Report based on a Case Study

| June 9, 2016

Question
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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