Big Businesses with Big Opportunities

Nowadays Businesses are struggling with abnormally growing volumes, speed and variety of information that used to generate everyday, everyday the complexity of information generation is also rapidly growing - the term to be known for as 'Bigdata'. Many companies are seeking for the technology to not only help them to bigdata storage and process but also finding many more business insights from bigdata and growing up the business strategies with bigdata.

Arround 80% information in world is unstructured, and many businesses are not even attempting to use  that information for their advantage or not aware how to use that information. Imagine if you and your business keep afford that all data generated by you business and keep tracking and analyzing it, Imagine if know to way the handle that bigdata?

The data explosion presents great challenge to businesses, today most lack the technology and knowledge about bigdata and how to deal with it and get real business values. Many Companies are focusing on the developing skills and insights of business needs to accelerate the path of transforming larger data sets. 

What bigdata can do? Businesses are growing up with bigdata to finding more business insights and row that caries values for business with latest bigdata processing technologies like Hadoop fromework.

Its now possible to track each individual user through cell phones, wireless sensors with measurement of his interest in particular thing, where does he lives, works, plays and what is his day to day program and collect the data, analyse this huge data using bigdata processing technologies and find out the business ways with each individual user to help or make his life simpler.

Bigdata in Social Networking, day to day millions of facebook comments, updates, twitter tweets are generating and many more so using bigdata processing to find out current market trends, what people are talking about, their likes, dislikes accordingly plan our business.

Bigdata in Healthcare, every hospital or healthcare organization maintaining their historical records with patients records which may kind of bigdata so technology can analyse that past records and predict in future which patients, on what date, with the cause and what are the possible treatments for similar cause.

Bigdata in BFSI, In BFSI domain fault tolerance is the one of the most important pillar so, there are millions of daily banking transactions are there we want to find out the fake transactions, bigdata helps us even for product recommendations, transaction analysis bigdata plays a major role.

Bigdata in  ECommerce, somewhere and somehow on online shopping sites you might seen dialogs like 'you bought this you may like this', this is kind of recommendations calculated by bigdata processing technologies.

The information that we have today, about 90% of information is generated in just last 2 years, I believe after 2020 there will about 70% businesses in world would wont be having any other option. Products would be delivered to the customer if he just think buying about it, Cab will arrive when people think of going out and discounts would be already there on Shirt we might think to buy.

Social Networking Analysis

Around 85% internet users around the world (1.59 billion monthly active users in 2016, representing a 25.2 percent increase over last years figures. Eighth-ranked instagram had over 400 million monthly active accounts.) uses a online social networking portals like facebook, whatsapp, tweeter, youtube to share their experiences and to get familiar with what’s happening around us. Facebook alone reported with 1.55 billion monthly active users. As any new product lunches in any industry we can found the real experiences provided by product user on these portals. Nowadays social networking plays a very important role in Business analysis and locating business lagging and growing areas, which helps businesses to create a business strategy to improving lagging areas and maintaining the qualities of growing areas.

Apache Hadoop and Spark plays a very important role in Bigdata collection, processing and providing a nearly real time analytics out of it.

Capitalizing Bigata.!!!

90% of data created today is unstructured and more difficult to manage that generating from data sources like social media(facebook, twitter), video(youtube), texts(application logs), audio(viacom), email(gmail), and documents. As all of know the social media becoming revolutionary factor for businesses.

 

Bigdata is much more than data and is already transforming the way businesses and organizations are running. It represents a new way of doing business, creating a bright path for future business world, one that is driven by data oriented decision making and new types of products and services influenced by data. The rapid explosion in Bigdata and ways to handle it, changing the landscape of not only IT industry but all over the data oriented systems, And this data is becoming so powerful and important to drive for today’s businesses, as it contains customer insight and business growth opportunities that have yet to be identified or even no one had a idea about. But due to its volume, type and speed of change, most companies are doesn't have enough resources  to address this valuable data and get business out of it. 

Its time to get together and find out the ways and patterns from bigdata that can help us to make our lives even simpler and we have the solution(Hadoop) but need to explore it more, to focus on true growth and identifying the business opportunities.

Bigdata & TimeMachine

Powers of #Bigdata analytics, we can find out which movie gonna be blockbuster next year, not only the movie but also the future, the TimeMachine. Yesterday I saw a movie Paycheck, Michael Jennings is a reverse engineer; he analyzes his clients' competitors' technology and recreates it, often adding improvements beyond the original specifications. I think this is a best real use-case of Bigdata Implementation.

Michael creates a Time Machine with one of the his old college roommate, James Rethrick, the CEO of the successful technology company Allcom, after successful creation of TimeMachine James wipes Michael's memory, but before cleaning Michael's memory, Michael seen his future(in TimeMachine) and accordingly he sent himself a parcel(which delivers him after two years) using the things the parcel has, Michael(with lost memory) able to predict the things which he should do after two years to save himself from James.                                                      

Now we can see the things, which really correlate with Bigdata Analystics, Time Machine woks on principle of Astrology and the things we did in past gonna help us in future to survive and get the right direction, technically the data we(and off course the people who has a impact on our life) generated in our past, gets analyzed and using that analytics we are able to predict a future. Many companies now Analyzing the Bigdata generated/generating by each business vertical and designing a recommendation and decision engines to help business to survive in market.

Recommendation and decision engines, an area of predictive analytics and decision management, are going to quite active in next year, The pioneer was Amazon.com which used collaborative filtering to generate “you might also want”  or “next best offers” prompts for each product bought or page visited. 

I really appriciate your valuable comments and suggestions that guide me and you to direct our own future. Stay tunned for more updates on #TimeMachine

Bigdata in Banking Domain

As financial industries growing with evolving business landscapes and increased information and business demands, finding efficient ways to store, organize and analyze the continuously increasing hell of data and integration and analysis is really crucial job. How effectively they can make better business decisions based on the this huge amount of data in short Bigdata they processes on a daily or weakly basis will be hurdle for the industry going forward. Nowadays banking system introduced very innovative and productive banking ideas like mobile banking, SMS banking, as we are able to carry banks in our pocket and every transactions are on our fingers. As it is increasing and having many more ideas equal proportionally the risk of banking also increasing like fraud, fake transactions, fake user accounts, miss-use of banking products by thefts and hackers.

 

Banking industries are using structural data from many years ago and finding a ways to tackle with such situations but they are not that much effective and accurate, So banks also should focus on not using more data but should use more diverse and variety of data from different data sources available on network, this includes not only the banks internal transactions and profile based data but the external information such as social networking data, application logs. Previously such data considered as none of any use but banks should use this data for customer analysis and getting more business insights out of it. Simply Banks should not only use internal structured data(traditional data) but also the external unstructured data to grow with more accurate results and effective predictions.

Bigdata plays a very important role to protect and secure end users and he’s banking activities. There are 1000’s of ways to protect our customer from theft and fraud if you have amount of data. As we can do analysis of customer transactions and monitoring its regular activities like customer salary, beneficiary transactions frequency and amount of every transaction helps banking industry to analysis of customers, customer location and transaction location analysis.

Today social networking is being very important part of every business network, we can found lots of ways customer analysis and sentimental analysis against products, as product reviews are easily available on such networking sites. There are 100s of solutions based on Hadoop available to replace banking traditional crucial analytics to new real time and less time consuming solutions to developing true relationship based analytics and finding out the true business values as per customers views.

Think again in growing business perspective take a look what data (internal plus external) we have, how we use it more effectively and where should we focus more to get more accuracy to fight in competitive market for survive and grow.

Fraud Detection and Risk Prediction in the Era of Bigdata

Fraud detection and Risk predictions is a multi-million dollar business and it is increasing proportionally every year. As mentioned on Wikipedia,  the PwC global economic crime survey of 2009 suggests that close to 30% of companies worldwide have reported being victims of fraud in the past year. 

Traditional methods of data analysis and mining have long been used to detect fraud. They require too complex architecture and time-consuming computations that deal with different domains like financial, economics and business practices, and still the results produces are not that much accurate  Fraud often consists of many instances or incidents involving repeated offences using the same method. Fraud instances can be similar in content wise and appearance wise but usually are not identical.

How exactly Bigdata helps to find out the Fraud or to predict most likely risk factors?

There are thousands of data sources with too large volumes and varieties, which are ignored by the traditional fraud analysis techniques and methods in short termed as Bigdata includes social media, transaction logs, application logs, weblogs,  geographical data etc.

For an example: A guy who has taken loan from bank say 1,00,000 with returning monthly installment of 10,000. He regularly paid installments of first four months as per policy after that he unable to pay remaining installments as unavailability of funds, But he is posting his new car, or new home or foreign trip pics on twitter. The guys who is already defaulter in banks record because of unavailability of funds and keeps posting a photos his new car on twitter or facebook. So bank officials can take immediate action on it without waiting for fraud to be happen.

Second example is like, A person whose is living in India, keeps/tries withdrawing money from Delhi, NewYark, Londan, Paris everyday, we can find out his geolocation history using google maps and  will compare with transaction location, resulting into immediate action.

There are many more use cases with bigdata to find out fraud and risk analysis, Advantage of using bigdata over traditional systems is most important is high accuracy towards results and most likely predictions, ultimately because of huge data, high accuracy and likely predictions are directly proportional to the size and sources of data.

Nowadays we have technology which can take over the bigdata analytics nearly real time, without wasting much time in computations and calculations, so action can be taken prior fraud to be happen. High performance analytics is just an technology fad, With new distributed computing options like Hadoop and in-memory processing on commodity hardware, insurers can have access to a flexible and scalable real-time big data analytics solution at a reasonable cost.

What people really thinks about Bigdata?

How much do you think people are aware of bigdata world and its advantages and disadvantages, or they are just aware of it, don't know how to use it? Bigdata analytics is really a hell? Bigdata is playing a role of hero or villain in our day today life?

Yes, these are the some headlines I found on internet while I was studying for bigdata analytics. Is that bigdata analysis is really difficult job? As per my experience I dint found such hardness and difficulties while going through. "If you know how to create a bigdata, then you should know how to bring business values out of it" this is the simple line I'm following.

Just think of end user perspective, you will get known many more dimensions and directions to analyse bigdata, do it and get successful in bigdata era.

being a simple end user is not that much difficult task I think so:) 

Bigdata and Business Verticals

As we are an active part of Bigdata ecosystems, where our day to day lifestyle and activities are responsible for data generation, and systems around us can collect the data, analyse it and consume it for their business to help our lifestyle. Nowadays world gets too much interconnected because of internet and mobile devices as never been in history, each day we are creating about 2.5 quintillion( 2.5×10¹⁸) of data, its huge amount created by different verticals in the industry, This verticals using this massive amount of information to rise above the business cloud. But before using this such huge amount of information industry must aware of the real time business scenarios, in short 'Usecases' to implement the solution for analysis of Bigdata.

We'll focus on some industry key verticals/domains which are using or most likely to use Bigdata analysis. Below are the some Bigdata value creation opportunities.

Financial Services:

-Fraud Detect

-Model and manage risk

-Improve debt recovery rates

-Personalized banking and insurance products

-Recommendation of banking products

Retail and Consumer Packaged Goods Industry:

-Customer Care Call Centers

-Customer Sentiment Analysis

-Campaign management and customer loyalty programs

-Supply Chain Management and Logistics

-Window Shoppers

-Location based Marketing

-Predicting Purchases and Recommendations

Manufacturing Industry:

-Design to value

-Consumer Sentiment Analysis

-Crowd-sourcing

-Supply Chain Management and Logistic

-Preventive Maintenance and Repairs

-Digital factory for lean manufacturing

-Improve service via product sensor data

Healthcare:

-Optimal treatment pathways

-Remote patient monitoring

-Predictive modeling for new drugs

-Personalized medicine

-Patient behavior and sentiment data

-Pharmaceutical R&D data

Web/Social/Mobile Industry:

-Location based marketing

-Social segmentation

-Sentiment analysis

-Price comparison services

-Recommendation engines

-Advertisements/promotions and Web Campaigns

Govenrment

-Reduce fraud

-Segment population, customize action

-Support open data initiatives

-Automate decision making

-Election Campaigns

Data growth in each section of each vertical is viral, speed of data generation is tremendous so needed a Bigdata capability for addressing such business problems, get ready soon and make your business to capable to hit big elephant of information.

Bigdata : Impact on day to day life

Would Bigdata really impact on our day to day life? If you asked this question 10 years before, the answer  might be No, but nowadays if you going for shopping to any mall, Google maps are tracking you, your home, you rout towards a mall and suggests the similar malls near to you. You reached to mall and  went to the mobile store, shop cameras are watching you, in which section you are spending more time and suggest you similar section to shop, Now you picked up a any gadget, they will calculate your interest and recommend you the gadgets with similar features and functionalists with discounts. (As they also want to grow up with their business:) ). Result leaving from home you decided for a-gadget and you b-gadget actually because of attractive offer on it.

From healthcare, to sports, from retails stores to the e-banking, from the business to the social networking, to the way we used to go for office, big data will making big changes to the way we live our lives. Specially internet is getting more and more importance to everyones life everyday, everyone is like to sharing his information on social site and social networking sites are becoming very popular for Business world. Businesses are becoming more and more consumer centric with the help of social networking and easily available information. Businesses are using this information to find out the customer trends and business out of it. Think of this we get an reason why E-Commerce businesses are getting more and more popularity these day. How weather forecasting is always being correct, Why healthcare programs are getting arranged in particular days of year, How fraud is detected in bank between millions of transactions per day. 

This is all about bigdata, we are surrounded by it as we are responsible for generating it and Businesses are just using it for their purpose to help us, ultimately both get benefited, We are happy because of we get better and  convenient solution even if we dint thought about it and Its impacting directly to Annual Revenue of Businesses. 

Big Business with Big Opportunities

Nowadays Businesses are struggling with abnormally growing volumes, speed and variety of information that used to generate everyday, everyday the complexity of information generation is also rapidly growing - the term to be known for as 'Bigdata'. Many companies are seeking for the technology to not only help them to bigdata storage and process but also finding many more business insights from bigdata and growing up the business strategies with bigdata. 

Arround 80% information in world is unstructured, and many businesses are not even attempting to use  that information for their advantage or not aware how to use that information. Imagine if you and your business keep afford that all data generated by you business and keep tracking and analyzing it, Imagine if know to way the handle that bigdata?

The data explosion presents great challenge to businesses, today most lack the technology and knowledge about bigdata and how to deal with it and get real business values. Many Companies are focusing on the developing skills and insights of business needs to accelerate the path of transforming larger data sets. 

What bigdata can do? Businesses are growing up with bigdata to finding more business insights and row that caries values for business with latest bigdata processing technologies like Hadoop fromework.

Its now possible to track each individual user through cell phones, wireless sensors with measurement of his interest in particular thing, where does he lives, works, plays and what is his day to day program and collect the data, analyse this huge data using bigdata processing technologies and find out the business ways with each individual user to help or make his life simpler. 

Bigdata in Social Networking, day to day millions of facebook comments, updates, twitter tweets are generating and many more so using bigdata processing to find out current market trends, what people are talking about, their likes, dislikes accordingly plan our business. 

Bigdata in Healthcare, every hospital or healthcare organization maintaining their historical records with patients records which may kind of bigdata so technology can analyse that past records and predict in future which patients, on what date, with the cause and what are the possible treatments for similar cause.

Bigdata in BFSI, In BFSI domain fault tolerance is the one of the most important pillar so, there are millions of daily banking transactions are there we want to find out the fake transactions, bigdata helps us even for product recommendations, transaction analysis bigdata plays a major role.

Bigdata in  ECommerce, somewhere and somehow on online shopping sites you might seen dialogs like 'you bought this you may like this', this is kind of recommendations calculated by bigdata processing technologies.

The information that we have today about 90% of information is generated in just last 2 years and this trend is going, I believe after 2025 there will about 70% businesses in world generated by Bigdata and Bigdata oriented. Product will be delivered to the customer if he just thinking about it, Cab will be waiting for us when decided to shopping and Discounts will already there on Shirt we might think to buy.