Description
The Guide to Business Data Analytics provides a foundational understanding of business data analytics concepts and includes how to develop a framework; key techniques and application; how to identify, communicate and integrate results; and more. This guide acts as a reference for the practice of business data analytics and is a companion resource for the Certification in Business Data Analytics (IIBA(R)- CBDA).
Explore more information about the Certification in Business Data Analytics at IIBA.org/CBDA.
About International Institute of Business Analysis
International Institute of Business Analysis(TM) (IIBA(R)) is a professional association dedicated to supporting business analysis professionals deliver better business outcomes. IIBA connects almost 30,000 Members, over 100 Chapters, and more than 500 training, academic, and corporate partners around the world. As the global voice of the business analysis community, IIBA supports recognition of the profession, networking and community engagement, standards and resource development, and comprehensive certification programs.
IIBA Publications
IIBA publications offer a wide variety of knowledge and insights into the profession and practice of business analysis for the entire business community. Standards such as A Guide to the Business Analysis Body of Knowledge(R) (BABOK(R) Guide), the Agile Extension to the BABOK(R) Guide, and the Global Business Analysis Core Standard represent the most commonly accepted practices of business analysis around the globe.
IIBA's reports, research, whitepapers, and studies provide guidance and best practices information to address the practice of business analysis beyond the global standards and explore new and evolving areas of practice to deliver better business outcomes.
Learn more at iiba.org.
Author: Iiba
Publisher: International Institute of Business Analysis
Published: 08/07/2020
Pages: 172
Binding Type: Paperback
Weight: 0.91lbs
Size: 11.00h x 8.50w x 0.37d
ISBN13: 9781927584200
ISBN10: 1927584205
BISAC Categories:
- Computers | Data Science | Data Analytics
- Computers | Management Information Systems
- Business & Economics | Information Management
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