Overview

There is an exponential growth in the volume, variety and velocity of data. We help you leverage the power of data and derive meaningful actionable insights. We have expertise in traditional as well as next-generation analytics. Our in-house data connectors, solution accelerators and big data integration capabilities enable faster data-driven decision making. 

Our Big Data solutions just don't offer frameworks, computing facilities and pre-packaged tools, but also help enterprises scale with cloud-based big data solutions such as Amazon Redshift, Amazon CloudSearch and Amazon Kinesis. 

Our offerings
We offer full lifecycle of Big Data services including POC, architectural consulting, data modelling, automation and preventive maintenance.

  • Big Data consulting and development

    We help businesses to determine their big data strategy and consult on improving the business performance uncovering the power of data. Our Big Data consulting includes POC/POV, technical recommendations, data source analysis, architectural consulting, capacity planning and much more.

  • Hadoop & Spark development

    We have deep expertise across Hadoop ecosystem (HDFS, Map Reduce, Hive, Flume, Sqoop, and Oozie) for building an integrated solution to gain meaningful and actionable insights. We also have deep expertise across Spark core, Spark Streaming, and Spark SQL components.We can help businesses with installation, architecture design, configuration and optimization & more. 

  • Cassandra development

    We provide development, consulting and training services on Apache and DataStax Enterprise Cassandra, including strategic planning & roadmap, data migration, and implementation of Cassandra in the data system. With our services, adding up data from multi-locations at high-speed comes handy.

  • Data visualization

    We have an expertise to capture data points and produce visuals and stories that generate high business impact. We enable faster, smarter, interactive and real-time data visualization with custom dashboards, reports, alerts, metrics, and scorecards. We have an in-depth understanding of various data visualization tools such as Tableau, Chart.js, Dygraphs and HighCharts to name a few.

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AWS Big Data Competency

The AWS Competency Program is designed to highlight competencies of APN partner. We offer full lifecycle of Big Data services and our technical proficiency and proven customer success have helped us to be one of the few AWS APN partners who could attain AWS Big Data competency.

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FAQs

Do you also have these queries?

  • What competencies do you have under Big Data domain? 

    We are proficient in Hadoop ecosystem (HDFS, Sqoop, Flume, Hive/Pig, Oozie etc.), Streaming & In Memory processing (Storm, Spark, Kafka), Enterprise Searching (Elasticsearch, Solr), NoSql Databases (MongoDB,Cassandra,Couchbase, Neo4J, Redis), Machine Learning (Mahout), Visualization (Tableau, R, D3.js, MS Excel) and Cloud Provisioning & Hosting Platforms (Amazon Web Services, Cloudera, Hortonworks). We have extensive experience in using Amazon services like Amazon EMR, Amazon Elasticsearch Service, Amazon RedShift, Amazon Kinesis etc.

  • Is your Big Data team certified?

    Our Big data team has Cloudera Certified Hadoop developers and Administrators, Amazon certified solution architects, MongoDB Certified Developers and DataStax certified developers and trainers.

  • Why should I use Hadoop? Does it provide real-time analytics?

    Apache Hadoop is an open source software project that enables the distributed processing of large data sets across clusters of commodity servers. It is designed for near linear scaling from a single server to thousands of machines, with a very high degree of fault tolerance. It is an ecosystem of multiple components which can be chosen depending upon requirements. Hadoop is primarily a distributed computation and storage platform for batch processing. It doesn’t provide real-time insights though there are a lot of solutions which can be integrated with existing Hadoop clusters to have real-time responsiveness.

  • How does Spark compare to Hadoop and which languages it support?

    Spark is a data processing engine compatible with Hadoop. It can perform real-time processing and has an ability to process data in Cassandra, HBase, Hive, HDFS and any Hadoop InputFormat. Spark can also run in Hadoop clusters through its own standalone mode or YARN. Spark supports Scala, Java, and Python.

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