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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.

big-data

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.

Via: NECSI

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.

 

Be Smart With Big Data

Be Smart With Big Data

smart dataSome companies get scared of big data. They think that since data is inherently dumb, a lot of it would be dumber still. But by being smart about big data, analysts can make sure that they get the most out of it. Handling big data can be a security risk and needs to be handled smartly.

The Present Way of Doing Things

Usually companies have one of three ways to handle data. They either go with the Heroic Model in which individuals take charge of requests and make decisions on their own without consulting with others. This model can work well for small businesses where individuals are usually aware of most situations across all areas of the business. But in bigger businesses, it can lead to confusion and chaos.

The Culture of Discipline on the other hand is one where individuals don’t make any decisions and follow a set of rules set by the management. Employees in this model can’t use data for their own decision making and just have to follow the processes set up for them.

The best way to handle data is to have a Data Smart Model in which data is managed on an evidence based management system. It is a combination of the first two methods and it works on a disciplined processing method but decision making is allowed at the individual level. This is the method that should be used to handle big data and it can result in smooth operation without much hassles.

How to Cultivate the Data Smart Culture

Certain steps need to be taken to create the data smart culture.

  • There should be a single source of truth. Decision making can be moved to the employee level but the guiding principles should be set from a single source.
  • Use ways to keep track of progress. Using a scorecard system, even on a daily basis, can help managers across different branches know how they are performing in relation to the other departments and they can then send in better data to record their progress.
  • Rules are important but there should be enough flexibility. Rules and guiding principles are needed but there should be flexibility to know when to bend the rules and when to break them. Sometimes what works in most parts of the country might not be best for a certain area. Businesses need to be able to adapt to such situations and change their rules accordingly.
  • Work on cultivating human resources. The people are the biggest asset of a company and it is important to educate them and provide them with the proper know-how to handle data. Managers need to be trained to educate the people working under them and give them a one to one engagement.

These steps can help businesses handle big data smartly and without much confusion. Every level needs to be trained to handle big data as the future is going to be all about big data.

9 Recent Surveys About Big Data

9 Recent Surveys About Big Data

big data surveyBig Data is the big word right now and many surveys have been conducted to find out just how big is Big Data. Take a look at the highlights of 9 such surveys to find out where big data is headed.

1. CompTIA

CompTIA, the IT association, surveyed 500 businesses and found out that:

  • 42% of businesses admitted that they have some type of big data initiative going on.
  • 93% said that data was critical for their business.
  • 18% thought that their business was ready for big data.

2. EMA and 9Sight Consulting

259 businesses and professionals were surveyed in this end user research. They found that:

  • 68% of the companies have at least 2 projects in their big data initiative.
  • 34% companies are using big data implementations in production.
  • 39% companies identified speeding operational time for analytics to be the number one driver for big data initiatives. Other drivers included competitive advantage with data use in business solutions (34%) and business requirements for higher levels of advanced analytics (31%).

3. Tech Pro Research

Tech Pro Research surveyed 144 businesses about the financial side of big data.

  • 54% have no interest in implementing big data initiatives. 8% have implemented some form of big data initiative, 12% are implementing and 26% are planning on implementation.
  • 82% of those who have implemented big data initiatives report seeing some form of payoff while only 4% believe they haven’t seen any benefits.

4. Gartner

They surveyed 720 members of the Gartner Research Circle.

  • 64% of companies are investing or planning to invest in big data.
  • But less than 8% have already deployed some form of initiative.

5. TEKsystems

They surveyed more than 2000 IT professionals and 1500 IT leaders. They found in their report:

  • 90% of IT leaders and 84% of IT professionals believe in big data as a good investment for time and money.
  • 14% of IT leaders said that big data is regularly applied in their businesses.
  • 66% of IT leaders and 53% of IT professionals said that their data is stored in disparate systems.
  • 60% of IT leaders said that their is no accountability for data quality.
  • At least 50% of IT leaders were not sure about the validity of their data.
  • 81% of IT leaders accepted that they do not have the adequate manpower with the right skill sets to implement big data initiatives.

6. Bain

Bain studied 400 large companies and found good results about big data.

  • They found that the companies that have big data analytics capabilities were outperforming their competition.
  • They were twice as likely to have better quarterly financial performance.
  • Five times more likely to make faster decisions.
  • Three times as likely to execute decisions.
  • And twice as likely to use data in their decision making process.

7. BCG

BCG surveyed 10,000 consumers in 20 countries worldwide. They found that:

  • 75% of consumers are concerned about privacy of their data.
  • The young generation is just as concerned about privacy as older generations.
  • Consumers will allow use of data as long as they trust the business with their data.

8. IBM

IBM studied 900 businesses from around the world. They found that the companies that were outperforming their peers were:

  • 166% more likely to make decisions based on data.
  • 2.2 times more likely to have a clear path for big data analytics in their organization.
  • driven by growth as the main source of value from data analytics.
  • measuring the impact of investment in analytics.

9. Forbes Market Insights

Rocket Fuel sponsored this study by Forbes Market Insights of 211 senior marketers.

  • The marketers that used big data at least half of the time in their campaigns said they exceeded their goals 3 out of 5 times.
  • Those who used data less than half of the time achieved similar results only 1 out of 3 times.
  • 92% of companies who used big data, exceeded their goals and only 5% fell short.

From such surveys it is clear that it is still early days for big data. Those who have taken the initiative have found dividends in big data while some still remain skeptical. Information taken from the article on Forbes.

IT Companies Should NOT Hesitate to Milk Big Data

IT Companies Should NOT Hesitate to Milk Big Data

Big Data is being utilized by businesses in every field to answer questions and predict the future with more reliability than the traditional methods that were used before big data analytics came along. It is surprising that IT isn’t utilizing big data as much as they should.

IT, like most other businesses, needs to predict the future in terms of surprise requirements, new opportunities and threats and worst case scenarios. A lot of these questions can be answered by using big data analysis. All parts of IT; operations, security, customer service, forecasting etc. can benefit by using big data.

IT has access to a lot of data in terms of logs, traces, emails, counters, feedback, polls etc. that it can use to solve critical problems related to predicting future scenarios.

Big data

The Usual Solution

The solution that IT has been using till now is to purchase packaged applications for their services and in case of a unique solution, they tend to integrate their own solutions to the applications with the help of their unique business know how.

The new idea is to use all the data collected, both internally and externally and apply big data analysis to it to move on to the next level.

It’s Already Started

A few IT companies have already started utilizing big data because they see the potential behind it. EMC IT is using big data to analyze their data and predict potential issues with their app delivery system.

Some companies are starting to use the huge amount of data they have collected for security. Already certain applications exist that analyze security data but by creating their own applications companies can come up with better solutions for their unique security requirement.

Companies can also use big data to forecast how much money they’d need to spend in the coming year on upgrading their capacity to store, compute and analyze data.

IT Always Leads the Way

It has been seen that the IT is always the one that takes on new technologies and systems and gains enough domain expertise in the area to help other branches of business later.

The data already exists and the tools for analysis of this data also exist. It’s just a matter of time before all IT companies start using big data in new and creative ways to solve unseen problems and predict the future. It is easy to get started and a lot of money is not required to get into big data. We are going to see a game changing utilization of data in the near future, just as soon as the IT sector wakes up and smells the data.

Apple’s Acquisition of Topsy Could be a Great Move

Apple’s Acquisition of Topsy Could be a Great Move

Apple has recently acquired Topsy Labs, a San Francisco based analytics firm, for $200 million. The Indian owned firm specializes in analyzing tweets and has an archive of over 400 billion tweets, starting from 2006 when Twitter was first launched. It also has a searchable database of all tweets ever sent, something that even Google doesn’t have, because of its partnership with Twitter.

topsyTopsy Labs was formed in 2007 by Vipul Ved Prakash, Rishab Aiyer Ghosh, Gary Iwatani and Justin Foutts. It collects and analyzes huge amount of data generated everyday on Twitter and allows its customers to make sense of all the noise. This buy could be a great move for Apple depending on how they use Topsy.

Apple hasn’t commented on what they intend to use Topsy for, but it is clear that with such a powerful tool, they have a lot of opportunities in front of them. Kristin Huguet, a spokesperson for Apple Inc, confirmed the acquisition but did not reveal Apple’s plans for Topsy.

“Apple buys smaller technology companies from time to time, and we generally do not discuss our purpose or plans,” Huguet said.

The Opportunities for Apple

The most obvious use is to get feedback about their products and services and market their products in a better way. They could also analyze key players on social networks and use them to spread the word about their services.

dataTopsy has developed many state of the art systems to deal with such huge amount of data obtained from social networks. They have filed patents for many systems and methods for customizing filtering and predictive crawling of social media. Apple could use this technology to analyze the data that they have been collecting through their devices and app store.

They could use it to improve the search feature of Siri, providing users with better search results by analyzing what recommendations their friends made on Twitter. Twitter is the most used social media platform on smart phones and getting access to all of its data along with the ability to analyse it, is definitely a great opportunity.

Competing with Google

Google has been trying to make their search engine more personalized based on data gathered from social media. Now Apple has a very strong tool to do the same. Both companies are spending big money on acquisitions in order to maintain their edge in the rapidly changing world of information technology. Apple spent $496 million in their last fiscal year on acquisitions while Google spent a whopping $1.4 billion.

Korea opens first big data analytics centre

Korea opens first big data analytics centre

To bring its technology sector at par with the global technology giants, South Korea has set up country’s first big data analytics center. The big data analytics centre will enable researchers and businesses to refine and analyze big data for their projects.

South Korea’s ministry of Science, ICT and Future Planning have worked in collaboration with National Information Society Agency (NIA) to open ‘Korea Big Data Centre’ (KBiG), the country’s first big data analytics centre in the NIA building.

Big_Data_center south koreaThe Ministry of Science informed that the Korea Big Data Centre is set up to promote data analytics in government and private sector with the intention to transform Korea into a data driven creative economy.

The new centre will allow all kinds of researchers, businesses and hospitals etc., to process and analyze the avalanche of data for their products.

The aim of the center is to bring the Korean industry at par with the global technology giants like Google and Amazon, who have gone ahead by 3-5 years by properly enrooting their big data.

Korea Big Data Centre is primarily created for small and medium size businesses, universities and citizens who wish to analyze their big data to find answers to their research or business issues.

Until the opening of KBiG, universities, research institutes and businesses in Korea were paralyzed when it came to securing and analyzing big data. They had to rely on limited IT infrastructure, they could create by themselves. Korea Big Data Centre will now provided the much needed shared service that everyone will benefit from.

According to an official from the Ministry of Science, the new centre is expected to be a “test bed” for big data analytics to foster research at universities. This, he says, is a basic solution for everyone to use the services in order to analyze big data.

Via: FutureGov

11/27/20131 commentRead More