Big Data Services

Big Data Managed Services

Harness big data analytics and big data tools to drive better business decisions

PetaBytz, we have the expertise in big data tools and processes to derive actionable insights from mountains of disparate data that enterprises collect each day. Our specialists have pioneered big data analytics solutions for leading organizations around the world and we offer complete services to help you harness the power of your big data.

These include the following: Big Data Analytics lab spread across multiple locations that focus on product evaluation and performance benchmarking Innovative industry-tailored frameworks to meet unique domain needs Domain specific KPI toolkits for Big Data Tools Business transformation through a mix of performance management and next-generation analytics Big Data Analytics academy that provides assistance to developers and architects as well as data scientists and advanced visualization specialists PetaBytz experts deliver big data and analytics services to help you strengthen your IT foundation and realize new possibilities that enable accelerated growth. PetaBytz helps organizations to improve operational efficiency and lower risk with enterprise data solutions

Benefits of working with Petabytz

  • 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 Stream processing architecture

The above diagram illustrates a big data stream processing architecture with sample technologies. The technology choices could be different based on various factors like cost, efficiency, open source, developer community, in-house, cloud ready, etc,. The stream processing process has 4 steps from capture to visualize:

Capture – Collection and aggregation of streams (in this case logs using Flume)
Transfer – Real-time data pipeline and movement (Kafka for real-time + Flume for batch)
Process – Real-time data processing (Spark) and batch processing on Hadoop using Pentaho
Visualize – Visualize real-time + batch processed data


  • 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
  • Data warehouse offload to Hadoop
  • 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, Bigtable, Cloud Pub/Sub, Cloud Storage, Cloud Dataproc, Cloud Dataflow, Cloud Dataprep
  • Azure Machine Learning platform
  • Machine-learning products: Spark MLlib, Mahout, GraphLab, R, Python ecosystem
  • Cloudera technologies: Cloudera Impala, Cloudera Search, Apache Sentry,Cloudera Manager
  • BI tools/visualization: Platfora, Tableau Software and more

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
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