What CITM-001 Questions and Answers feature?

Information derived from processing transaction reduces uncertainty about a firm’s order backlog or financial position because it provides a quantitative and forward-looking measure of demand. Order backlog is the amount of orders that a firm has received but not yet fulfilled. It reflects the expected future revenue and cash flows of the firm, as well as its ability to meet customer needs and expectations. Order backlog can also indicate the competitive position and market share of the firm, as well as its operational efficiency and capacity utilization. Therefore, disclosing order backlog can help stakeholders such as investors, analysts, managers, and regulators to assess the firm’s performance and prospects more accurately and reliably. References: Sample Exam - GAQM, page 4; Implications of Disclosing Order Backlog, page 1-2; Backlog Definition, Implications, and Real-World Examples - Investopedia

Whatsup is an application software that allows users to send text messages, voice messages, make voice and video calls, and share images, documents, user locations, and other media. Whatsup is a cross-platform instant messaging subscription because it works on different operating systems such as Android, iOS, Windows Phone, and KaiOS, and it requires users to pay a yearly fee after the first year of use. Whatsup uses the user’s phone number as the primary identifier and encrypts all communication end-to-end. References: Whatsup - Wikipedia, Whatsup FAQ - About Whatsup, Whatsup FAQ - How to verify your number, Whatsup FAQ - How to access your messages and media.

Data warehousing and data mining are closely related technologies that support business intelligence and analytics. Data warehousing is the process of collecting, integrating, and organizing data from various sources into a centralized repository that can support complex queries and analysis. Data mining is the process of applying various techniques and algorithms to extract useful information and patterns from the data stored in the data warehouse. Data mining can help discover hidden relationships, trends, anomalies, and insights that can improve decision making and performance. One of the main reasons for building a data warehouse is to enable data mining, as data warehouses provide a consistent, reliable, and comprehensive source of data that can be mined for various purposes. Data warehouses also facilitate data mining by providing data quality, data cleansing, data transformation, data aggregation, and data indexing services that can enhance the accuracy and efficiency of data mining. Data warehouses and data mining are complementary technologies that work together to deliver business value and competitive advantage. References: Data Warehousing and Data Mining 101, Data Warehousing and Data Mining - Topcoder, Difference between Data Warehousing and Data Mining