Big Data Technologist



The 24 hours training aims to introduce the concepts, terminologies and IBM technologies available today to process, operate, and maintain Big Data repositories to further help executives to make decisions and to understand the sentiments of data at certain domain. The training aims to presents the successful uses cases of Big Data in today’s business. The training is intended to provide a broad introduction into the Big Data technologies and their related ecosystem.


Targeted Audience:


Senior executive managers, senior undergraduate computer and business students, post graduate students, IT staff, and business users who are interested in Data Science. 




Basic knowledge of computer and Information Technology concepts. Superficial knowledge of Linux and programming concepts.

Advantageous: R and Python programming skills. Jupyter for data scientist.


Textbook and Articles:


- Lecture Notes will be distributed during the training.

- White, T. (2015). Hadoop: The definitive guide (4th, revised & updated ed.). Sebastopol, CA: O'Reilly Media. ISBN 978-1-491-90163-2. 756pp.

- Zikopoulos, P., deRoos, D., Bienko, C., Buglio, R., & Andrews, M. (2015). Big data beyond the hype: A guide to conversations for today’s data center. New York:  McGraw Hill Education.

- Google’s Paper on Big Table:

- Google’s Paper on MapReduce:


Desktop / Notebook Requirements:




- Windows 7+ Pro, or preferably Windows 10 Pro, 64-bit, 8 GB RAM (16+ GB strongly preferred), 100 GB available disk (or a 500GB+ external USB drive).


- Apple computers with a recent version of Mac OS X can be used, but all directions given throughout the course will be for Microsoft Windows 10 environments exclusively. Again, minimal memore if 8 GB RAM, with 16+ GB strongly preferred.




9:00 am to 5:00 pm.




24 Hours Training/ 3 Days

Training fees

1500 AED / person



  • Develop an understanding of the concepts of Big Data terminologies and the associated successful uses cases.
  • Evaluate, acquire, process, and model the several types of data.
  • Compare and evaluate the major component of Hadoop ecosystem.
  • Prepare attendees to the international IBM Big Data Engineer Mastery Award certificate
  • This training aims to prepare and qualify practitioners from academia and industry for the IBM professional exam Big Data Engineer Mastery Award for Educators (2018) and IBM Big Data Engineer - Explorer Award for Educators 2018. Upon the completion of training and attendance , attendees will be granted an online digital badge issues by IBM (Explorer award for Educators 2018) that certifies holder eligibility of attending this training course and passing exam.
  • Moreover, attendees will be eligible for the Big Data Engineer Mastery Award for Educators (2018) exam. Upon passing this exam (60%) practitioners will be awarded the Mastery award badge (2018)

Training Contents


Training Duration

3 days

(Thursday, Friday and Saturday)

9:00 am to 5:00 pm.

  • Orientation and Introduction to Big Data What is Big Data? History, Decision making, Data Types (Data at rest, Data at motion), Big Data uses cases, Why Hadoop? Hardware implementation, commodity hardware.
  • Hadoop and HDFS Introduction to Big Data and Data Analyticsو Introduction to HDP (overview)و Apache Ambariو Hadoop and the Hadoop Distributed File System (HDFS), MapReduce and YARN, Apache Spark. Storing and Querying Data, ZooKeeper, Slider, and Knox, Loading data with Sqoop, Security & Governance, Stream computing.
  • Introduction to Data Science Data Science & Data Science Notebooks, Data Science with Open Source Tools.
  • Big SQL Introduction & Developers: Using Big SQL to access data residing in the HDFS, Creating Big SQL schemas and tables, File formats and querying Big SQL tables, Administrators: Managing the Big SQL Server, Configuring Big SQL security, Data federation with Big SQL.
  • Data Science Experience (DSX) Introduction to IBM Data Science Experience (DSX), Analyzing data with DSX .
  • Certification Test Pre-Run .

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American University in the Emirates

Location: Dubai Int. Academic City, P.O. Box: 503000, Dubai, UAE
Phone: + 971 4 4499 000 | Fax: + 971 4 4291 205
Email: |
Toll free 800AUE (283)

Dr. Abedallah Abualkishik

Position / Designation Here

Dr. Abedallah is a Software Engineering Ph.D holder. He is an assistant professor at the AUE. He is an active researcher in the software cost estimation field, empirical software engineering studies, and functional size measurement.