Topic: CCC Big Data Foundation
Assessment
CCC Big Data Foundation
Assessment
MasterClassTitle
Level of Difficulty Bloom Level 1 & 2: Knowledge and Comprehension
Qualification Objectives
● Explain Big Data, its origin, and its characteristics.
● Discuss about the tools applicable to Big Data processing.
● Explain data mining.
● Discuss the most popular Big Data technologies—Hadoop and MongoDB.
● Tell about Big Data projects and the main players involved.
References
Specific Sources:
• Facebook.com
• Twitter.com
• MongoDb.org
• Hadoop.org
• New York Times – “How Companies Learn Your Secrets” (Target's Story – Module 1)
• Business Insider (Pirates Story – Module 1)
• SAP.com
• Microsoft.com
• Oracle.com
• International Monetary Fund – http://www.imf.org/external/data.htm#data
• World Bank – http://data.worldbank.org/
• US Government – http://www.nber.org/data/
• European Commission – http://ec.europa.eu/economy_finance/db_indicators/
• Open Data US – data.gov
• Open Data Australia – data.gov.au
• Open Data European Union – open-data.europa.eu/en/data/
• KNIME – knime.org
• Weka – http://www.cs.waikato.ac.nz/ml/weka/
- Topic: CCC Big Data Foundation
- Author: Berter
- Created: 21-10-2020
- Played: 9
- Questions: 40
Sponsored by Adelaide Consulting Group, An Accredited Training Organisation.
Level of Difficulty Bloom Level 1 & 2: Knowledge and Comprehension
Qualification Objectives
● Explain Big Data, its origin, and its characteristics.
● Discuss about the tools applicable to Big Data processing.
● Explain data mining.
● Discuss the most popular Big Data technologies—Hadoop and MongoDB.
● Tell about Big Data projects and the main players involved.
References
Specific Sources:
• Facebook.com
• Twitter.com
• MongoDb.org
• Hadoop.org
• New York Times – “How Companies Learn Your Secrets” (Target's Story – Module 1)
• Business Insider (Pirates Story – Module 1)
• SAP.com
• Microsoft.com
• Oracle.com
• International Monetary Fund – http://www.imf.org/external/data.htm#data
• World Bank – http://data.worldbank.org/
• US Government – http://www.nber.org/data/
• European Commission – http://ec.europa.eu/economy_finance/db_indicators/
• Open Data US – data.gov
• Open Data Australia – data.gov.au
• Open Data European Union – open-data.europa.eu/en/data/
• KNIME – knime.org
• Weka – http://www.cs.waikato.ac.nz/ml/weka/