Big Data Architecture

Big Data Architecture

Terabytes of data are being generated every minute by media, cloud storage, internet, smartphones, etc. and processing this volume of data has become a priority. This demands cost-effective, innovative forms of information processing for enhanced insight and decision making.

We have developed a custom Apache Spark framework which enables our client to process large volumes of data efficiently, along with organizing and producing actionable outputs. DataKare framework not only builds a robust big data platform but also significantly reduces development and implementation time.

DataKare Solutions has quality experience in designing and implementing big data analytics solutions in various sectors such as Health Care, Retail, Financial and Transportation, etc. We specialize in developing and using big data applications that solve the needs of next-generation advanced analytics by leveraging NOSQL and cutting edge big data technologies.

Our primary goal is to develop a big data solution that gives data scientists, businesses, and data analysts the ability to perform data mining, advanced analytics, and provide API endpoints to access/analyze the data in real-time. This subsequently optimizes operations for maximum efficiency, reduces risks, acquires new customers to improve sales and identify opportunities, etc

Technology Stack

  • Distributed storage system:

Hadoop HDFS, MAPR FS, Amazon S3, Azure Blob.

  • Data management:

Apache Cassandra, Azure CosmosDB, Amazon RedShift, Apache Hive, Apache HBase.

  • Data Science:

Spark Machine Learning Library (MLlib), Azure ML Studio, TensorFlow, Theano, Torch.

  • Data processing:

Apache Kafka, Apache Nifi, Apache Spark, Apache Storm, Hadoop MapReduce.

  • Programming languages:

Scala, Java, Python, R.

  • CI/CD Tools:

Jenkins, Git, TerraForms, Azure cloud Formation.

  • Other Big data tools:

Scoop, Apache Nifi, Talend, Apache PIG.