Introduktion

Question 1

Varför är det bra att använda big data i beslutsfattande inom företag enligt en studie av Brown et al(2011)?

Answer 1

företag som använder data och affärsanalys för att vägleda beslutsfattande är mer produktiva och upplever högre avkastning på eget kapital än konkurrenter som inte gör det.

Question 2

Vilka är “the 5 Vs of Big Data”?

Answer 2

Volume, value, velocity, veracity & variety

Question 3

Vad menas med the first V “volume”?

Answer 3

refers to the amount of all types of data generated from different sources and continue to expand. The benefit of gathering large amounts of data includes the creation of hidden information and patterns through data analysis.

Question 4

Vad innebär the second V “variety”?

Answer 4

refers to the different types of data collected via sensors, smartphones, or social networks. Such data types include video, image, text, audio, and data logs, in either structured or unstructured format.

Question 5

Vad innebär the third V “velocity”?

Answer 5

refers to the speed of data transfer. The contents of data constantly change because of the absorption of complementary data collections, introduction of previously archived data or legacy collections, and streamed data arriving from multiple sources

Question 6

Vad ingår i “data sources”?

Answer 6

Sociala medier, Machine-generated data, sensing, transactions, IoT (“IoT represents a set of objects that are uniquely identifiable as a part of the Internet.”)

Question 6

Vad innebär the fourth V “value”?

Answer 6

is the most important aspect of big data; it refers to the process of discovering huge hidden values from large datasets with various types and rapid generation

Question 6

Vilka 5 kategorier klassificeras big data in i enligt Hashem et al (2015)?

Answer 6

(i) data sources, (ii) content format, (iii) data stores, (iv) data staging, and (v) data processing.

Question 7

Vad ingår i “content format”?

Answer 7

Structured data, unstructured data & semi-structured data

Question 8

Vad är structured data?

Answer 8

Structured data are often managed SQL, a programming language created for managing and querying data in RDBMS. Structured data are easy to input, query, store, and analyze. Examples of structured data include numbers, words, and dates.

Question 9

Vad är semi-structured data?

Answer 9

Semi-structured data are data that do not follow a conventional database system. Semi-structured data may be in the form of structured data that are not organized in relational database models, such as tables.

Question 10

Vad är unstructured data?

Answer 10

Unstructured data, such as text messages, location information, videos, and social media data, are data that do not follow a specified format.

Question 11

Vilka 4 saker ingår i “data stores”?

Answer 11

Document-oriented, column-oriented, graph database, key-value

Question 12

Vad är en document-oriented data store?

Answer 12

Document-oriented data stores are mainly designed to store and retrieve collections of documents or information and support complex data forms in several standard formats, such as JSON, XML, and binary forms (e.g., PDF and MS Word).

Question 13

Vad är en column-oriented data store?

Answer 13

A column-oriented database stores its content in columns aside from rows, with attribute values belonging to the same column stored contiguously. Column-oriented is different from classical database systems that store entire rows one after the other [16], such as BigTable

Question 14

Vad är en graph database?

Answer 14

A graph database, such as Neo4j, is designed to store and represent data that utilize a graph model with nodes, edges, and properties related to one another through relations

Question 15

Vad är key-value?

Answer 15

Key-value is an alternative relational database system that stores and accesses data designed to scale to a very large size

Question 16

Vilka 3 saker ingår i “data staging”?

Answer 16

Cleaning, transform, normalization

Question 17

Vad innebär cleaning (steg i data staging)?

Answer 17

Cleaning is the process of identifying incomplete and unreasonable data

Question 18

Vad innebär transform (steg i data staging)?

Answer 18

Transform is the process of transforming data into a form suitable for analysis.

Question 19

Vad innebär normalization (steg i data staging)?

Answer 19

Normalization is the method of structuring database schema to minimize redundancy

Question 20

Vilka 2 saker ingår i “data processing”?

Answer 20

Batch & real time

Question 21

Vad är batch i kontexten data processing?

Answer 21

Batch processing is the method computers use to periodically complete high-volume, repetitive data jobs

Question 22

Vad är real time i kontexten data processing?

Answer 22

a method of processing data at a near-instant rate, requiring a constant flow of data intake and output to maintain real-time insights

Question 23

Vad innebär “veracity”? (5 V)

Answer 23

Veracity innebär sanningshalten i datan - hur nyligen den är uppdaterad osv.