Data Analytics and Knowledge

What is the purpose of data analytics?

• To generate raw data

• To clean and format data

• To make sense of data and produce information

• To retrieve structured data

What is the DIKW model used for?

• To clean and check the validity of input data

• To understand the evolution of data analytics

• To turn raw data into useful information, knowledge, and wisdom

• To apply machine learning and deep learning in data analytics

What are the three articles in the 'How data becomes knowledge' series?

• From data to knowledge, Data lakes and data swamps, Extracting dark data

• Data sources, Structured and unstructured data, Data mining tools

• Cognitive processing, Machine learning, Deep learning

• Data analytics, Data governance, Data lakes

What is a major source of machine-generated and real-time data?

• Traditional relational database

• Internet of Things (IoT) devices

• Scraped websites and social media

• Human interactions over digital media

Which type of data is more challenging for computers to understand?

• Structured data

• Unstructured data

• Machine-generated data

• Relational data

What makes processing structured data with computers easy and efficient?

• High degree of organization

• Machine-readable structure

• Efficient querying

• Human-centric processes

What is a disadvantage of human-centric processes in dealing with unstructured data?

• Time-consuming and energy expensive

• Lack of machine-readable structure

• Efficient retrieval and processing

• High degree of organization

What is the main focus of the DIKW model?

• Cleaning and formatting data

• Extracting information from diverse media formats

• Turning raw data into useful information, knowledge, and wisdom

• Applying machine learning and deep learning in data analytics

What are the challenges of processing unstructured data?

• Time-consuming and energy expensive

• Lack of machine-readable structure

• Efficient retrieval and processing

• High degree of organization

What is the main focus of data cleaning and formatting?

• Extracting information from diverse media formats

• Turning raw data into useful information, knowledge, and wisdom

• Applying machine learning and deep learning in data analytics

• Cleaning and formatting data