name 5 sources of big data
social networking, high speed networks, mobile computing, IoT, tracking equipment/software
5 forms of big data
4 characteristics of big data
volume
scale of data
velocity
analysis of streaming data
variety
different forms of data
veracity
uncertainty of data
value
converting data into money
how is value extracted from data
with business intelligence
increasing value of big data
BI
set of techniques/tools for acquiring/transforming raw data into meaningful and useful purposes
garbage in, garbage out
low quality data will not lead to any quality value
6 purposes of BI
data warehouse
holds data obtained from internal/external sources
business/data analytics
creates reports through queries/rules
business performance management
linkage of data with business objectives for efficient tracking
describe the BI framework
getting data in = data warehousing
getting data out = business intelligence
data and business decision making hierarchy
AI
intelligence exhibited by a machine
3 levels of AI
Turing tests
attempts to see whether computer responses are indistinguishable from a human
7 branches of AI
machine learning
deep learning and predictive analysis
NLP
translation, classification/clustering, info extraction