1. The authors of your textbook describe ten of the most prevailing metrics that define the readiness level of data for an analytics study. From among the ten metrics described by the authors, select the six metrics you consider especially essential to define the readiness level of data. To respond fully to this question prompt: List the six metrics you consider especially essential, define each metric, and briefly describe why you consider each essential.

1. The authors of your textbook describe A Simple Taxonomy of Data. Prompt One: What are the main categories of data. Prompt Two: What types of data can we use for BI and analytics?

1. The characteristics of charts can help in selecting and using the right chart/graph for a specific task. Prompt One: What are the main differences among line, bar, and pie charts? Prompt Two: When should you use one over the others?

1. At the heart of the technical side of the data warehousing process is extraction, transformation, and load (ETL). Prompt One: List and describe the three steps of the ETL process. Prompt Two: Why is the ETL process so important for data warehousing efforts?

1. A Data Warehouse is a pool of data produced to support decision making, as well as a repository of current and historical data of potential interest to managers throughout the organization. Prompt One: List and briefly describe each of the alternative data warehousing architectures discussed in the Alternative Data Warehousing Architectures section of Chapter 3. Prompt Two: Which architecture is the best?