Report based on a Case Study

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BUSINESS
INTELLIGENCE MANAGEMENT

ASSIGNMENT-1

Assessment Marking Criteria:

Available Marks

Allocated Marks

Introduction

15

10

Organisation

20

10

Quality of Information

25

14

Grammar Usage

15

10

References used

10

6

Conclusion

15

8

Total

100

58

Executive Summary

This paper aims to discuss the
significance of big data analytics in today’s competitive world. Further it
analyzes the significance of big data in retail industry and how it facilitates
organizations to gain competitive advantage.

Big data is an embryonic phrase that
illustrates any capacious sum of planned, semi-structured and unstructured data
that has the prospective to be considered for information. Big data is the
union of supplementary data from additional sources than we have ever
perceived; it furthermore characterizes an edifying shift in the approach
retailers unite with consumers in a consequential manner. This upshot impact of
big data is what formulates it a business necessary and why retailers across
the world are leveraging it to make over their progressions, their
organizations and, shortly, the whole industry.

TABLE OF CONTENTS.doc#_msocom_1″>[MJ1]

Executive Summary
———————————————————————— 2

Introduction ———————————————————————————
4

CASE STUDY: Alana’s Retail
Clothing House ————————————— 5 – 7

PART: B – TIME WARNER
CABLE ————————————————- 8 -11

REFERENCES
—————————————————————————- 12

Introduction

Big data is an embryonic phrase that
illustrates any capacious sum of planned, semi-structured and unstructured data
that has the prospective to be considered for information. Big data is the
union of supplementary data from additional sources than we have ever
perceived; it furthermore characterizes an edifying shift in the approach
retailers unite with consumers in a consequential manner.

Retailers that are seizing assistance of
Big Data’s prospective are harvesting the rewards. They’re competent to utilize data to
successfully arrive at consumers through the accurate channels and with
messages that reverberate to exceedingly besieged addressees.

For retailers contending in an
industry with lean margins, exploiting the accurate data and smart scrutiny
will escort to superior commitment, more trustworthy clientele and an
aggressive advantage..doc#_msocom_2″>[MJ2]

CASE STUDY: Alana’s Retail Clothing House

Retailers can utilize Big Data to
elevate its business and product assortment. Big data endows with a lot of
information on consumers’ inclinations, that information is then employed to
formulate procuring pronouncements that ultimately facilitates retailers to
perk up its sales by augmenting the alteration speed of browsing to purchases,
by demonstrating those products on its website that the consumers desires. The
stratagem has moreover enabled retailers to perk up its margin by plummeting
inventory expenditure. Retailers can utilize Big Data to enhance sales. Big
data facilitate retailers to enhance their store displays by installing latest
technology and paraphernalia, and fabricate its data management competence to
formulate the promotion more tailored.

Big Data is facilitating retailers in
unraveling the Omni-channel enigma with data. Retailers with a data-centric
loom are crunching an unbelievable sum of customer actions data to comprehend
how clientele are exploring and procuring products. Insights accomplished
through scrutinizing business deal data, foot traffic and in-store depart wait
instances have escorted to alterations in marketing stratagems and in-store
campaign. Accordingly, ARCH can introduce in-store stalls, complimentary Wi-Fi,
and equipped their sales personnel with mobile devices that permit them to
serve superiorly Web-savvy clientele on the spot. Big Data can also facilitate
ARCH in augmenting personalization. Big Data will furnish ARCH the distinctive
prospect to emulate the storekeeper of yore, acclimatizing communication and
sales approaches to life proceedings and predilections. Personalization will
facilitate ARCH to fetch around eight times the ROI on marketing venture and
enhance sales by 10 percent. ARCH need to comprehend that customer is all right
with giving out individual details so long as it fetches them something.

ARCH can incorporate TALEND, one of the
big data tool as it proffers an Eclipse-based IDE for sequencing simultaneously
data dispensation jobs with HADOOP. Its tools are premeditated to facilitate
with data assimilation, data eminence, and data managing, along with subroutines
adjusted to these jobs. TALEND also retains TALENDFORGE, an assortment of open
source porches that formulate it uncomplicated to toil with the company’s
products.

Technology will furthermore develop the
customer experience as Next Best Offer (NBO) expertise becomes authenticity NBO
characterizes the convergence of synchronized data scrutiny and mobile
proffers. ARCH can incorporate NBO approach with the help of big data in order
to promote their product as well. By reaching customers at the accurate
instance, in the right place, through the precise channel, NBO furnishes
personalization on steroids and is the prospect of the industry. Harnessing Big
Data is a
substantial activity, but the induce lies in unearthing the most beneficial
clientele. Prioritizing these significantly worth clientele is indispensable to
success, particularly reflecting on that it expenses more to obtain novel
clientele than to sustain the preeminent clientele. Enhancements in
data-crunching aptitudes will permit ARCH to scrutinize the deeds and desires
that impel individual clientele, which consequences in more pertinent and
beleaguered proffers.

It
is established that up to 30 percent of the pricing pronouncements
organizations formulate every year not succeed to deliver the preeminent price.
And it’s principally worrying considering that the downpour of data currently
accessible furnishes organizations with a prospect to formulate extensively
enhanced pricing pronouncements. The numeral of client touch points remains
blowing up as digitization stimulates emergent multichannel intricacy. The
clandestine to augmenting profits precincts is to exploit big data to reveal
the preeminent price at the product—not class—level,.doc#_msocom_3″>[MJ3]relatively than sink in the numbers
downpour. For each product, ARCH ought to be competent to unearth the most
favorable price that a consumer is keen to pay. Preferably, they’d feature in
extremely explicit insights that would persuade the price—the cost of the
next-best viable product against the worth of the product to the consumer.

ARCH need to consider certain factors
such as the broader financial state of affairs, product predilections, and
sales-representative confers—expose what compels prices for each consumer
fragment and product and incorporate big data analytics to set the price. ARCH can
incorporate SPLUNK, one of the big data tools in order to set the price. SPLUNK
is a bit diverse from the other tools. It’s not precisely a report formulating
tool or an assortment of AI practices, even though it carries out much of that
all along the system. It crafts a manifestation of the data as if the data were
a manuscript or a mass of text. The manifestation facilitates associate the
data in these and numerous other widespread server-side circumstances that will
eventually facilitate ARCH in setting price. ARCH moreover needs to automate
data as it allows setting prices for bunches of products and fragments based on
data. Automation furthermore formulates it much effortless to imitate and
squeeze analyses so it’s not indispensable to initiate from scrape each time..doc#_msocom_4″>[MJ4]

CONCLUSION:

By rapidly pulling data collectively
from numerous sources, retailers can superior optimize their product assortment
and price, as well as settle on where to aim ads. Retailers can make use of
simulation models and predictive analysis in order to generate the preeminent
blueprint for its products. Devoid of proceeding internal structures, obtaining
administrative support or enlightening internally, hoping on these Big Data
inclinations is virtually impracticable. Big Data can be overpowering, and it’s
imperative that retailers comprehend what their existing systems can handle.
For data to fabricate consequences, retailers necessitate to assimilate
technology to make certain that they are obtaining insights they can rapidly
proceed upon. Once in-house resources are fixed – incorporating both human
acquaintance and technology resources – Big Data potentials are infinite..doc#_msocom_5″>[MJ5]

PART: B

Choosing The Right Big data Application

Time Warner Cable deals with lots of
data and they utilize big data tools to circumnavigate through the shifting
broadcasting landscape in order to fine-tune their infrastructure to the
altering necessities of their clienteles. The viewer metrics that they obtain
through their clienteles can furnish a lot of discernments in what their
clienteles are looking for; as well facilitate craft comprehensive customer
contours for personalized publicizing. This directs to new-fangled returns
streams for Time Warner Cabl.doc#_msocom_6″>[MJ6]e.

As Big Data enables in behavioral
analytics, with admittance to data on customer behavior, organizations can
acquire what stimulates a consumer to twig around stretched, as well as acquire
more concerning their customer’s individualities and procuring behaviors in
order to develop marketing endeavors and perk-up revenues. With services alike
HULU and Netflix contending for viewers’ responsiveness, Time Warner
accumulates data on how recurrently customers tune in, the outcome of bandwidth
on customer behavior, customer commitment and topmost usage times in order to
enhance their service and augment revenues. Time Warner Cable also fragments
its clienteles for advertisers by relating viewing behaviors with public
statistics—such as voter registration data—in order to promote exceedingly
beleaguered campaigns to explicit positions or demographics.

Tools And Techniques Used

The Jaspersoft platform is solitary of
the open source tools of Big Data for generating reports from database. The
software is well refined and at present installed in Time Warner Cable’s system
spinning SQL tables into PDFs that everybody can analyze at seminars. The
Jasper Reports Server confers software to pull up data from several of the
chief storage platforms, comprising Mongo DB, Cassandra, and Neo4j. Once the
data is fetched from several sources, Jaspersoft’s server will represent it to
collaborative tables and charts. The reports can be pretty refined
collaborating tools that assist to analyze into several corners. This is a
well-built big data tool of the software domain, and Jaspersoft is intensifying
by formulating it at ease to utilize these sophisticated intelligences with
innovative resources of data.

Time Warner Cable utilizes an enormous
assortment of data sets to generate the meticulous customer profiles. Time
Warner Cable syndicates public data arrays such as real estate chronicles,
demographics or voter cataloging records with native inspecting behaviors. This
empowers them to aid their customers to craft and convey advertising promotions
that are exceedingly beleaguered. But they do not merely emphasize on
personalized publicizing, but moreover multi-channel publicizing. With loads of
customers downloading their iPad app and obtaining knowledge from everywhere in
their network, a reliable experience is imperative. Time Warner Cable permits their
clienteles to craft promotion campaigns that concurrently beleaguered the
identical customers via cable television, mobile applications, societal media,
the Internet and other podiums. They employed big data approaches to determine
the engagement of the consumers on each distinct platform and could fine-tune
the commercial campaign on each platform if required. For the customers this
destined an unswerving promotion experience transversely all platforms, which
is enormously valued to Time Warner Cable Media’s customers..doc#_msocom_7″>[MJ7]

Business and Organizational Impact Using Big data

Time Warner Cable utilizes the
aggregated user data efficiently. With the help of this data they can enhance
their network and software design. The fetched data furnishes information
concerning how regularly customers utilize what sort of services extending from
OTT services, interactive or mobile TV through their iPad. These data furnishes
them with information concerning how bandwidth influences what clienteles and
how to handle peaks in network ultimatum. With such an enormous volume of data,
there is adequate information to descend from it. Time Warner Cable utilizes
Alteryx to assist them comprehend the entire set of data. The fetched data
allowed them to comprehend how their addressees viewed their programming as
well as how their publicizing clients accomplished. With collaborative
campaigns they have been competent to draw the places of responding audiences
to the places of the pertinent stores. Big data analytics facilitated Time Warner
Cable in executing cross-platform scrutiny in order to envisage which homes
would be engrossed in what movies through their Movie on Demand application..doc#_msocom_8″>[MJ8]This facilitated them to release the
accurate movies at the accurate instance to the precise homes, by this means
augmenting their sales. Time Warner Cable comprehends that data is inexorable
in the progression and has by now efficaciously employed it to unearth novel
returns streams, developing their marketing efforts along with their network
infrastructure.

Pentaho is another software application
employed by Time Warner Cable that initiated as a report-producing engine, limb
into big data by formulating it effortless to suck up information from the
novel resources. The unique sorting and separating tables of Pentaho are
exceedingly functional for perceptive just who was splurging the most sum of
instance at the Time Warner Cable’s website. Minimally arranging by IP address
in the log files exposed what the profound users were performing. Thus
facilitated to understand the customer’s preferences and determine the
engagement of the consumers on each distinct platform.

Big data Solutions And Its Values To Other Organization

Assimilating highly developed analytics
for big data with Business Intelligence systems is an imperative stride toward
achieving complete return on investment. Highly developed analytics and
Business Intelligence can be exceedingly harmonizing; advanced analytics can
endow with the deeper, probing perception on the data, while BI systems furnish
a more planned user familiarity.

Big Data solutions furnishvalues
to business intelligence toTime Warner Cable by enhancing product superiority
and security; product quarantines can be ascertained based on explicit,
objective data relatively than prejudiced estimations.Big Data solutions furnishes in eradicating
overlapping venture and employees support.Big Data solutions permit Time Warner Cable to obtain
novel products to market up to significantly quicker than before, a noteworthy
accomplishment with considerable consequences on profits and losses. The
synergy of business intelligence and big data endows with mutually macro and
granular outlooks of information that permits management, operators, and
engineers of Time Warner Cable to work collectively based on rapid feedback in
data-driven surroundings. The synergy of business intelligence and big data
endows Time Warner Cable in appropriate funds allocation based on novel
business strategies and course of action strategies.

Factors That Influence The Success Of Business Intelligence

The major success aspects of business
intelligence in the organization are it provides data transparency that fetches
data from diverse organizational functions to be incorporated. Another major
success aspects of business intelligence in the organization is it provides
process visibility that allows managers to perceive how progressions unfurl as
they ensue, which permits for real-time fine-tunings. Furthermore it provides
data visualization, as methodical are pertained to big data, the productivity
ought to be evaluated scientifically and characterized visually so as to permit
end users to essentially distinguish the concealed data and its significance.
This is principally imperative in light of the actuality that the data is
lively in real instance.

Conclusion:

So
a Big Data Environment consists of a number cloud-based data centers, this
sources regarding data encased with people files focuses that’ll be reviewed,
analytics software to make sense from it all, and the network in which attaches
all of it jointly. The particular network element is necessary: Minus the
risk-free high-speed on the web connectivity supplied by firms like Time Warner
Cable Business Class, Big Data would not deliver this remarkable insights it is
well-known for, like this a example: In the event you check out a flick which
has a title in which ends in several, odds are practically 100 percent that you
won’t like it very much. Don’t inquire the reason why; that’s what Big Data
research explains to us all. So keep your money—rent this DVD AND BLU-RAY.

REFERENCES

Baesens, B. (2014). Analytics
in a big data world: The essential guide to data science and its applications.

Thomas
H. Davenport and Jeanne G. Harris. (Aug 12, 2014), Analytics and Big Data: The Davenport Collection

Minelli, M., & Chambers, M. (2013). Big data, big analytics: Emerging business intelligence and analytic
trends for today’s businesses.

Ohlhorst, F. (2013). Big
data analytics turning big data into big money. Hoboken, N.J.: John
Wiley & Sons.

Foreman, J. (2013). Data
smart using data science to transform information into insight.


.doc#_msoanchor_1″>[MJ1]MS Generated Toc should have been
given

.doc#_msoanchor_2″>[MJ2]The introduction and the conclusion are key
elements in the structure of your report. They are the bookends that stop the
bits in the middle collapsing, if you like.

There are some
important things you need to do in the introduction:

· You need to define what you are going to talk about. Otherwise
your marker can’t tell if you’ve talked about it meaningfully or not.

· You need to show your marker what you are trying to do with your
topic
– your direction.

· You need to show your marker what you are going to cover (and
what you’re not, if need be).

· You need to give your marker background information necessary to
their understanding

.doc#_msoanchor_3″>[MJ3]What Business and Organizational
strategies can be achieved using Big Data solutions

.doc#_msoanchor_4″>[MJ4]Justification is required for you to
choose technology. What other Big Data Technologies available

.doc#_msoanchor_5″>[MJ5]Need to focus on all points
discussed in the report.

.doc#_msoanchor_6″>[MJ6]What
the organization do?

.doc#_msoanchor_7″>[MJ7]What other Big Data Technologies
available

.doc#_msoanchor_8″>[MJ8]How?

Practical and Written Assessment: Creating the Big Data
Strategy

Task Description

You are to write a report on how Big Data
can be used in Decision making. Select a Big Data use case/ case study and your
task includes to define the technology stack and required data and analytics
architecture including the Master Data Management (MDM), ETL/ELT/data
enrichment, data warehousing, BI, and advanced analytics requirements necessary
to support the Customer Intimacy business strategy. Your report should address:

1. Why Big Data intelligence is important?

2. How do Big Data management helps in IT
Process management?

3. How structured and unstructured data can
be merged for decision making?

4. What role social media plays in
organisations decision making?

5. Your report should consist of 3000 words
and use 5 scholarly articles.

Some of the Big Data Use Cases can be found
at http://www.slideshare.net/Dell/big-data-use-cases-36019892

Assessment Due Date

Week 11 Friday (29-May-2015) 05:00 PM AEST

Assignment 2 is due on Friday Week 11 at
17:00 AEST.

Return Date to Students

Exam Week Friday (19-Jun-2015)

Weighting

40%

Assessment Criteria

Assessment marking criteria:

1. Introduction 15%

2. Organisation 20%

3. Quality of Information 25%

4. Grammar Usage 15%

5. References used 10%

6. Conclusion 15%

  

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