Lesson 1 Quiz
One of the key differences between business analytics and data science is their primary focus either on business problems or on mathematical algorithms.
True
Analytics and analysis are essentially the same thing; they both focus on the granular level representation of complex problems through decomposition of the whole into its lower-level parts.
False
If a data scientist is analyzing historical data to identify problems and root causes, he/she is essentially conducting descriptive analytics.
True
ERP stands for enterprise resource planning and is used for the integration of company-wide data.
True
The most important driver behind business analytics popularity is the need for business managers to make experience and intuition driven business decisions.
False
Business analytics and data science have the same purpose: to convert data into actionable insight through an algorithm-based discovery process.
True
Major commercial business intelligence products and services were established in the early 1970s.
False
If I am distributing funds to different financial products to maximize return, | am essentially doing descriptive analytics.
False
Today, analytics can be defined simply as "the discovery of information/knowledge/insight in data.”
True
Business intelligence is a broad concept that also includes business analytics within its simple taxonomy.
False
Analytics is the art and science of discovering insight to support accurate and timely decision making.
True
Business analytics is the process of developing computer code and novel IT frameworks.
False
Organizations apply analytics to business problems to identify problems, foresee future trends, and make the best possible decisions.
True
DeepQA is a massively parallel, web mining focused, probabilistic computational algorithm developed by the SAS Institute.
False
Descriptive analytics is also called business intelligence that is the entry level in analytics taxonomy.
True
Lesson 1 Post Assessment
What are the main roadblocks to the adoption of analytics?
All of these
Jim, the marketing manager in the company, is interested in the sales numbers in the south region by each product type for the last six months. What type of analytics would you use to help him?
Descriptive
Which of the following developments is not contributing to facilitating the growth of decision support and analytics? AO Knowledge management systems
Locally concentrated workforces
What type of analytics seeks to identify the courses of action to achieve the best performance possible?
Prescriptive
If Jack is interested in identifying the optimal quantity of purchase orders in order to minimize the overall cost, which of the following types of analytics should he use?
Prescriptive
Firms have used analytics to enhance which of the following business activities?
All of these
Which of the following is not commonly used as an enabler of descriptive analytics?
Data mining
Lesson 2 Quiz
1. Association patterns can include capturing the sequence
of events and things.
True
2. Cubes in OLAP are defined as a multidimensional
representation of the data stored in and retrieved from data warehouses.
True
3. Prediction modeling is often classified under the
unsupervised machine learning methods.
False
4. Data mining can be used to predict the result of sporting
events to identify means to decrease odds of winning against specific opponent.
False
5. In banking and finance, data mining is often used to
manage microeconomics movements and overall cash flow outcomes.
False
6. One of the most pronounced reasons for the increasing
popularity of data mining is due to the fact that there are less suppliers than
corresponding demand in the business marketplace.
False
7. Novel is a key term in the definition of data mining,
which means that the patterns are known by the user within the context of the
system being analyzed.
False
8. Segmentation and outlier analysis are part of
classification modeling.
False
9. Data mining is primarily concerned with mining (that is,
digging out data) from a variety of disparate data sources.
False
10. In the retail industry, association rule mining is
frequently called market-based analysis.
True
11. CRM aims to create one-on-one relationships with
customers by developing an intimate understanding of their needs and wants.
True
12. Data mining leverages capabilities of statistics,
artificial intelligence, machine learning, management science, information
systems, and databases in a systematic and synergistic way.
True
13. The original terminology of data mining commonly refers
to discovering known patterns in large and structured data sets.
False
14. Manufacturers use data mining to classify anomalies and
commonalities in the production system to improve the manufacturing system.
True
15. Information warfare often refers to identify and stop
malicious attacks on critical information infrastructures in literarily any and
every organizations and business
True
Lesson 1 Post Assessment
In data mining, clustering is classified further into:
segmentation and outlier analysis.
Which of the following is the most commonly used clustering
k-means
What kinds of patterns can data mining discover?
Each correct answer represents a complete solution. Choose all that apply.
Clustering
Classification
Optimization
Forecasting
Association
What are the most common reasons why data mining has gained overwhelming attention in the business world?
All of these
In retailing, data mining is most commonly used to: |
predict future sales.
Which of the following statements is true about clustering?
Assigns customers to different segments
What is the primary difference between statistics and data mining?
Statistics starts with a well-defined proposition and hypothesis, whereas data mining starts with a loosely defined discovery statement.
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