Big Data has exploded onto the scene as a tremendous opportunity for companies to gain competitive advantage. However, these new technologies can be challenging to implement. So how do you get started with BigData Consulting and what are the factors to getting it right?
Eworks works with big industry leaders to develop their Big Data. Our years of experience in BigData technologies, Big Data patterns and designs, best practices, project templates, pre-built components and our deep understanding ensure your successful implementation of BigData technology at your organization.
Uncovering insights of data requires effective aggregation, integration, validation and gleaning techniques. It extends beyond change of technology landscape to include analytical processes, methodologies and workflows aimed at generating the right insights that accelerate real-time business value.
Eworks through big data consulting, enables organizations conceptualize and drive a well-thought-out big data program across multiple domains and focus areas. Our big data services help companies achieve the twin objectives of revenue maximization and increased operational efficiency. Our big data solutions provide organizations with the right customer insights on their cross sell and up-sell, helping them identify revenue leakages and fraud, thereby, driving profitability.
Programming Framework for Implementing BigData
Hadoop is an open source, Java-based programming framework that supports the BigData processing, storage and analytics in a distributed computing environment. Hadoop makes it possible to run applications on systems with thousands of commodity hardware nodes, and to handle thousands of terabytes of data.
Its distributed file system facilitates rapid data transfer rates among nodes and allows the system to continue operating in case of a node failure. This approach lowers the risk of system failure and unexpected data loss, even if a significant number of nodes become inoperative.
Consequently, Hadoop quickly emerged as a foundation for big data processing tasks, such as scientific analytics, business and sales planning, and processing enormous volumes of sensor data.
As a software framework, Hadoop is composed of numerous functional modules, Other components include:
- Hadoop Distributed File System (HDFS): It is capable of storing data across thousands of commodity servers to achieve high bandwidth between nodes.
- Hadoop Yet Another Resource Negotiator (YARN): It provides resource management and scheduling for user applications.
- Hadoop MapReduce: It provides the programming model used to tackle large distributed data processing, mapping data and reducing it to a result.
- Apache Flume: It is a tool used to collect, aggregate and move huge amounts of streaming data into HDFS.
- Apache HBase: It is an open source, nonrelational, distributed database
- Apache Hive: It is a data warehouse that provides data summarization, query and analysis
- Apache Oozie: It is a server-based workflow scheduling system to manage Hadoop jobs.
- Apache Phoenix: It is an open source, massively parallel processing, relational database engine for Hadoop that is based on Apache HBase.
- Apache Pig: It is a high-level platform for creating programs that run on Hadoop.
- Apache Sqoop: It is a tool to transfer bulk data between Hadoop and structured data stores, such as relational databases.
- Apache Spark: It is a fast engine for big data processing capable of streaming and supporting SQL, machine learning and graph processing.
- Apache Storm: It is an open source data processing system.
- Apache ZooKeeper. An open source configuration, synchronization and naming registry service for large distributed systems.
Eworks is the leader to provides BigData Consulting and Implementation services including Hadoop consulting, implementation and NoSQL based database implementation for multiple industries. We have a team of experts who have vast and wide area of knowledge in the field of BigData. Eworks offers following NoSQL Database implementation to get the benefits of BigData technology: