Could not attend the live training workshop, November 11th & 18th? Get it On-Demand!
If you did not get a chance to access our live training workshop sessions (November 11th & 18th) , no worries! Here is your chance to catch what you missed. You can still purchase an on-demand access ticket and watch the session recordings at your convenience, up until February 15th, 2021, by logging in to the Agenda page. Your on-demand ticket includes access to all session recordings and the presentation decks.
About this Training Session
Studies have shown that over 80% of the work in Data Analytics projects is on Data Engineering, so Data Engineers and Data Engineering skills are currently in high demand. Data Engineering (a.k.a DataOps) is the collection, transformation and ingestion of data in a format that can be used by the Data Scientist to derive insights.
Data Engineering for Reliable Data Analytics is a two half-day live, virtual, and practical training course designed to equip participants with key data engineering concepts and skills. The course is conceptual in nature and not does go deep into specific technologies or vendor products. It touches upon the key data engineering tools and processes one needs to know to streamline their data management processes from the Data Capture or Transactional Systems to the Data Warehouse or Data Lake. This course will provide you with better insights and the building blocks of Data Engineering knowledge.
Key Session Objectives:
Our Data Engineering for Reliable Data Analytics training is designed for Data Managers, Business Analysts, Data Scientists, Programmers, and Data Governance Leaders and builds one’s technical and managerial competencies. In other words, this course is designed for data management professionals who work closely with the Data Engineer.
This training has 3 key learning objectives.
Understand Data Engineering, Analytics, Business Data and Business Systems
Build Knowledge on the key building blocks of Data Engineering
Learn key Data Engineering strategies and processes to acquire quality data for Data Analytics.
Training Methodology, Certificate of Achievement, and Session Recordings:
This training is a two half-day, 4-session course and uses field-tested tools and techniques. The training material is constantly updated to match the latest trends and industry best practices. Our instructor uses a variety of approaches including live presentation, classroom discussions, videos, pre-class readings, and case studies.
Participants will be awarded a Certificate of Achievement as evidence of the course mastery. Post training, Dr. Southekal is always available for any short discussion with the students via email, LinkedIn, phone, or video conferencing tools.
Session recordings will also be provided to participants after the event.
Continuing Education (CE) Credits:
AIDMs and CIDMs attending will receive 15 CE credits towards their IDMA continuing education program.
Prashanth Southekal, PhD
Managing Principal at DBP-Institute, and Adjunct Faculty of Data Analytics at University of Calgary (Canada) and IE Business School (Spain)
Dr. Prashanth H Southekal is the Managing Principal of DBP-Institute, a Data Analytics Consulting and Education company. He brings over 20 years of Information Management experience from companies such as SAP AG, Shell, Apple, P&G, SAS and General Electric. In addition, he has trained over 1000 professionals world over in Analytics, Data Products, and Enterprise Performance Management (EPM). He sits on the Advisory board of SAS (Western Canada) and Grihasoft (India). He is the author of the book - Data for Business Performance and Analytics Best Practices. He is an adjunct faculty of Data Analytics at University of Calgary (Canada) and IE Business School (Spain). He holds a PhD from ESC Lille (France) and MBA from Kellogg School of Management (United States).
Founded in 1983, and currently serving over 4000+ members, the Insurance Data Management Association (IDMA) is a global, independent, non-profit professional association dedicated to increasing the level of professionalism, knowledge, and visibility of enterprise data management in insurance and financial services through education, research, best practices, forums, and peer-to-peer networking. Visit www.idma.org for more information.