Open Source Big Data Projects

Open Source Big Data Projects

     Open Source Big Data Projects is the fastest vehicle to outreaching the top of the Everest victoriously. Our world-taking professionals are 10+ years of experience in this respective field. As a part of our huge motivation is offering to hands on experience for worldwide students and research scholars. We invite scholars from the various streams of departments such as Information Technology (IT), Computer Applications (CS), Electrical and Electronic Engineering (EEE), Electrical and Communication Engineering (ECE) and Computer Application (CA). Nowadays, vast range of students and researchers come and join with us due to our standardized service. If you have anxious to utilize our experienced knowledge and guidance, get in touch with us swiftly.

Open Source Big Data Projects

    Open Source Big Data Projects give new-fashioned big data research projects for students and research scholars with the best quality and low cost. Innovations in greater affordability digital technologies have managed through today’s age of big data which is an explosion in diversity and quantity of high frequency digital data. Owing to we give the best of best for scholars to develop record breaking applications in their future profession.

Open Source Big Data Various Ubiquitous Sources:

  • IoT devices
  • Previous data warehouses and databases
  • Data feeds from social media
  • Legacy systems flat files
  • Mobile, web and application logs
  • Public datasets used

Plenty of Open Source Tools used to do Open Source Big Data Projects:

Before Big Data

  • OWB
  • SSIS
  • Talend
  • Pentaho Kettle
  • Informatica Power Center

Hadoop Ecosystem

  • HQL for Hive
  • Apache Pig
  • MapReduce

Apache Spark

  • Spark SQL
  • Jupyter and Zeppelin
  • Spark Shell

ODBS/JDBC connectivity databases

  • Spark SQL through Thrift Server
  • MPP data warehouses
  • Drill, Impala and Hive

SQL based Business Intelligence Tools

  • Tableau
  • Qlikview
  • Pentaho BI

Latest Open Source Big Data Tools:

  • Burrow [Apache Kafka monitoring companion]
  • Pinot [Real-time analytics engine]
  • Project Apex [Big Data software compatible with YARN]
  • Aerosolve [Dynamic pricing software]
  • Apache Zeppelin [Web front-end software]
  • Airflow [Manage various systems working]
  • Apache Flink [Distributed in-memory processing framework]

The Ways of Storing Open Source Big Data:

  • Search Databases (Solr and ElasticSearch)
  • Traditional databases and data warehouses
  • Hive meta-store managed tables
  • A different self-describing files (i.e. Avro, JSON, Parquet, XML)
  • Low latency SQL-on-Hadoop engines like Drill, Kudu, Impala
  • Wide table databases and Key-value table for random access (Cassandra and HBase)

     However, selecting software/tools is a quite challenging task and hard for students since there are number of tools is available in public. To help you, we ready to use any types of open source tools for your Open Source Big Data Projects. In below, we enumerate few lists of topics for your reference.

  • Emerging Mobile Communication Technologies in 5G Network for Healthcare System
  • Hybrid Backtracking Search optimization Algorithm and K-Means in Wireless Sensor Networks for Clustering
  • Visual Inspection System for Frequency Features based Rail Corrugation
  • A paradigm to Identify Repackaged Apps for Third Party Android Marketplaces
  • Vehicle Classification in Hybrid Dictionary Learning Based Acoustic Sensor Networks
  • Unsupervised Anomaly Detection for Smart Nursing Homes Using Light Switches
  • Low Complexity Intra Prediction Mode Selection Algorithm in High Frequency Video Coding (HFVC)
  • Enhanced Exponential Smoothing Model on Prediction of Public Bicycle Stations Rental Trends
  • Applying Virtual Coordination Anchor Node in Wireless Sensor Networks to Routing Mechanism
  • Massive Open Online Course (MOOC) Learning Effect and Learning Behaviors Using Causal Association Analysis Algorithm
  • Attack Detection Using ANN (Artificial Neural Network) and Generic Feature Selection in Cloud Infrastructure
  • Hybrid Recommendation Based on Collaborative Filtering and Deep Learning for Clod Start Problem
  • Managing Energy Efficiency for Analyze Power and Processing Usage Quantitative Using SNMPv3 in Cloud Computing
  • A Strategy Using Specialized Codes for Controlling Mobile Device Functionality
  • Semantic Based Strategy for Screen Based Reading to Building Auxiliary System