brijeshbmehta adlı kullanıcının profil görüntüsü
@brijeshbmehta
18 Kasım 2013 den beri üye
2 Tavsiyeler

brijeshbmehta

Çevrimiçi Çevrimdışı
I am comfortable with Installation and configuration of big data related tools and technologies such as, Hadoop, Spark, Pig, Hive, and NoSQL databases. I can work on data management as well. You can ask for anything related to Hadoop stack. I am also working on Kubernetes, and Docker. I am also a talented and experienced Articles Writer. I have good experience with Article writing. I am a hard worker and enjoy working at all critical conditions. If hired by you I will be responsible to complete the task within the stipulated time frame and with utmost confidence.
$20 USD/hr
2 değerlendirme
2.1
  • 100%Tamamlanmış İşler
  • 100%Bütçe Dahilinde
  • 100%Zamanında
  • N/ATekrar İşe Alım Oranı

Portfolios

Son Değerlendirmeler

  • Sandeep C. görüntüsü Hadoop BigData - Urgent... [Sealed]

    “Nice work done by Brijesh M.”

  • Open Source S. görüntüsü MongoDB cluster configuration $15.00 USD

    “Calm personality and very helpful. Really enjoyed working with him. Hire this guy, you won't be disappointed! Highly recommended.”

Tecrübe

Big Data Consultant

May 2019

Configure, manage and maintain big data storage infrastructure. Develop storage architectures to store large amount of data. Recently configured MongoDB cluster with shards.

Assistant Professor

Jan 2018 - Mar 2019 (1 year)

Taught Under Graduate and Post Graduate students of Engineering. Recruited under National Project Implementation Unit (NPIU) - Technical Education Quality Improvement Programme III (TEQIP III) sponsored by world bank. Taught subjects like, Distributed Computing / Systems, Network Programming, Database Systems, Distributed Database Systems. Worked as an Information Technology Infrastructure Coordinator and Technical Events Coordinator.

PhD Research Scholar

Aug 2014 - Dec 2017 (3 years)

Research contribution towards the scalability of existing Privacy Preserving Data Publishing Approaches such as k-Anonymity and l-Diversity. Worked on converting unstructured data to the structured data using Conditional Random Fields (CRF) based Named Entity Recognition (NER) approach. Apache Hadoop 1x cluster was built for the experiments. Implemented our proposed approaches using Apache Hadoop (MapReduce), Apache Pig and Python.

Assistant Professor

Dec 2011 - Jul 2014 (2 years)

Taught Under Graduate and Post Graduate students of Engineering. Involved in institute level committee for organizing technical events. Held position of Secretary-cum-treasurer in ISTE(Indian Society for Technical Education) Chapter, which is responsible for organizing and managing technical activities at our Institute. Taught subjects like, Distributed Computing / Systems, Distributed Operating Systems, Advanced Computer Networks, Advanced Computing Technology, Advanced Java Technologies.

Assistant Professor

Jan 2011 - Dec 2011 (11 months)

Taught Under Graduate students of Engineering. Involved in department level committee for organizing technical events. Taught Computer Programming and Utilization (includes, basics of computer and C language).

Hardware Engineer

Aug 2007 - Jul 2008 (11 months)

Provided service and support for Thin Client machines manufactured by our company (Smart Station). Resolved computer hardware issues for our clients. Configuration and installation of Servers and Thin Clients.

Linux Administrator Trainee

Jan 2007 - Jul 2007 (6 months)

Maintenance and Administration of Linux servers. Administration of websites developed by our company. Worked on technologies such as CVS, Xen, RHEL, MySQL, Php, Shell Scripting, Fedora, KDE

Eğitim

Doctorate

2014 - 2019 (5 years)

Master of Technology

2009 - 2011 (2 years)

Bachelor of Engineering

2003 - 2007 (4 years)

Nitelikler

M201: MongoDB Performance (2019)

MongoDB University

M121: The MongoDB Aggregation Framework (2019)

MongoDB University

M001: MongoDB Basics (2019)

MongoDB University

M103: Basic Cluster Administration (2019)

MongoDB University

Scala 101 (2019)

Cognitive Class

Python 101 (2019)

Cognitive Class

End to End Innovation Program (2018)

IIT Bombay

Hadoop 101 (2017)

Big Data University

Data Science 101 (2017)

Big Data University

Big Data 101 (2017)

Big Data University

CSE1309x: Python Programming (2016)

edX The University of Texas System

Advanced Systems Security: Attacks and Defenses (2016)

MNIT Jaipur

CS190.1x: Scalable Machine Learning (2015)

edX Berkeley

ENGRI1280x: Wiretaps to Big Data: Privacy and Surveillance in the Age of Interconnection (2014)

edX Cornell University

ColWri2.3x: Principles of Written English, Part 3 (2014)

edX Berkeley

Architecting Software for the Cloud, an online course on Building Cloud based Applications (2014)

IIT Ropar and IIT Kanpur

Java Fundamentals and Java Programming (2014)

Oracle Academy

Digital Systems and Pedagogy Overview (2013)

IIT Gandhinagar and IEEE

Yayınlar

Improved l-Diversity: Scalable Anonymization Approach for Privacy Preserving Big Data Publishing

Scalable l-Diversity (SLD) is improvised in terms of data utility as Improved Scalable l-Diversity (ImSLD) for Privacy Preserving Big Data Publishing (PPBDP). The proposed algorithm is implemented using Apache Pig and Python over Apache Hadoop cluster.

Towards privacy preserving unstructured big data publishing

Scalable k-Anonymization (SKA) is improvised in terms of data utility as Improved Scalable k-Anonymization (ImSKA) for Privacy Preserving Big Data Publishing (PPBDP). Conditional Random Fields (CRF) based Named Entity Recognition (NER) is used to convert unstructured data to structured data. The proposed algorithm is implemented using Apache Pig and Python over Apache Hadoop cluster.

Scalable l-Diversity: An Extension to Scalable k-Anonymity for Privacy Preserving Big DataPublishing

Scalable k-Anonymization (SKA) approach is extended for l-diversity as Scalable l-Diversity (SLD) for Privacy Preserving Big Data Publishing (PPBDP). The proposed algorithm is implemented using Apache Pig and Python over Apache Hadoop cluster.

Toward Scalable Anonymization for Privacy-Preserving Big Data Publishing

Scalable k-Anonymization (SKA) approach is proposed over Hadoop cluster for Privacy Preserving Big Data Publishing (PPBDP). The proposed algorithm is implemented using Apache Hadoop (MapReduce) and Python.

Privacy preserving big data publishing: a scalable k-anonymization approach using MapReduce

A novel scalable approach based on k-anonymization is proposed for large volume of data in Privacy Preserving Big Data Publishing (PPBDP). The proposed algorithm is implemented using Apache Pig and Python over Apache Hadoop cluster. Based on empirical analysis it is found that the proposed approach have low information loss and very low running time as compared to existing approaches.

Towards Privacy Preserving Big Data Analytics

Discussion related to privacy issues with big data. Comparison of existing privacy preserving techniques with 3Vs of big data.

Privacy Preserving Unstructured Big Data Analytics: Issues and Challenges

Discussion related to privacy issues and challenges with respect to unstructured big data.

Watermarking for security in database: A review

A brief survey of database watermarking schemes.

A Novel approach as Multi-place Watermarking for Security in Database

Discussion related to database watermarking and existing techniques. Proposed a novel approach of inserting watermarking at two different places in database for copyright protection

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