Capturing Value from Big Data

Question 1

What are data-driven business models (DDBMs)?

Answer 1

business models that support data-related ventures to capture value. They need to use data as a key resource for their business model.

Question 2

What does the static view describe?

Answer 2

the current state of a company and the dynamic view examines the evolution of a business model. A business model articulates the value proposition, identifies a market segment, and defines a company’s value chain.

Question 3

What are the six key dimensions of the DDBM framework?

Answer 3

key resources, key activities, offering/value proposition, customer segment, revenue model, and cost structure.

Question 4

What do firm resources include?

Answer 4

all assets, capabilities, organizational processes, firm attributes, information, and knowledge controlled by a firm

Question 5

what are five types of data sources?

Answer 5

operation data from transaction systems, dark data that you own but is currently unsused, commercial data, social data, and public data.

Question 6

What does internal data include?

Answer 6

owned but unused data, self-generated data, and crowd sourced data.

Question 7

What does external data include?

Answer 7

bought data, data provided by customers or business partners, and freely available data.

Question 8

What can freely available data be split into?

Answer 8

open data (downloadable, structured), social media data, and web-crawled data.

Question 9

What are five data-related key activities?

Answer 9

selection of data, pre-processing data, data reduction or transformation, data mining, and the interpretation and visualization.

Question 10

What is the offering/value proposition?

Answer 10

the value created for customers through the offering. A company’s offering can either be data or information/knowledge (interpreted data).

Question 11

Name different revenue streams

Answer 11

asset sales, lending/renting/leasing, licensing, usage fee, subscription fee, brokerage fee, advertising.

Question 12

Type A: Free data collector and aggregator

Answer 12

Type A companies create value by collecting and aggregating data from a vast number of different, mostly free, data sources, and then distributing it.

Question 13

ype B: “Analytics-as-a-service”.

Answer 13

Type B companies conduct analytics (100 per cent) on data provided by their customers

Question 14

Type C: “Data generation and analysis”

Answer 14

Type C companies generate data rather than relying on existing data. Moreover, many also perform analytics on this data. Firms can be roughly subdivided into three groups: companies that generate data through crowdsourcing; web analytics companies; and companies that generate data through smartphones or other physical sensors.

Question 15

Type D: “Free data knowledge discovery”

Answer 15

Type D companies create value by performing analytics on free available data

Question 16

Type E: “Data-aggregation-as-a-service”

Answer 16

Companies in this cluster create value neither by analysing nor creating data but by aggregating data from multiple internal sources for their customers. This cluster can be labelled “aggregation-as-a-service”. After aggregating the data, the companies provide it through various interfaces (distribution: 83 per cent) and/or visualise it

Question 17

Type F: “Multi-source data mash-up and analysis”

Answer 17

Type F companies aggregate
data provided by their customers with other external, mostly free, available data
sources, and perform analytics on this data. The offering of these companies is characterised by using other external data sources to enrich or benchmark customer data.