BIG DATA SOLUTION DATA SHEET

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1 BIG DATA SOLUTION DATA SHEET

2 Highlight. DATA SHEET HGrid247 BIG DATA SOLUTION Exploring your BIG DATA, get some deeper insight. It is possible! Another approach to access your BIG DATA with the latest technology, Hadoop Distribute applications across clusters of commodity hardware using MapReduce technique Large scaled distributed file system with unlimited scalability Highly fault tolerant and designed to be deployed on low cost hardware A proven framework implemented by large social media such as Google, Amazon, Facebook and Zynga It is difficult to develop real world applications. Not anymore, HGrid247 make it much easier HGri247 is Hadoop grid workflow designer created by Solusi247 with readyto use ETL library No coding or less coding experience to generate MapReduce code Now, transaction data is too big for a traditional data warehousing. Large social media, such as Google, Amazon, Facebook and Zynga have implemented an open source framework, Hadoop, to manage their data. It spans an arc from that sort of starting point to the enterprise to pick up Hadoop and use it as an alternative to the traditional data warehousing. In 20o4, Google described an architecture called MapReduce to support their query engine and Yahoo started an open source development project under Apache to bring the MapReduce forward. And created a distributed file system to support it called Hadoop Distributed File System (HDFS). And rather than take the conventional step of moving data over a network to be processed by program, MapReduce uses a smarter approach tailor made for big data sets. MapReduce moves the processing program to the data.

3 DATA SHEET Hadoop has become a mainstream for Big Data solution. Many big vendors like Oracle, IBM, Teradata, HP, Microsoft, and others have been busy adopting and implementing this technology into their offering stack. Hadoop has capabilities to be implemented as processing resource, storage or both at the same time. It scales up to tens of thousands of nodes, almost unlimited and processed peta bytes of data easily. Hadoop lets you store files bigger than what can be stored on one particular node or server. So you can store very, very large files. It also lets you store many, many files. HGrid247 Big Data Solution is an experiences based solution of Big Data. For more than a decade we plunge into large scale data processing of telco transaction data. HGrid247 Workflow Designer is application tool to generate MapReduce code with no or less coding experience required. Data Monitoring is an application to monitor the trend of data processing result. Hadoop is quite complex to use, thus we are creating tool to make the hadoop implementation much easier called HGrid247 Workflow Designer as part of HGrid247 Big Data Solution. HGrid247 Workflow Designer

4 DATA SHEET Features Drag and drop workflow design and visualization Ready to use ETL library: Transformator Converter Aggregator Combiner Join Group by Filter Duplicate check Ready to use workflow library: Pipe Splitter Buffer Merger PMML Check point Sequence workflow Custom library editor Basic Statistic and Data Mining Library Source and Sink Library Hadoop file system JDBC Executable map reduce generator Audit log counter process Performance optimization HGrid247 Workflow Designer. A graphical user interface designer that will ease the workflow design and implementation in Hadoop. HGrid247 Workflow Designer is provided by a comprehensive set of ETL functions, data preparation and predictive modeling library. HGrid247 Workflow Designer is built on top of cascading framework. Cascading is created in late 2007 as a new java API to implement functional programming for large data workflows. Cascading is a pattern language for enterprise data workflows which is simple to build, easy to test and robust in production.

5 DATA SHEET Benefits Develop and test code from any development environment including from PC or Laptop Easy deployment to Hadoop Grid Cluster Additional functions is easily written and added as UDF in Java (simple and easy, not necessary to learn any new language/ script) Help organization accelerating time to value by reducing complexity in big data implementation

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