Enterprises have long realized the value of converging and analyzing business, user, and machine activities across diverse organizational functions and systems. However, this has only been partially leveraged, thereby limiting its applicability to more tangible, function-specific analytics or purpose-specific reporting. This approach has worked acceptably so far, and traditional reporting and analytics systems have served the purpose reasonably well. However, as businesses enter today’s highly complex, competitive, and rapidly evolving marketplace, the need for cross-domain analysis and decision-support systems operating across converged data sources and cutting across extremely large and varied data sets in near-real time has become an imperative in an increasingly growing number of scenarios. Traditional technologies are not designed to handle well and if applied, present a weak cost-value proposition, posing a challenge to businesses.
Hadoop and a supporting ecosystem of complementing technologies, building blocks, and implementation frameworks today provide one of the most powerful, mature, and compelling answers to problems in this domain. The true power of the Hadoop stack lies in it being a complete solution, covering the entire life cycle needs of applications including data collection, web-scale storage, data curation and organization, massively parallel processing, statistical and analytical tooling, integrative, visualization, and reporting tooling. All of this is made possible at costs that make sense in today’s highly constrained economic environment.
As a specialized solution and consulting services provider, AXNIIT expertise covers an array of relevant tooling, frameworks, and building blocks. Our pre-verified and gaps-addressed core Hadoop frameworks remove the guesswork out of the implementation. Our HPC-grade Hadoop cluster serves as a prototyping sandbox, so you can take the logistics for granted and focus on the core business problem, experiment with the technology, and develop an appreciation for its value to business quickly and definitively before you go all out . And, when you are ready to move on, our solution and deployment expertise across Hadoop distributions in varied deployment models ensures you have a smooth transition. Experience Hadoop at AXNIIT!
Hadoop dossier
Dedicated Hadoop practice—part of a focused Cloud Computing CoE
Dedicated Hadoop Sandbox cluster: More than 70-node cluster
Comprehensive expertise: data aggregation, storage, parallel processing, analytics, data visualization, and machine learning
Hadoop-focused QA: comprehensive big data verification, cluster benchmarking, and performance-tuning expertise—methodology, tooling, and practices
Hadoop RIM: trained and certified Hadoop administration staff
Partnership with industry leaders: AWS, Cloudera, and VMware
Extensive expertise in BI, data warehousing, and VLDBS
Expertise in consulting, implementation, migration, and administration
Research focus: R&D, application frameworks, security, and best practices
Platform expertise
Data aggregation and storage
Distributed log processing: Flume, Scribe, and Chukwa
NoSQL databases: MongoDB, Cassandra, HBase, and Neo4j
Raw distributed storage: HDFS, Amazon S3, Azure Storage, and Walrus
Parallel processing
Hadoop core: Apache Hadoop, Cloudera Hadoop, and Amazon EMR
Coordination infrastructure: Apache ZooKeeper
Workflow frameworks: Cascading and Oozie
Analytics and data visualization
ETL solutions
Data warehousing: Sqoop, Hive, Pentaho, SSRS, Cognos, and QlikView
Ad hoc query: Pig and Hive
Analytics database: Netezza, Vertica, and Greenplum
Machine learning: Apache Mahout
Test expertise
Focused team: dedicated QA Architect and Big Data Test team
Comprehensive Hadoop solution test coverage: Platform layer, Application layer, and cluster infrastructure
Specialized test methodology: purpose-engineered statistical test methodology for big data solution verification
Performance tuning specialization: performance benchmarking and cluster performance tuning expertise (TeraSort, Rumen, GridMix, and Vaidya)
Administration and cluster management
Hadoop deployment: configuration management, deployment, upgrades, and data set management
Hadoop monitoring: Hadoop Metrics, Ganglia, Cloudera Manager, and CloudWatch (AWS)
Hadoop managing: rack awareness, scheduling, and rebalancing
Trained and dedicated Hadoop administration team
Expertise in: Apache Hadoop, Cloudera Hadoop, and Amazon EMR
