D204 WGU Study Material Graded A 2024

List the Data Analytics Life Cycle phases. 1. Business understanding 2. Data acquisition 3. Data cleaning 4. Data exploration 5. Predictive modeling 6. Data mining 7. Reporting and visualization Describe the business understanding phase of the data analytics life cycle. This phase is also known as the discovery phase. -Defines the major questions -Determines the needs of the stakeholders -Assesses the resource constraints of the project Describe the data acquisition phase of the data analytics life cycle. This is the phase of collecting data. -Data will be retrieved from a database, perhaps a component of a data warehouse, by using a language like SQL. -Sometimes, data might not be available. In these cases, the analyst will use tools such as web scraping or surveys to acquire it. Describe the data cleaning phase of the data analytics life cycle. Common alternative names include data cleansing, data wrangling, data munging, and feature engineering. -When this phase is ignored or skipped, the results from the analysis may become irrelevant. -Data quality is measured in terms of uniqueness and relevance. Describe the data exploration phase of the data analytics life cycle. -Begin to understand the basic nature of data and the relationships within it. -Relies on the use of data visualization tools and numerical summaries, such as measures of central tendency and variability. Describe the predictive modeling phase of the data analytics life cycle.