Math 144 Reviewer

Which of the following TRUE about the differences of Business Intelligence (BI) and Data Science?

I. Where Data Science problems tend to require highly structured data organized in rows and columns for accurate reporting, BI projects tend to use many types of data sources, including large or unconventional datasets.

II. Data Science tends to be more exploratory in nature and may use scenario optimization to deal with more open-ended questions.

• I only

• II only

• 
  

  both I and II

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  neither I nor II

Among the business drivers that push businesses to become more analytical and data driven, this one involves customer churn, fraud and default

• Optimize Business Operations

• Identify Business Risk

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  Predict New Business Opportunities

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  Comply with Regulatory Requirements

Which of the following is always TRUE about Big Data?

 I.  Due to its size or structure, Big Data cannot be efficiently analyzed using only traditional databases or methods.

 II. Although the variety of Big Data tends to attract the most attention, generally the volume and velocity of the data provide a more apt definition of Big Data.

• 
  

  I only

• 
  

  II only

• 
  

  both I and II

• 
  

  neither I nor II

This are centralized data containers in a purpose-built space that supports business intelligence and reporting but restricts robust analyses.

• 
  

  Data marts

• 
  

  Data warehouses

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  Analytic Sandbox

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  None of the Above

Which of the following are problems encountered in traditional data architecture?

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  High-value data is hard to reach and leverage, and predictive analytics and data mining activities are last in line for data.

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  Data scientists are limited to performing in-memory analytics which will restrict the size of the datasets they can use.

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  Data Science projects will remain isolated and ad hoc, rather than centrally managed.

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  All of the Above

Which of these attributes stand out as defining Big Data characteristics?

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  Huge volume of data

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  Complexity of data types and structures

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  Speed of new data creation and growth

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  All of the Above

This type of data has no inherent structure, which may include text documents, PDFs, images, and video.

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  Quasi-structured Data

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  Unstructured Data

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  Semi-structured Data

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  Structured Data

Which of the following is true about the current analytical architecture?

I. Data sources are first loaded into the data warehouse where data needs to be well understood, structured, and normalized with the appropriate data type definitions. This kind of centralization enables security, backup, and failover of highly critical data.

II. Once in the data warehouse, data is read by additional applications across the enterprise for BI and reporting purposes. These are high-priority operational processes getting critical data feeds from the data warehouses and repositories.

• 
  

  I only

• 
  

  II only

• 
  

  both I and II

• 
  

  neither I nor II

Examples that fall under this group includes financial analysts, market research analysts, life scientists, operations managers, and business and functional managers.

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  None of the Above

• Technology and Data Enablers

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  Data Savvy Professionals

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  Deep Analytical Talent

The following are recurring sets of activities that data scientist performs EXCEPT

• 
  

  Develop insights that lead to actionable recommendations.

• Provide technical expertise to support analytical projects such as provisioning and administrating analytical sandboxes.

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  Reframe business challenges as analytics challenges

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  Design, implement, and deploy statistical models and data mining techniques on Big Data