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Articles by: Bharat Bhushan

The three V’s for successful Big Data adaptability programs

The three V’s for successful Big Data adaptability programs

Three Vs Big Data-1Research and development is part of every successful organization’s mantra and to fuel this research Big Data plays a very important role. And how Big Data analytics is used is determinant in the success or failure of an organization. In today’s time when there is so much information to process it is imperative to experiment with dynamic and variety of Big Data strategies so that you assimilate the best mix and match for sure shot success. A good mix of Big Data strategies is ruled by three major principles, the three V’s – Volume, variety and velocity which all function like a force to shoot your organization into the realms of success.

# Volume

A successful big data strategy should have perfect conscience of high volumes of data and experimentation with the products/services. If you want to go one step further, a Big Data strategy should always be coinciding with the big picture strategy of the organization itself so that after giving a shot at experimentation, the ideal plan is adopted. According to experts the best way is to run multiple strategies at one time, providing the team with whatever resources they want and hope that something really innovative comes up.

# Velocity

Time is the key to building successful products/services and velocity at which an idea is generated using Big Data is determinant factor. All that needs to be done is channelize all the ideas and suggestions into an innovation tunnel that finally filters out the winning product. This is where fast execution of plans comes in. After having a clear vision of what needs to be achieved the next step is to work on the Big Data along with the experimentation process. For this good tools in the operational systems are required so that time lag is minimal and this finally leads to an improvement in innovation cycle which leads to big ideas propping-up.

# Variety

It is a known truth that variety is the flavor of success and Big Data analytics in no different. If you have a variety of innovative ideas that could be something big, the chances are you are in fact going onto something big. The best strategy is to get an array of products/services and the potential customers to combine it with the collection of ideas in the innovation tunnel. Just to keep in mind, the best way is to get a clear picture of your USP and then get everything to revolve around it.

All these V’s help you to take advantage of Big Data in an optimal way to get competitive advantage over competitors and there is no denying that Big Data and rapid experimentation go hand in hand for successful innovation programs in organizations.

Obama demands review of Big Data industry in light of privacy

Obama demands review of Big Data industry in light of privacy

President Obama in his recent speech at the Justice Department has urged the National Security Agency (NSA) to improvise on security of networks to protect important user information.Obama Big Data

In his address Obama showed concern over security, especially because of a year full of privacy upheavals, thanks to the prominent Edward Snowden leaks, which exposed facts about NSA tapping foreign fiber optic cables and cracking encryption protocols of famous tech companies. Obama opined that such leaks have made the task of national security difficult.

Big companies likes Google and Facebook, based on recent events of information theft, have already strengthened their security systems. Understanding the position, Obama has advised the NSA to review the current role of its security apparatus and to understand how widespread future Internet surveillance programs need to be.

US government has understood the complexities of Big Data analytics and has realized the benefits enterprises have reaped with data interpretation at such large magnitude. President has ordered a comprehensive review of Big Data analytics and privacy, for this, a group of government officials will be constituted who will work in tandem with President’s Council of Advisors on Science and Technology and reach out to business leaders and privacy experts to understand how public and private sectors are facing the challenges imposed by Big Data.

The presidential working group will examine how private and public companies are collecting Big Data and how the collection of avalanche of data and its analysis for purposes besides intelligence and law enforcement is affecting privacy.

In his speech, Obama has guaranteed reforms in safeguarding the privacy of Americans by providing transparency and protecting personal information offline and online. Thus, prima-facie motive of reviewing the Big Data analytics and privacy is to comprehend how NSA can promote free flow of information consistently with both security and privacy, and to identify areas where reform in policies might be required to restrain Big Data technologies.

Identifying important information in Big Data to answer real world challenges

Identifying important information in Big Data to answer real world challenges

Over the past one year, knowingly or unknowingly, Big Data has become the biggest buzzword enterprises are finding hard to pass. Believe it or not, according to the current dependence on Big Data and its allied technologies, we can assume that Big Data is here to stay, and we all will have to use it to address our real world problems.


The way in which Big Data technologies have evolved in the real word enterprise goes on to show that even technologists and scientists who might have disparaged the word (Big Data) previously, will now be acknowledging it.

Like everything has loopholes, Big Data isn’t any different. Big Data problems are basically issues caused not because of the unavailability of data, but by the abundance of available data. There is so much influx of data that is rather impossible to know which piece of information is actually important and how different important information pieces can be put together for meaningful information.

Researching on a general way to understand complex systems and to answer the biggest question that Big Data can’t answer – ‘how to know what’s important in complex world?’ president and scientist of the New England Complex Systems Institute Yaneer Bar-Yam has devised a trick to identify patterns in largest scale of behavior. Bar-Yam has revealed his findings in the article titled “Beyond big data: Identifying important information for real world challenges”

According to Yaneer, to understand and address most social and biological challenges, it is important to frame a scientific inquiry with an idea to objectively conclude what is important or unimportant instead of amassing larger and larger sets of data.

Yaneer explains that the identified patterns of behavior determined from handful of information are the key to understanding a system and to inform how the behavior can be influenced in the future.

Yaneer Bar-Yam and his team have used the successful tested this approach by predicting various complex systems and real world challenges like market crashes, ethnic violence, food prices and many more biological and complex social systems.


Four high value use cases for Big Data, are you doing it right?

Four high value use cases for Big Data, are you doing it right?

With the ever increasing digitization, organizations are accumulating terabytes of data annually. Presently, most of this unstructured data goes unused, though it is being retained for regulatory purposes. However, the current trend of data analytic suggests that know-how of Big Data can work in favor of enterprises in the long run.

high value use cases for Big Data

Big Data will play a significant role in the enterprises; but one question that surrounds authority of big data analytics is how it can actually be used to add value.

Few managers have mastered the tact of making decisions based on data analytics, something they would do based on their gut feeling until just a couple of years back. But since the influx of data is such that tradition data management systems cannot cope up with it, managers have become dependent on Big Data analysts to turn this avalanche of data into meaningful decisions.

Having understood applicable use of Big Data to an extent, it becomes imperative to know where Big Data will work within the enterprise and what problems Big Data can address.

Here we have listed four instances, which according to experts make Big Data analytics worth the investment for organizations. These are high value use cases of Big Data as found by IBM.

1.    Exploration of Big Data

The idea of Big Data exploration is to make companies research the existing transactions and repositories using Big Data techniques. This allows companies to accumulate data from various sources stored over different places in order to create a clear picture of available data and gain insights on how to use it for value results. Data exploration thus implies finding, understanding and visualizing Big Data to improve the quality of decision making. Big Data exploration basically addresses the business problem of storage of data in different systems by accumulating it in one place for all to see and analyze.

2.    Enhancing customer knowledge

Companies use Big Data to have a 360 degree view of their customers to understand and engage more personally with them. For example, telecom companies using phone data records and social media usage to understand behavior of a customer. Enhancing customer view enables enterprises to gain full understanding of the customer and then place goods and services based on their analysis.

3.    Extension of security

Big Data analytics can be used to detect fraud by analyzing credit card transactions, or detect terrorism and cyber crimes by monitoring data processing, phone calls, social media, emails etc. constantly. With Big Data analytics fraud and cyber security can be monitored in real time.

4.    Using Big Data for operations analysis

Connected gadgetry and Internet of Things is creating new data with great speeds. Smart gadgetry is contributing immensely to the data stream. Analyzing this avalanche of data can allow companies to improve performance. The abundance of data coming from sensors, GPS devices, IT machines etc. can be analyzed using Big Data for operations analysis to allow companies to attain real time insight of what’s what.


3 Big Problems Big Data Will Probably Create in Near Future

3 Big Problems Big Data Will Probably Create in Near Future

Big Data has undoubtedly been the biggest buzzword in the past one year. One can look back at the just concluded 2013 and consider it as the breakthrough year for the term Big Data.

Big_Data challengesBig Data may not be an outright term in innovation but it certainly is in awareness. In spite of the Big Data receiving more attention in the mainstream, there are business and individuals who still confuse the term and use it inappropriately.

All things said, business enterprises are investing big time in Big Data with the motive to have the best from advanced data analytics. As mobile data, internet data and cloud data trends multiply, a need for more sound Big Data adaptation platforms such as Hadoop have been felt. Though, real potential of Big Data is still very abstract to nail down, the ramifications and business challenges it will create have already begun to show from.

Let us read on for three most important problems Big Data analytics will probably create in the near future.

  1. 1.    Legal and privacy are risk issues

Big Data can be used for good, and obviously it can be harnessed for the betterment of the society. But it can also be abused! So, not everything is sunny about Big Data. Since the accumulation of data means more threat to privacy, privacy challenges around Big Data are nothing new. It may be the dark side of Big Data but an average consumer has begun to understand the implication.

This becomes challenge since enterprises use Big Data to benefit from advanced analytics. It is believed (and explained by Sand Hill survey) that almost 62 percent enterprises use Hadoop for advanced analytics it can provide.

In 2014, Big Data with the rise of Internet of Things, leading to more mobile data, drone data, sensory data and even image data is bound to create more legal concerns over Big Data privacy. This, as explained, because consumers are becoming more aware of the real impacts of Big Data on their lives. It is therefore important for enterprises to remain ahead with compliance law and keep themselves to date with changing data protection laws.

2.    Human decision making Vs. data-driven decision making

As more businesses pursue Big Data to drive their decision making, there is soon going to be a clash in ways of doing things. As MIT Sloan School of Management research scientist Andrew McAfee points out, most management education programs train employees to trust their gut. Trusting the gut feeling is the old way of decision making, so changing it with data-driven decision making can lead to conflict. Becoming data-driven will require businesses to undergo a paradigm shift, since whether the company is data driven or not will become the competitive differentiator between successful and not so successful businesses.

3.    Big Data used for discrimination

Many research projects based on the use of Big Data have raised concerns of data being used for discrimination in addition to looming privacy concerns.

Researchers including Kate Crawford of Microsoft suggest that Big Data is being used speedily for precise forms of discrimination. We are not new to discrimination, but Big Data creates a new form of automated discrimination. Researchers suggest that social media and health care are the most vulnerable.

To safeguard against the issue of discrimination, organizations can create transparent Big Data usage policies in order to protect consumer data.


Big Data & LAPD: Predicting Crime before It Happens

Big Data & LAPD: Predicting Crime before It Happens

We are all aware that explosion in data (Big Data) gives us the ability to do a lot of different things. The potential things to do with Big Data are fantastic. Given the fact, the dynamic nature of data is fast changing the way we live our lives. When I was watching BBC’s video (placed below) titled The Age of Big Data, I was moved by the way police in Los Angeles is trying to predict crime even before it actually happens.

Big Data and LAPD

The initial segment of the video details a pilot project undertaken by the Los Angeles Police Department in collaboration with the University of California. The Foothill Division of the LAPD has been using a trial algorithm to predict crime that is about to occur in the division.

According to experts, in the last few years the world has seen more data than in all of human history, and with the same progress this avalanche of data is surely heading in the direction of becoming the greatest sources of power of this century. Thriving on this advantage of big data, officers in the LAPD are using predictive policing software dubbed the PredPol, which relies on the collection and analysis of Big Data to allow them to anticipate where crimes are likely to happen, well before they happen.

The PredPol basically works by collecting and analyzing crime data and then running it through an algorithm to generate maps. The maps inform (with bright red squares drawn on them) the police officers about where crime might take place. Police spends more time patrolling identified areas with crime risk and as presumed, prevent the crime from happening.

According to LAPD, predictive policing has assisted the department in reducing the crime rate in the Foothill Division station area.

The predictive policing software, which employs mathematics to study crime was started in University of California, Los Angeles some seven years back. UCLA mathematician and one of the postdocs on the predictive policing software project, George Mohler, has introduced an equation, which has transformed the work process. According to Mohler, mathematically speaking earthquakes and crime work in a similar way. So, if earthquake aftershocks can be predicted with mathematical model, after-crimes can also be predicted too. This Mohler concept works on the model that one crime sets tone for another crime in the area, so understanding the first the after crimes can be prevented.

Predictive policing software and Mohler’s equation can predict crimes such as robbery, car stealing etc., it can predict the areas but not who will commit the crime.

Hit the jump to see BBC’s video ‘The Age of Big Data’ to know about people mining the avalanche of big data.

Apps may minimize need for big data scientists

Apps may minimize need for big data scientists

If technology can be backed, then soon we could have a new breed of applications that would allow businesses to create their own big data apps in cloud, thus minimizing the need for IT and big data scientists. 

big data appsBig data, a word that was brushed away as a buzz word by many technology scientists has made it presence felt in a big way. Even the scientist that dared to believe it as only a buzz world have acknowledged the importance of big data for enterprises.

Considering the hype around big data, recently a survey was conducting by SAS institute. The survey concluded that there is a significant rise in demand for qualified data scientists, who can find decisive results from the avalanche of data.

The report revealed that there is an expected 243% increase in demand for big data specialists in UK alone in the next five years.

The opportunity for big data scientists is enormous, since there isn’t enough number of experts on the ground. But is this demand only hype on the big data expansion, or is it time for universities and institutes to churn out armies of qualified big data experts?

According to an article by Successful Workplace co-founder and marketing executive, Chris Taylor, on Wired, there are good enough scientists around already, and as more institutes and courses spring up, producing data analysts will be an automated effect.

An infographic – world needs more data scientists, points out that ‘data scientist job postings increased 15,000 percent between 2011 and 2012 alone’. And people seeking career in big data technologies could soon become the most sought-after people in the IT industry.

However, according to Chris Tylor, the word big data scientist has just been coined a few years back and thus there is so much demand for it. He further that numbers don’t really add up, he is off the view that data scientists have always been there in the IT industry, it just the role is more demanding this time.

According to Taylor and a point that really strikes us is that, given the exponential growth of technology, data scientists could soon find themselves replaced with new applications devised to simplify the process of big data analytics.

New apps could be launched soon, which will allow businesses, governments and individuals to create their own big data apps in the cloud with much lower number of data scientists. Citing this Taylor believes enterprises should refrain from rushing into hiring too many data scientists for now.

Via: SiliconAngle

3 ways big data analytics is changing our lives

3 ways big data analytics is changing our lives

Big data has travelled a great deal from just being a buzzword only a year back. Service providers and analytics are fully engrossed in understanding the benefits which can be derived out of big data analytics. Since big data is everything we do every day to leave a digital trace, it can be analyzed to better our lives. Read on to know how big data analytics is changing our lives with each passing day.

big data changing livesWith the explosion of data in every form, from books to maps and from calls to apps, from advertisements to social network updates and from surveys to varying trends – we are leaving more and more digital traces with every digitalizing world. Since all this avalanche of data is touching our lives every day, it has become one of the mega trends that will impact (and is impacting) everyone in one way or the other.

Listed below are a few examples of how big data analytics is already changing our lives for good.

At home and office

There was a time when nothing was possible at home without human intervention, today we have small and seasoned manufactures developing devices that help us monitor every single thing at home, from elders to pets and from appliances to door locks, everything can be monitored from miles ways just by using a smartphone and an application.

Manufacturers have devised sensors to automate lighting and your appliances at home or in offices. You can turn on the lights or the air conditioner even before you walk into the office or home. You don’t have to stand up and turn of the light or walk to the washing machine to switch it on, a smartphone with dedicated app can do it for you from the comfort of your bed.

While driving or shopping

Auto manufacturers like Ford are using big data analytics to make their future vehicles more environmental friendly. In addition, there are companies and third-party developers who have developed applications to allow smartphones to send out location information, information about how fast you’re are driving, combined with the information of real time traffic to give you the best routes to avoid traffic, or give you information of the nearby gas station, restaurant, bank etc.

While shopping, the loyalty card of the store is combined with your purchase history and social media data to offer you discount coupons and personalized offers based on your loyalty to the store. This is really making shopping more fun, economical and very personalized.

Hospitals, healthcare and fitness

Doctors are maintaining record of patients to keep track of their medical history, for better, quicker and more pin point treatment. While, pediatric units in hospitals are live steaming heartbeats of premature and sick babies in the womb. Combining the information with historically data and based on analysis, doctors are now able to detect infections in babies even before they are born.

Fitness and healthcare have become the biggest market for electronic companies. Most manufacturers, including Nike have are coming out with fitness bands, smartwatches and pedometers etc to collect daily data of a person’s physical routine, calories, sleep patterns and heart rate etc., which is then sent wirelessly to smartphone, doctors and insurance companies to devise  better and more customized healthcare programs.

Cloudera and Udacity partner to deliver Hadoop and Data Science training

Cloudera and Udacity partner to deliver Hadoop and Data Science training

Data education giants Cloudera and Udacity have formed a strategic partnership to address the shortage of big data skills by offering easily accessible online training for everyone. The partnership will offer open Hadoop and MapReduce Courses tailored to equip students with technical and analytical skills to have a great career in the emerging data market.

In the present scenario, as the amount of structured and unstructured data being generated and stored around the globe in various sectors has shot up considerably, there has been a significant rise in the enterprise demand for skilled and qualified workers.

Big data

Recently we read about Udacity introducing paid big data courses to bridge this widening gap of demand and supply, today we learn that Cloudera, a Apache Hadoop-powered market leader in enterprise analytic data management has partnered with Udacity, the online higher education provider, to deliver training on Hadoop and Data Science to anyone using Udacity’s easy to access online educational portal.

The course curriculum, which has be designed and developed by expert faculty at Cloudera University in collaboration with Udacity will equip the interested students with all the fundamental technical and analytical skills. The course is basically an introduction for Hadoop and MapReduce, understanding of which will help students kick start their careers in the every growing big data economy.

The course has been basically created to work as a support system for the shortage of skilled data professionals in the economy. With the course, Cloudera and Udacity are making available an open, state-of-the-art big data training within the reach of almost anyone who has access to the Internet and is passionate about learning the basics of Hadoop and MapReduce.

On completing this accessible course, students will have an opportunity to enroll in Cloudera University’s live professional training courses to earn certification for their professional training.

Via: MarketWired

11/22/20131 commentRead More
Ford’s new green future driven by big data

Ford’s new green future driven by big data

Ford considers big data analytics as the next frontier of innovation and productivity. It has been using big data – in and out of vehicles, to design new age eco-friendly vehicles that will help the environment appreciably.  Talking about green automobile innovations, there is hardly any manufacturer that can come close to what Ford has delivered to the environmentally conscious world in the past few years. There are many outlining things Ford has done differently to get to the pinnacle, but one thing that stands apart from the rest is use of big data to its advantage. Ford Logo Ford has invested a great deal in big data technologies and analytics. This investment has permitted the automaker’s scientists and researchers to understand realistic fuel economy targets and green routing services. In addition to learning about the availability of rare raw materials that go into the making of in-car batteries and powertrains. Ford took the decision of investing in big data on the recommendation of the company’s Research and Innovation Center, which came into existence towards the end of 1990s. The Center began providing small insight based on the information extracted from the avalanche of data. But with time, the group has begun providing broad information on climate science findings and weather trends etc. that can influence Ford’s decision making about developing new products and services. The information derived from diagnosis of big data is helping Ford achieve new standards in green automobile technology. In spite of heavy investments in big data technologies, Ford has not been able to streamline and sort all the data. This data is still stored in different pockets, which makes most information exist in isolation. Ford however is working on ways to find solutions to this. Ford’s new vehicles are producing gigabytes of data each hour. The automaker is working on ways to seek permission from vehicle owners to collect all this data in cloud data centers to analyze it and use the information to add useful green services to its vehicles. Ford also hopes to use the data collected from its fleet to help automate green routing system so that the vehicles can automatically optimize their speeds to create least impact on the environment. Ford scientists, computer modelers, mathematicians and other researchers have determined from big data analyses that Ford, in particular, is better investing and creating vehicles based on alternative engines like hybrid, all-electric, plug-in electric etc.