T4 - Business Analytics Flashcards

1
Q

What is the difference between Business intelligence (BI) and Business Analytics (BA)?

A
  • BI involves the acquisition of data and information (eventually knowledge) from a significant variety of sources, promoting its organization in data warehouses and its use to support decision making.
  • Business Analytics supplies the analysis models and the procedures for Business Intelligence.
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2
Q

What is a multidimensional database?

A

A multidimensional database is structured around measures, dimensions, hierarchies, and cubes rather than tables, rows, columns, and relations.

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3
Q

And what is the purpose of multidimensional models?

A

Multidimensional models support BA by providing the organization analysts with data optimized for manipulation and analysis.

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4
Q

What are aggregates in cubes?

A
  • An aggregate is a value formed by combining values from a given dimension or set of dimensions to create a single value.
  • This is often done by adding the values together using the sum aggregate, but other aggregation calculations can also be used.
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5
Q

What are preprocessed aggregates and why do we have them?

A
  • Cubes with X dimensions and X hierarchies require quite a few aggregate calculations as the user navigates through the cube.
  • This can slow down analysis significantly.
  • To combat, the possible data aggregates are calculated ahead of time & stored within the cube.
  • These stored values = preprocessed aggregates.
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6
Q

What are the different possible OLAP operations?

A
  • Slice - a subset of a multidimensional array
  • Dice - a slice on more than two dimensions
  • Drill-Down - navigating among levels of data ranging from the most summarized to the most detailed
  • Roll-Up - computing all of the data relationships for one or more dimensions
  • Pivot - used to change the dimensional orientation of a report or an ad hoc query-page display
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7
Q

What are Drill-Down and Roll-Up?

A

Data can be disaggregated and aggregated along a dimension according to their natural hierarchy

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8
Q

What are “Slicing and Dicing“ the Data?

A

Choosing a range out of each dimension

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9
Q

What is Rotating the Data?

A

Different users will require different views of the multidimensional cube – OLAP allows easy rotation of data

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10
Q

What is Location-Based Analytics (and examples)?

A
  • Geospatial Analytics
  • Geocoding
    • Visual maps
    • Postal codes
    • Latitude & Longitude
  • Enables aggregate view of a large geographic area
  • Integrate “where” into customer view
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11
Q

What are two approaches to location-based analytics and what falls into each of these?

A
  • Organization oriented
    • Geospatial static approach: examining geographic site locations
    • Location-based dynamic approach: live location feeds, real-time marketing promotions
  • Consumer oriented
    • Geospatial static approach: GPS Navigation and data analysis
    • Location-based dynamic approach: historic and current location demand analysis, predictive parking, health-social networks
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12
Q

What is a Geographic Information System (GIS) used for and how?

A
  • System designed to capture, store, manipulate, analyze, manage, and present all types of spatial or geographical data.
  • GIS applications are tools that allow users to create interactive queries (user-created searches), analyze spatial information, edit data in maps, and present the results of all these operations.
  • Combined with integrated sensor technologies and global positioning systems (GPS)
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13
Q

What is Location Intelligence (LI)?

A

Interactive maps that further drill down to details about any location

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14
Q

What are examples of location analysis capabilities?

A
  • overlay analysis
  • proximity analysis
  • network analysis
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15
Q

What is meant with Real-Time Location Intelligence?

A
  • Many devices are constantly sending out their location information
    • Cars, airplanes, ships, mobile phones, cameras, navigation systems, …
      • GPS, Wi-Fi, RFID, cell tower triangulation
  • Reality mining?
    • Real-time location information = real-time insight
    • Path Intelligence (pathintelligence.com)
      • Footpath – movement patterns within a city or store
      • How to use such movement information
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16
Q

What is Stream Analytics? Why?

A
  • Streaming analytics = Data-in-motion analytics and real-time data analytics
  • through the use of continuous queries (=event streams)
  • Analytic process of extracting actionable information from continuously flowing data
  • Why? Because it may not be feasible to store the data, or lose its value
17
Q

What are examples of Stream Analytics Applications?

A
  • e-Commerce
  • Telecommunication
  • Law Enforcement and Cyber Security
  • Power Industry
  • Financial Services
  • Health Services
  • Government
  • Smart Cities