BMED 2400 Unit 1
questions and answers
data engineering - answer curating, organizing, cleaning, and storing data in
databases and warehouses for subsequent analysis
the pre-processing
data analysis - answer apply biostatistical techniques to derive actionable
insight
data visualization - answer put the results into pretty figures/graphics to be
discussed and shown to the laypeople
obtain actionable information - answer what is the ultimate goal of data
scinece?
healthcare, biomedical engineering - answer two of the biggest domains that
can be iproved with big data analytics
engineering, analysis, visualization - answer 3 arms of data science
big data - answer a broad term for datasets so large or complex that
traditional data processing applications are inadequate.
lots of mixed data types coming in at high speed
volume, velocity, variety, veracity - answer What are the four V's of big data?
, volume - answer - how many bytes of data do you have
- peta/exa/zetta
90 - answer % of world data tat was created in the last 2 years alone
velocity - answer - data flow is continuous and massive
- speed of data creation an processes
- speed of incoming data and its perishable nature
no - answer are batch processes always feasible for big data
static, dynamic - answer with velocity, you have to link ______ and _________
data sources
perishable data - answer data is not useful after a certain period of time
variety - answer - data in many forms and types
- audio, images, text, numeric fields
- cannot simply be managed by getting better hardware
veracity - answer - data in doubt due to inconsistencies and ambiguities
- fast streaming and multiple formats can increase errors
- data flow/sources can be onisy
veracity issues - answer inconsistencies, missing data, duplications, partial
entries, ambiguities, approximations
yes - answer can data meaning change? does that cause a veracity issue?
questions and answers
data engineering - answer curating, organizing, cleaning, and storing data in
databases and warehouses for subsequent analysis
the pre-processing
data analysis - answer apply biostatistical techniques to derive actionable
insight
data visualization - answer put the results into pretty figures/graphics to be
discussed and shown to the laypeople
obtain actionable information - answer what is the ultimate goal of data
scinece?
healthcare, biomedical engineering - answer two of the biggest domains that
can be iproved with big data analytics
engineering, analysis, visualization - answer 3 arms of data science
big data - answer a broad term for datasets so large or complex that
traditional data processing applications are inadequate.
lots of mixed data types coming in at high speed
volume, velocity, variety, veracity - answer What are the four V's of big data?
, volume - answer - how many bytes of data do you have
- peta/exa/zetta
90 - answer % of world data tat was created in the last 2 years alone
velocity - answer - data flow is continuous and massive
- speed of data creation an processes
- speed of incoming data and its perishable nature
no - answer are batch processes always feasible for big data
static, dynamic - answer with velocity, you have to link ______ and _________
data sources
perishable data - answer data is not useful after a certain period of time
variety - answer - data in many forms and types
- audio, images, text, numeric fields
- cannot simply be managed by getting better hardware
veracity - answer - data in doubt due to inconsistencies and ambiguities
- fast streaming and multiple formats can increase errors
- data flow/sources can be onisy
veracity issues - answer inconsistencies, missing data, duplications, partial
entries, ambiguities, approximations
yes - answer can data meaning change? does that cause a veracity issue?
