CHAPTER 1: OVERVIEW OF BUSINESS ANALYTICS
(Chapter Content)
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Overview of business analytics
Origin of business analytics
Business analytics
Business intelligence
Big data and business analytics
Four aspect of big data
OVERVIEW OF BUSINESS ANALYTICS
- to explain the business analytics, you have to make a
lot of assumptions that generalize the challenges
organization have with making using business data to
make good decisions.
tools with which people can disseminate the data that’s
been collected, to produce meaningful conclusions
(Fulton, 2013)
- Business Analytics is the study of data through
statistical and operations analysis, the formation of
predictive models, application of optimization
techniques, and the communication of these result to
customers, business partners, and college executives
(Galleto, 2018)
- making decisions is the most important task in the role
(Business Analytics)
- ginagamitan ng data / mathematical computer based
model
- art of assembling data gathered
- portion of business intelligence according to Fulton
- organization have been employing business analytics
to analyze their data for decades. Every organization
has different data and a different approach to analyzing
it. There is no one size fits all business analytics
solutions.
- to gain more insight the company
- Summary
- has a direct impact on organization’s strategic, tactical
and operational business decisions. BI supports factbased decision making using historical data rather than
assumption and gut feeling.
ORIGIN OF BUSINESS ANALYTICS
- focus on financial
BUSINESS INTELLIGENCE
- From ancient times, people have had this need to
predict the future. They have used crude methods like
stones and sticks to project how much crops they were
going to harvest or how they were going to yield.
- process of collecting information from all sources to
make data-driven decisions in an organization (Fulton,
2013, Galleto, 2018).
- mga taong naka dipende sa mga bagay bagay
- process of combining aspects of reporting, monitoring
and alerting, dashboards, scorecards, and ad hoc query
data exploration (Caspistrano, 2018, Galleto, 2018).
- they use stick and they predict how many they are
going to harvest
- 1970 computer’s created.
- giving the right decisions at the right time to the right
person
- contains messy information / inaayos ang mga data or
information
BUSINESS ANALYTICS
- business analytics is one of the most talk-about topics
in the field of business and information technology. An
as expected, business analytics is becoming one of the
most sought-after courses in the academe.
- Business analytics is the art of assembling the data
gathered through business intelligence in such a way
that it can be analyzed by people. It is comprised of the
BIG DATA AND BUSINESS ANALYTICS
- Statistical Analysis System (SAS) defines data as a term
that describes the large volume of structured and
unstructured data which can be analyzed for insights
needed for better decisions and strategic business
moves. IBM, in the other hand, refers to it as data sets
whose size or type is beyond the ability of traditional
relational databases to capture, manage, and process
the data with low-latency.
- involved machine automation to analyze data
(FOUR ASPECTS OF BIG DATA)
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VOLUME
o Volume is the base. The main
characteristics that makes data “big” is
the volume. It makes no sense to focus
on minimum storage unit because the
total amount of information is growing
exponentially every year. Volume has to
do with the ever-increasing size of the
data and databases.
o Refers size of data sets
VARIETY
o Describe the organization of the data
including whether the data are
structured or unstructured. It is
considered as the complexity of the
data in this class. A wide variety of data
is available from such sources as mobile
phones, videos, text, retail scanners,
internet searches, government
documents, multimedia, empirical
research, and many others.
o Many different forms of data
VERACITY
o Veracity refers to the trustworthiness of
the data, because it has to do with data
quality, correctness, and accuracy. This
includes provenance and curation.
Provenance is based upon the pedigree
of the data, the metadata and the
context of the data when collected.
Curation is an integral concept that
binds veracity and provenance to
principles of governance and data
quality assurance.
o Trustworthiness of data / quality of
data
o Indicate to reliability, authenticity and
legitimacy of data
Provenance – protecting security
Curation – improve wrong data like fixing errors
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VELOCITY
o Velocity refers to the speed with which
data is generated with which the data
are available and with which the data
can be processed. The velocity
characteristic of data is important in
ensuring that data are current and
updated in real time.
o Frequency of incoming data