Has your company recently launched new product or company is concerned with the poor sales figure or want to reach new prospects and also reduce the existing customers' attrition, then this thought evoking short hand guide is available for you to explore.

1. IS YOUR COMPANY BRACED UP FOR HANDLING BIG DATA?
Version: 1.0
Date: 01st December 2014
Author: Himanshu Agrawal
Image Credit: http://www.exelanz.com

2. INTRODUCTION ..................................................................................................................................................... 3
WHY BIG DATA MATTERS A LOT FOR BUSINESS? ................................................................................................... 3
WHAT ARE THE CONSEQUENCES IF COMPANIES MISS THE OPPORTUNITY TO ANALYZE THE BIG DATA? ............... 5
HOW COMPANIES CAN EFFECTIVELY UTILIZE BIG DATA? ....................................................................................... 6
1. Organizational Decisions must be derived on Fact, not Instinct .................................................................. 6
2. Understand your Customer .......................................................................................................................... 6
3. Forecast with Greater Accuracy ................................................................................................................... 7
CONCLUSION: ........................................................................................................................................................ 7
ABOUT AUTHOR .................................................................................................................................................... 8

3. Introduction “Big data is like teenage sex: Everybody wants to talk about it but very few really know how to do it. Everyone thinks everyone else is doing it, so everyone claims they are doing it.”
Well, As per Rebecca Shockley, Global Research Leader for Business Analytics at the IBM, “Big data is quite simply data that cannot be managed or analyzed by traditional technologies. So what is considered big data for one company may be different for another company. ‘Big’ doesn’t have to be really that big; it’s just bigger than what you’re used to dealing with.”
For the past few years, Big Data is the biggest buzzwords around and that forced the companies to think whether they should adopt it or not? Before just going into deep dive with Big Data, let’s try to analyze below questions:
1. Has your company recently launched new product across multiple regions like mobile or television and your company is excited to canvass the feedback of these products being used in target audience?
2. Your company already has lots of products in its inventory but not sure about how to reach new customers/prospects or how sales figure can be improved for the products which are idle in inventory for quite few weeks or months.
3. You are associated with a telecom company and marketing head is worried about the customers’ attrition in past few months and so you need to precisely analyze the customer churn. You would have to exactly analyze your clients’ preferences, call drop rates and sentiment analysis etc. to provide better customer satisfaction.
4. You are a large financial service company and want to proactively analyze any fraudulent transactions in credit/debit cards.
5. You are a large fitness chain of health clubs and want to analyze the fitness data generated from various connected and wearable devices to provide members’ better personalized recommendations regarding their health, diet plan etc.
These are few of the examples which are having potential use cases for big data. If your company is also having some similar scenario, then there might be chances your company is already addressing big data otherwise it is the high time to consider big data solutions to gain better sales figure, reaching out to new customers and provide increased customer satisfaction.
Why Big Data matters a lot for Business?
"The goal is to turn data into information, and information into insight." – Carly Fiorina, former chief executive of HP.

4. As data is generating at very high pace, organizations need to process and analyze this data and attain the insight from this data. Today, businesses are witnessing exponential data growth and big data analytics are invariably becoming inevitable for them.
Many companies are generating sensor-based data as well, which needs technology that can help provide cross-functional value across departments.
The organizations, who will pro-actively take the measure to analyze this big data will grow, others will have to survive or will be delayed in the race.
With the right analytics approach, business leaders can unlock insights from big data that lead to profitable business decisions.
A number of industries—including health care, the public sector, retail and manufacturing are getting benefitted from analyzing their rapidly growing mounds of data.
Lets’ look at few examples, how companies are gaining the significant opportunity using Big Data solutions like Hadoop, NoSQL and Enterprise Data Warehousing:
1. By integrating Big Data solutions, the major logistics company US Xpress is able to store enormous amount of sensor and geo data from thousands of trucks and with the intelligence they mine out of this, saves them $6 million/year in fuel cost alone. [Source]
2. The multinational department store chain Sears, were able to surpass its initial target to reduce mainframe costs by $500,000 per year while also delivering 20 to 50 to 100 times better performance by adopting Big Data solution of Hadoop. According to Sears’ CTO, eliminating all of the mainframes in use would enable the company to save "tens of millions" of dollars.[Source]
3. As per Major Telecom Equipment Company Nokia, Big Data analytics is absolutely mission critical for them. Using massive scalability and flexibility of Hadoop, Nokia is able to push the analytics envelope, creating 3D digital maps that incorporate traffic models that understand speed categories, recent speeds on roads, historical traffic models, elevation, ongoing events, video streams of the world, and more. [Source]
4. Nextbio is dealing with stunning large volumes of multi-terabytes of genome data by using Hadoop map reduce technology. Hence, It was able to reduce significant cost for server, storage, network infra and power and able to provide faster ROI for customers.[Source]
5. A Major retail bank made it able to quantify substantial asset risk and comply with regulatory reporting by analyzing trillions of records using Big Data solution of Cloudera and Datameer platform. [Source]
Image Credit:http://www.techrepublic.com/

5. 6. By applying accurate predictive analytics of Big Data, News Agencies were able to predict very precise pre-poll election result in last United States Presidential election.[Source]
7. Using better integration of big data solutions into healthcare, US economy would be able to save $300bn a year as per the latest statistics. This would in turn can reduce the healthcare cost of every US citizen by $1,000 a year. [Source]
8. US Retailers could increase their profit margins by more than 60% through the full exploitation of big data analytics. [Source]
These are just few scenarios where significant opportunities have been derived from big data. Therefore real-time big data isn’t just the process for storing Petabytes or Exabyte’s of data in a data warehouse but also the capability to make more valuable decisions and take worthwhile actions at the right time.
It is about detecting fraud while someone is swiping a credit card, or triggering an offer while a shopper is standing on a checkout line, or placing an ad on a website while someone is reading a specific article. It is about combining and analyzing data so you can take the right action at the right time and at the right place.
What are the Consequences If Companies miss the Opportunity to Analyze the Big Data?
“Does the data in your organization have patterns? If no, your decisions can have random output. Do you drive your vehicle randomly too?”
A recent survey finds out that only one-quarter of companies equipped to meet their anticipated analytics needs in the future.
If an organization needs to grow, then it is evident that the business or strategic decisions must be established on the accurate analysis of various data inputs collected from multiple sources. Business can’t wait to take decision for the completed and structured data. It needs to take decision by analyzing huge volume of unstructured data. Business Houses ignoring unstructured data are doomed.
Research shows that higher performing organizations collect and leverage data at every stage of their strategic initiatives. Companies that miss the opportunities hidden in their data risk being left behind. Poor data across businesses and the government costs the U.S. economy $3.1 trillion a year. [Source]
Today, even the most basic items like electrical appliances, water heaters and mechanical equipment’s can generate and provide data. While the Internet of Things is giving rise to massive sources and quantities of data, new big data technologies are emerging that help uncover crucial business insights from the data.
Companies not implementing big data solutions are missing an opportunity to turn their data into an asset that drives business and a competitive advantage.

6. How Companies can effectively utilize big data? Big Data provides businesses with a means of identifying customer requirements, preferences, likes and demands – and in turn, how to satisfy these various needs, traits, quirks and particularities.
To gain competitive advantage over peers, it is evident to nicely capture, process, parse and analyze this big data and provide customer centric recommendations to improve sales, maximizing profits and lowering the marketing costs. Ultimately, no amount of data is useful if there isn't a means of analyzing it, making recommendations based on the data, and measuring the results of steps taken. Well, however the question remains, how best to make use of Big Data? The answers to that question are numerous and varied, but in general, businesses would be well-served following these basic principles:
1. Organizational Decisions must be derived on Fact, not Instinct "Without data, all you have is an opinion" Success of any organization lies into the right decision taken at right time. Big data analysis can help to suggest fact based recommendations regarding company business strategy, pricing decision and talent requirement thoughts based on hard numbers, not on the hunches. As soon as a company realizes this, it can start adopting concrete steps to address legitimate and documented needs – customer needs, internal needs, logistics needs and more. The perfect example of this can be observed into sales decision of particular product. Let say a company is not sure about to continue the particular product or service, based on lower sales numbers. So company can collect customer feedback from different data points like Social media (Facebook, twitters etc.) and public platforms like Wikipedia, IMDB etc. Based on the parsing and analysis of this vast information, company identifies that on these platforms demand is high of product despite lower sales numbers. Perhaps this implies that the product is poorly marketed or above market-acceptable costs. So company can strategize to launch new mobile app or update the existing app and more focus on marketing and pricing strategy to reach those prospect online customers through the innovative features of new or enhanced apps. Big Data can provide these data insights but being able to make the connection and determine how to solve the problem will be what leads to success.
2. Understand your Customer Enhancing the customer retention and optimizing the customer experience and engagement are most prevalent drivers for several product or services industries.

7. Organizations facing these concerns can conduct the survey with below queries:
• What is the current level of satisfaction of customers with specific services?
• What are the major domains of complaints that customers are encountering and how this behavior is changing over time?
• What are the some key customer segments that provide higher potential upsell opportunities?
• What are the most frequent issues that lead to customer churn?
There are couples of resources through which company can address these customer concerns and sentiments like sending survey emails to subscribed or lead customers, customer satisfaction surveys, call center notes and other internal documents.
Big Data analytics can help to identify and address causes of customer dissatisfaction in a timely manner. It can help to improve brand image by proactively solving problems before they become a big sticking point with customers.
To calculate the true holistic understanding of the customers, organizations need to correlate the data generated from the above sources with behavioral and psychographic data collected via social media platforms.
3. Forecast with Greater Accuracy Enterprises can gain significant long-term benefits by doing accurate predictive analytics to their operational and historical data. Predictive analytics practices can help companies in several key areas like minimizing risk, identifying fraud and pursuing new revenue opportunities. It helps companies to fine-tune their ability to identify risk in areas such as loan and credit origination or fraud in areas such as insurance claims. Importantly, by embedding predictive analytics into operational data, companies can put themselves in a better position to identify new revenue opportunities. For example, by looking at a customer's historical purchase patterns, companies can make reasonable predictions about the kinds of promotional offers and coupons that are likely to resonate with that customer. So the major benefit of this accurate forecasting is, of course, to make more informed decisions in the present that could be game-changer for the company in due course.
Conclusion: “Information is the oil of the 21st century, and analytics is the combustion engine.” – Peter Sondergaard, Gartner Research There exist numerous opportunities for the organizations with use of big data. The large amount of data flowing in from various resources is making information highly valuable. Nowadays, companies use

8. efficient data collection and predictive analysis to formulate more cogent business strategies. Some organizations are already fetching the returns from it and other companies would also join the band wagon sooner or later. As per Angela Ahrendts, CEO of Burberry: "Consumer Data will be the biggest differentiator in next two to three years. Whoever unlocks the reams of data and uses it, strategically will win." From an entrepreneurial perspective, this is just too good to miss. Meanwhile, Big Data isn’t just for big business. With the number of companies that now offer Hadoop as a service, any size business can afford to implement big data. It no longer takes a complicated and costly infrastructure to get it up and running. Additionally, with big data in the cloud, companies have the flexibility to scale their storage to whatever their needs may be. They don’t have to waste money on the storage that they might not be using. Also, Big Data services in the cloud generally only charge for the services you actually use. No need to stress out about high prices on products that won’t be used.
About Author Himanshu Agrawal is a Senior Technical Lead at 3Pillar Global. He brings with him rich experience in designing/developing enterprise wide web applications and platforms. He has expertise on complete J2EE stack and open source technologies and has been majorly involved in designing/developing products for Healthcare, Finance, Global Trade Management, and Content Management Applications. His area of interest is in Big Data technologies including Hadoop, Pig, Hive and NoSql databases etc. He likes to be driven by challenges and is passionate about learning emerging technologies/domains with prime area of interest being web platforms. Prior to joining 3Pillar Global, he has worked for various product and service based companies including RSystems, Syntel and Metacube. To know more, you can connect with him on LinkedIn.