Big Data Infrastructure

With multiple big data solutions available, choosing the best one for your unique requirements is challenging. Pythian’s big data infrastructure services help enterprises demystify this process. Our big data architects, engineers, and consultants can help you navigate the big data world, and create a reliable, scalable solution that integrates seamlessly with your existing data infrastructure. From defining the strategy, to deploying and monitoring it, we’ll help you assess your needs, design your architecture, and build, deploy, and manage your solution–ensuring you get more from your data.

Each individual on Pythian’s big data team brings passion, insight, and knowledge. And as a team, that collective wisdom and vision have put Pythian at the forefront of the big data market.  Our top-calibre team comprises certified Hadoop experts, sought-after speakers, published authors, and frequent bloggers, who’ve never met a challenge they couldn’t solve. We’ve acted as trusted advisors to clients with sophisticated big data teams. We’ve filled knowledge gaps in our clients’ existing teams. We’ve been their team. Whatever your need, Pythian will get you there quickly.

Benefits of working with Pythian

  • Customize your big data solutions to suit your needs and requirements
  • Identify the best technologies and platforms to propel your business
  • Stay at the forefront of the emerging big data market with custom solutions
  • Drive performance without interrupting your day-to-day operations
  • Gain critical insights quickly to plan and execute strategies
  • Integrate seamlessly with your existing infrastructure to keep your business running smoothly
  • Develop a reliable, scalable big data platform that grows with your enterprise
  • Build your solution with the best tools, technologies, and expertise

Big Data Infrastructure Services

Continuous transformation and operational excellence

PLAN

  • Assess current technology environment
  • Identify potential use cases
  • Discuss desired big data outcomes
  • Recommend architecture and platform to support business needs
  • Create a detailed deployment plan
  • Discuss plans for future expansion of big data environment

IMPLEMENT

  • Review data source details and availability
  • Review data transformations needs
  • Define system architecture for big data
  • Deploy and configure big data technology components
  • Develop data models, data ingestion procedures, and data pipeline management
  • Integrate data
  • Pre-production health checks and testing

MANAGE

  • Hadoop 24X7 monitoring, alerting, and problems resolution
  • System optimization
  • Proactive and reactive monitoring
  • Continuous improvements
  • Performance tuning
  • Platform upgrades
  • Security configuration

Specializations

  • Hadoop distributions: Cloudera, MapR, Hortonworks, Amazon EMR
  • Apache Hadoop ecosystem: Hive, YARN, Pig, Hbase, Oozie, Azkaban, Mahout, ZooKeeper, Spark, and more
  • Hadoop security: Kerberos, Apache LDAP, Active Directory, encryption
  • Cloudera technologies: Cloudera Impala, Cloudera Search, Apache Sentry,Cloudera Manager
  • BI tools/visualization: Platfora, Tableau Software, and more
  • NoSQL databases: Apache HBase, Apache Cassandra, MongoDB
  • Data ingestion: Apache Kafka, Apache Flume, Apache Sqoop
  • Complex event processing: Apache Storm, Spark Streaming
  • Search engines: Apache Solr, Elasticsearch
  • ETL tools: Pentaho, Talend, SSIS, and DataStage
  • Cloud: AWS, Microsoft Azure, Google Cloud Platform
  • AWS tools: RedShift, DynamoDB, RDS, Kinesis, Data Pipeline, EMR, SQS, SNS, etc.
  • Google Cloud Platform: BigQuery, Dataflow, Compute Engine
  • Azure Machine Learning platform
  • Machine-learning products: Spark MLlib, Mahout, GraphLab, R, Python ecosystem

Team Member Certifications

  • Hortonworks Certified Developer
  • Cloudera Certified Administrator for Apache Hadoop
  • Cloudera Certified Developer for Apache Hadoop
  • MapR Certified Administrator
  • Certified Google Cloud Developer
  • Cloudera Champion of Big Data