (1EA)
  •  Switch (2EA)
  •  Rack (1EA)
  • System installation and optimization support

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