3. Metadata a) List and briefly describe the metadata below. More date = more variables→ more descriptive → enriched narrative. Includes capturing of meta-data (data that describe the data) to help analysts extract latent and nuanced insights. data TimeStamp Day 42370.0424 Fridey 42370.0431 Friday 42370.0438 Friday Location PaymentTyp IP Addes 164 138 2821 136. 142175.7 24.243. 197 20 Inde Terminal Lo Sales cash cash enline 23043731, 76.6s 29.7 43 235 16 48.03, 26J3.68 41.91 $ 320 81 212. 150.95 44.42 204 19 10.39, 178.36 654 233.15 30.78, 219.04 25.87 S online 24 online EFTPOS 4 42370 0445 Friday store EFTPOS 30 42370.0452 Friday 42370.0458 Friday 42370.0465 Friday 253. 119.128 23 180.2491782 online EFTPOS 50 online EFTPOS 205 02 24.6, 86.07 285 online cash 2348 3112, 17s.05 s0.41 144 126 134.16 22 32.01 S7.08, 185.08 57.37 139.71 21.39, 241.08 45.4 S 42373.3403 Monday 42373.341 Monday 42373 3417 Monday 42373.3424 Monday 42373 3431 Monday 42373.3438 Monday 4750 store EFTPOS 23 4751 store EFTPOS 259 15 50.33, 101.65 5.76 5.76 56.47, 335 98 42.59 353.13 10.37, 2373 25 45 5 417 4799, 172.02 58 4752 online EFTPOS 95.129.144.10 50 4753 online EFTPOS 132 152 2510 4754 online EFTPOS 11 16 55.7 4755 online EFTPOS 155..24 23 31 Meta data b) What information does it provide to help enhance business objectives? c) How can metadata be used to improve services and customer experiences? d) Evaluate the key differences between small data and big data analytics for Tibco Electricals.
3. Metadata a) List and briefly describe the metadata below. More date = more variables→ more descriptive → enriched narrative. Includes capturing of meta-data (data that describe the data) to help analysts extract latent and nuanced insights. data TimeStamp Day 42370.0424 Fridey 42370.0431 Friday 42370.0438 Friday Location PaymentTyp IP Addes 164 138 2821 136. 142175.7 24.243. 197 20 Inde Terminal Lo Sales cash cash enline 23043731, 76.6s 29.7 43 235 16 48.03, 26J3.68 41.91 $ 320 81 212. 150.95 44.42 204 19 10.39, 178.36 654 233.15 30.78, 219.04 25.87 S online 24 online EFTPOS 4 42370 0445 Friday store EFTPOS 30 42370.0452 Friday 42370.0458 Friday 42370.0465 Friday 253. 119.128 23 180.2491782 online EFTPOS 50 online EFTPOS 205 02 24.6, 86.07 285 online cash 2348 3112, 17s.05 s0.41 144 126 134.16 22 32.01 S7.08, 185.08 57.37 139.71 21.39, 241.08 45.4 S 42373.3403 Monday 42373.341 Monday 42373 3417 Monday 42373.3424 Monday 42373 3431 Monday 42373.3438 Monday 4750 store EFTPOS 23 4751 store EFTPOS 259 15 50.33, 101.65 5.76 5.76 56.47, 335 98 42.59 353.13 10.37, 2373 25 45 5 417 4799, 172.02 58 4752 online EFTPOS 95.129.144.10 50 4753 online EFTPOS 132 152 2510 4754 online EFTPOS 11 16 55.7 4755 online EFTPOS 155..24 23 31 Meta data b) What information does it provide to help enhance business objectives? c) How can metadata be used to improve services and customer experiences? d) Evaluate the key differences between small data and big data analytics for Tibco Electricals.
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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