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There are a wealth of physical objects—devices, vehicles, buildings and other items (embedded with electronics, software, sensors, and network connectivity) that businesses rely on to collect and exchange data. However, the objects that can be sensed and controlled remotely across existing network infrastructure which executives can access are often limited or not available in the time or format needed to offer a complete picture. The opportunities for more direct integration of the physical world into computer-based systems are increasing.

Our MapReduce ETL solutions bring sensors and actuators together. We employ technologies such as smart grids, smart homes, intelligent transportation and smart cities. Each object is uniquely identified through its embedded computing system but is able to interface within the Apache Hadoop infrastructure. We have developed a comprehensive MapReduce ETL solution set, which is aligned with Apache Hadoop and Eclipse IoT to ensure that the right semantic web is delivered using the Internet Protocol Version 6 (IPv6). Our solutions use a flexible, multi-purpose Apache Hadoop platform that extracts, translates, and locates multiple IoT sources of unstructured data into the Hadoop Distributed File System (HDFS).

Enterprise MapReduce has developed a portfolio of Eclipse IoT related Apache Hadoop capabilities that optimizes the true value of MapReduce ETL. We are experts in delivering Enterprise IoT with the MapReduce ETL Solution Set. We provide Enterprise IoT services in the following markets:

  • Media
  • Environmental monitoring
  • Infrastructure management
  • Manufacturing
  • Energy management
  • Medical and healthcare systems
  • Building and home automation
  • Transportation
  • Large scale deployment

The Methodology

  • Strategy Design: MapReduce ETL and Enterprise IoT analysis to optimize operational performance and strategy design to improve in-house capabilities.
  • Proof-of-Concept: Prototype MapReduce ETL models to support Enterprise IoT operations and define detailed requirements and design.
  • Model Build and Deployment: MapReduce ETL implementation of interfaces to Enterprise IoT operational systems.
  • Process Outsourcing: Business reporting, MapReduce ETL refresh and Enterprise IoT model management outsourcing and solutions hosting.
  • Operational Support: Support for existing Eclipse IoT model deployments and in-house IoT operations.

For MapReduce ETL solutions contact us at sale@enterprisemapreduce.com and we will help you with your MapReduce ETL solutions implementation and/or customization services.

MapReduce ETL on the Hadoop IoT Cloud

MapReduce ETL on the Hadoop IoT Cloud

MapReduce ETL can be deployed in a traditional onsite data center as well as in the Hadoop IoT cloud. The Hadoop IoT cloud allows organizations to deploy MapReduce ETL without needing to acquire hardware or specific setup expertise. MapReduce ETL supports the following Hadoop IoT hosted cloud platforms:

  • IBM BigInsights on Cloud – BigInsights is an industry standard Apache Hadoop offering that helps enterprises cost-effectively manage and analyze Apache Hadoop. BigInsights on Cloud provides managed operations, 24/7 monitoring, and IBM Open Platform with current and stable Apache Hadoop components.
  • Microsoft Azure HDInsight – Azure HDInsight is a service that deploys Hadoop on Microsoft Azure. HDInsight uses Hortonworks HDP and was jointly developed for HDI with Hortonworks. HDI allows programming extensions with .NET (in addition to Java). HDInsight also supports creation of Hadoop clusters using Linux with Ubuntu. By deploying HDInsight in the cloud, organizations can spin up the number of nodes they want and only get charged for the compute and storage that is used. Hortonworks implementations can also move data from the on-premises datacenter to the cloud for backup, development/testing and bursting scenarios. It is also possible to run Cloudera or Hortonworks Hadoop clusters on Azure Virtual Machines.
  • Amazon Elastic MapReduce – Amazon Elastic MapReduce (Amazon EMR) is a web service that makes it easy to quickly and cost-effectively process vast amounts of data. Amazon EMR simplifies Apache Hadoop processing, providing a managed Hadoop framework that makes it easy, fast and cost-effective for you to distribute and process vast amounts of your data across dynamically scalable Amazon EC2 instances. You can also run other popular distributed frameworks such as Apache Spark and Presto in Amazon EMR and interact with data in other AWS data stores such as Amazon S3 and Amazon DynamoDB.
  • CenturyLink Cloud (CLC) – CenturyLink Cloud offers Hadoop via managed and un-managed models using their Hadoop offering. CLC also offers customers several managed Cloudera Blueprints, the newest managed service in the CenturyLink Cloud Apache Hadoop Blueprints portfolio, which also includes Cassandra and MongoDB solutions.
  • Google Cloud Dataproc – Google Cloud Dataproc offers a managed Hadoop MapReduce, Spark, Pig, and Hive service, to easily process Apache Hadoop sets at low cost. Control your costs by quickly creating managed clusters of any size and turning them off when you’re done. Cloud Dataproc integrates across Google Cloud Platform products, giving you a powerful and complete data processing platform.

For MapReduce ETL solutions contact us at sale@enterprisemapreduce.com and we will help you with your MapReduce ETL solutions implementation and/or customization services.

MapReduce ETL & IoT Standards

MapReduce ETL & IoT Standards

MapReduce ETL provides solutions for building inter-operable IoT processes. From sensors and actuators, MapReduce ETL is built upon end-to-end standards:

  • MapReduce ETL supports the protocols for device-to-device or device-to-server communications.
  • MapReduce ETL supports the device management protocols for remote control of IoT devices and gateways.
  • MapReduce ETL supports IoT Gateways and Servers interfaces.

MapReduce ETL and CoAP
MapReduce ETL supports CoAP (Constrained Application Protocol), the protocol specialized for use with constrained nodes and networks.

MapReduce ETL and ETSI SmartM2M

  • MapReduce ETL supports ETSI SmartM2Mand the specifications for M2M services and applications.
  • MapReduce ETL provides specific focus on aspects of the Internet of Things (IoT) and Smart Cities.

MapReduce ETL and MQTT
MapReduce ETL supports Message Queuing Telemetry Transport (MQTT), the protocol designed to connect physical world devices and networks with applications and middleware used in IT and Web development.

MapReduce ETL and OMA LightweightM2M
MapReduce ETL supports OMA LightweightM2M (LWM2M) the industry standard for device management of M2M/IoT devices.

For MapReduce ETL solutions contact us, at sale@enterprisemapreduce.com  and we will be able to help you for your Enterprise IoT solutions implementation/customization services.

MapReduce ETL with IoT Services & Frameworks

MapReduce ETL and Frameworks for Kura

MapReduce ETL supports Kura, a set of Java and OSGi services that are most commonly required for IoT gateways including I/O services, Data Services, Cloud Services and Networking.

MapReduce ETL, SmartHome, and SCADA

MapReduce ETL supports SmartHome. SmartHome project is a framework that builds smart home solutions with a strong focus on heterogeneous environments, i.e. solutions that deal with the integration of different protocols or standards.

MapReduce ETL supports Eclipse SCADA. Eclipse SCADA is a way to connect different industrial devices to a common communication system and post both process and visual data to operating personnel.

For MapReduce ETL solutions contact us, at sale@enterprisereduce.com  and we will be able to help you for your Enterprise IoT solutions implementation/customization services.