1. Businesses are aggressively moving towards IT support for their organizations. Can you list at least 2 of the factors driving this movement?
• Speed and efficiency.
• Legibility and precision.
• More economical research and development.
2. The definition of Business Intelligence (BI) is:
BI is a general term that combines architecture, tools, databases, analytical tools, applications and methodologies.
What does the term “umbrella” mean?
The definition of Business Intelligence (BI) encompasses various software applications that are used to analyze the raw data of an organization. The discipline involves many related activities, including data mining, online analytical processing, querying, and reporting.
3. We sometimes say that the term Business Intelligence (BI) is “context free”. What does this mean?
The term business intelligence is “context-free” in the sense that the term means different things to different people. For this reason, we have seen researchers advance different definitions of business intelligence.
4. Describe what a data warehouse is and how it might differ from a traditional database used for transaction processing.
A data warehouse is a central repository of corporate data and information that an organization derives data from transactions, operating systems, and external data sources. Although these two may appear similar, they exhibit several differences regarding usage pattern, architecture, and technology. A traditional database relies on operational processing, while a data warehouse relies on information processing.
A data warehouse focuses on the storage, filtering, retrieval, and analysis of voluminous information.
A traditional database is used for day-to-day operations, while a data warehouse is used for long-term information requirements.
5. What is the difference between a data warehouse and a data mart?
A data mart is a subset of a data warehouse that relates to a specific line of business. Data markets are managed by a specific department within an organization. On the other hand, a data warehouse involves multiple subject areas and gathers detailed information from multiple source systems.
6. What is meant by “Big Data”?
Big data refers to a large volume of structured, semi-structured, and unstructured data from which viable information can be extracted. This type of data is so voluminous that it cannot be processed using outdated database and software techniques. Big data helps organizations improve their operations and be in a position to make quick and smart decisions.
7. Data mining methods are divided into supervised and unsupervised methods. What are these and how are they different?
The supervised data mining method is all about presenting fully labeled data to a machine learning algorithm. On the other hand, unsupervised data mining methods perform pooling. Data instances are divided into several groups.
Unsupervised data mining methods do not emphasize default attributes. Also, it does not predict a target value. Instead, unsupervised data mining finds hidden structures and relationships between the data.
Supervised data mining methods are appropriate when there is a specific target value that will be used to predict the data. Goals can have two or more possible outcomes, or even be a continuous numerical value.
In supervised data mining methods, the classes are known in advance, while in the other the groups or classes are not known in advance. In supervised data mining methods, data is mapped to be known before calculation, but in unsupervised learning, data sets are mapped to segments, with no groups being known.
8. When we consider KPIs (key performance indicators), we distinguish between driving KPIs and result KPIs. What is the difference between the two? (Give a couple of examples of each)
Key performance indicators provide a framework against which organizations can assess their progress. Outcome KPIs, which are also called lagging indicators, measure the result of past activities. On the other hand, driver / leading indicator KPIs measure activities that have a significant impact on the results KPIs. Drivers’ KPIs have a significant effect on results KPIs, but the reverse is not necessarily true.
9. A BSC (balanced scorecard) approach to BPM (business process management) is well known and widely used. Describe the strengths of a BSC approach.
BPM involves activities
BPM involves activities such as automation, remodeling, monitoring and analysis and improvement of business processes.
This is one of the most palpable benefits of the BPM approach. Reduce costs and increase revenue. BPM adds crucial long-term value by enabling companies to compete globally. BPM technology equips a company to change gears and respond appropriately to the changing business environment.
Change is inevitable in business and a company must be prepared for sudden changes at any moment. BPM gives a company the flexibility to make changes at minimal costs.
BPM automates various elements within regular workflows. Process improvements, such as the elimination of hassles, the elimination of redundant steps, and the introduction of parallel processing, are achieved through BPM. These process improvements allow employees to focus on other important business activities, as basic support functions would have been handled.
Basically, BPM uses advanced software programs to facilitate the automation process. These programs allow process owners to keep abreast of their performance. In addition to ensuring transparency, BPM keeps track of how processes work without the need for extensive work and monitoring techniques.
10. A closed loop process is often used to optimize business performance. Briefly describe what a closed loop process means.
A closed loop process, also known as a feedback control system, is a management system that promotes a well-organized base of preferred results and feedback from the system. This process is designed to achieve and maintain the desired result compared to the actual condition.