ACCT10003 Lecture Notes - Lecture 10: Enterprise Resource Planning, Customer Relationship Management, Unstructured Data
19 Jun 2018
School
Department
Course
Professor
Accounting Processes and Analysis
Lecture 10: Big Data
LO#1- Define big data and describe its key characteristics
“Big data refers to datasets whose size is beyond the ability of typical database software tools to capture,
store,
manage and
analyse”
Volume
exponential growth in generation,
collection and storage of data
Velocity
The speed at which data is acquired and used. Determine the meaning at a faster rate and in real-time
Variety
Data may be structured or unstructured. (80% non-traditional unstructured data, 20% traditional
structured data)
Structured data: a defined length and format. E.g. numbers, dates, strings. Usually stored in
a database and can be queried (for example, with Structured Query Language (SQL)). “Traditional”
accounting and financial data, including Customer Relationship Management (CRM) data and
Enterprise Resource Planning (ERP) data.
Sources of structured big data include computer or machine generated (Sensor data; e.g.
RFID tags, smart meters, medical devices, GPS data - Web log data: servers, applications, networks,
capture data about their activity - Point-of-sale data: swipe a product code - Financial data: e.g.
automated stock trading data) and human generated (Input data - Click-stream data).
Unstructured data: Machine generated (Satellite images: e.g. Google Earth, weather data -
Scientific data: e.g. seismic data, atmospheric data, climate data - Photographs and video: includes CCTV,
security, surveillance, traffic videos - Radar or sonar data) and human-generated unstructured data
( Internal business textual data: emails, documents, reports, logs, etc. - Social media data: YouTube,
Facebook, Twitter, LinkedIn, etc. - Mobile data: text messages, location data – Website content)
Veracity
find more resources at oneclass.com
find more resources at oneclass.com
Document Summary
Lo#1- define big data and describe its key characteristics. Big data refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage and analyse . Volume exponential growth in generation, collection and storage of data. The speed at which data is acquired and used. Determine the meaning at a faster rate and in real-time. Data may be structured or unstructured. (80% non-traditional unstructured data, 20% traditional structured data) Usually stored in a database and can be queried (for example, with structured query language (sql)). Traditional accounting and financial data, including customer relationship management (crm) data and. Unstructured data: machine generated (satellite images: e. g. google earth, weather data - Scientific data: e. g. seismic data, atmospheric data, climate data - photographs and video: includes cctv, security, surveillance, traffic videos - radar or sonar data) and human-generated unstructured data ( internal business textual data: emails, documents, reports, logs, etc.
