Cloud Computing connects large pool of resources through private or public network and this technology makes infrastructure planning easier. Cloud Computing provides dynamically scalable infrastructure for cloud based applications, data, and file storage. Businesses can choose to deploy applications on Public, Private, Hybrid clouds or the newer Community Cloud. Public clouds are provided to the public by a service provider who hosts the cloud infrastructure. Public cloud providers like Amazon AWS, Microsoft and Google own and operate the infrastructure and offer access over the Internet. With this model, customers have no visibility or control over where the infrastructure is located.All customers on public clouds share the same infrastructure pool with limited configuration, security protections and availability variances. Private cloud is cloud infrastructure dedicated to a particular organization. Private clouds allow businesses to host applications in the cloud, ensuring data security and control, which is not ensured inn a public cloud environment. Hybrid Clouds are a composition of two or more clouds (private, community or public) that remain unique entities but are bound together offering the advantages of multiple deployment models. A community cloud is a multi-tenant cloud service model that is shared among several organizations and governed, managed and secured commonly by all the participating organizations or a third party managed service provider. To know more go to: https://blog.zopim.com/2013/11/20/3-ways-analytics-transforming-customer-service/

The strength of social media is that it can answer questions you had not asked and perhaps had not even thought of. Its weakness is that it can't answer most of the questions that market researchers' clients ask. There have been some successes and a couple of examples are

• Assessing campaign or message breaks through.

• Identifying language, topics and ideas.

• Outside market research.

But the key problems are:

• Most people do not comment in social media, and most of the comments are not about clients’ brands and services.

• Social media deals with the world as it is, brands can’t use it to test ads, to test new products and services, or almost any future plan.

• The dynamic quality of social media means that it is very difficult to compare two activities. Thus the accuracy of social media measurements become limited.

• Good social media usage requires people, which tend to make it more expensive and slower.

• It is very difficult to attribute the comments to distinct groups.

Read more at: 

http://www.greenbookblog.org/2014/04/25/why-has-social-media-analytics-met-with-limited-success-in-market-research/</a

Social media defines an array of Internet sites that enable people from all over the world to interact. We all have our own reasons for using social media. What is interesting is that the researchers found that people who are more anxious and socially insecure are more likely to use the social networking site. In 2012, Anxiety UK found that 53% of participants said social media sites had changed their behavior, while 51% of these said the change had been negative. Many people using social networking sites make comparisons with others, which can lead to negative emotions. Furthermore, the survey revealed that two thirds of participants reported difficulty relaxing and sleeping after they used the sites, while 55% said they felt "worried or uncomfortable" when they were unable to log onto their social media accounts. Although many studies point to the negative impacts of social media on mental health and well-being, some researchers say they could have the opposite effect. Social networking sites could be a useful tool in identifying individuals with mental health issues. A study, from the University of California San Diego, suggests that using social media may even spread happiness. They found that happy status updates encourage other users to post happy status updates themselves. Overall, it appears that the exact effects of social media on our mental health and well-being remain to be seen. Read more at:

http://www.medicalnewstoday.com/articles/275361.php</a

Business leaders understand the strengthg and usefulness of managing the improvement of business results through process improvement teams. There is no better approach to process improvement than the application of Six Sigma tools and methods. Moreover, the disciplines of project management and Six Sigma are substitutes but they are complementary. The similarities between project management and Six Sigma include:

• Utilization of established project management techniques to efficiently manage a project and project teams.

• Necessity of proactive project sponsors or champions to help ensure project success.

• Life cycle and phases.

• Need for a well-experienced project facilitator to lead the effort.

Six Sigma adds additional dimensions to project management: 

• Powerful set of process improvement tools.

• Statistical and process thinking to understand and improve results.

• Understanding of variation, to eliminate knee-jerk reactions.

• Quantitative analysis for base decisions on facts and data.

Read more at: 

http://www.microsoft.com/project/en/gb/six-sigma.aspx

The year 2014 tends to be an important year where technology discovery will further build a future in which companies make data-driven decisions. The Top 5 data analytics trends that companies believe are going to rule the industry are:

• Data Visualization Goes Mainstream-Visual analytics allows business users to ask interactive questions regarding their prepared data sets which makes the whole process engaging.

• Mobile Data Marches to the Top- The top priorities for companies will be defining mobile metrics that matter, understanding mobile technology and collecting and analyzing mobile data.

• Analytics in the Cloud Grows Up- Innovations like cloud data warehouse platform from Amazon will gain importance  enabling fast and secure solution at very cheap prices.

• Predictive Analytics Takes Center Stage- the increasing demand for business users to examine data for decision making, provide the base for predictive analytics to gain significant ground in 2014.

• Internet of Things -- It’s everywhere! - Companies that are doing a great effort in product design and development will emerge as the first winners as they adopt through innovative marketing.

Read more at: 

http://tdwi.org/Articles/2014/01/28/5-Data-Analytics-Trends-2014.aspx?Page=1</a

Today companies have vast amounts of informations available to carry business moves. The General Mills and IBMs of the world now are using complicated-and expensive-Business Intelligence (BI) systems that can combine data together from a multiple operating systems and generate best reports that highlight not only what has occured and what is happening, but also what will probably happen. Can Small Business Benefit From Business Intelligence Software?

• It can help a small business compete with larger competitors or enhance market share.

• Vendors are getting experienced at making software that’s affordable.

• BI vendors are starting to educate a younger crowd. 

• The cloud now puts non-IT users in the driver’s seat. 

• Before investing in BI tools, one must know what answers they are looking for.

• Forget about using BI software if one don’t have access to best operational data.

• BI is increasingly going mobile. 

 Read more at:

http://www.inc.com/articles/201109/business-intelligence-software-for-small-business.html

Master Data Management (MDM) programs often start with the analysis of the available technology and products but not the business problem they tend to solve. Three primary categories of MDM benefits are operational efficiency, better business intelligence, and regulatory compliance. The following are ten things one can do now to prepare the organization for  MDM initiative:

• Set goals and success criteria.

• Prepare a business case.

• Build a governance process.

• Choose the first subject areas to attack.

• Carry a data inventory.

• Recognize executive sponsorship.

• Identify business champions.

• Set up an educational forum.

• Educate yourself about products and approaches.

• Develop a business model of the data to be handled.

Read more about this article at: 

http://esj.com/Articles/2008/06/25/Ten-Tips-for-Master-Data-Management-Success.aspx?Page=1

Analytics and big data are on the verge of scoring major points in sports. The following are eight ways data analytics can improve efficiency, accuracy and profitability in sports:

• Better Precision in the Strike Zone- In baseball, Pitchf/x technology from Sportvision has been set up in Baseball Stadiums to have a track on pitches.

• More Resources for Analytics Buffs- Statistic enthusiasts have a series of websites they can visit to see different aspects of specific games and plays.

• Data From Wearable Technologies- Adidas has a system called miCoach that works by attaching a wearable device to the players's jerseys to gather data.

• Live on the Field Data Collection- A Company; SportVU has six cameras in each NBA arena which gather data on the movements of the basketball 25x per second.

• Predictive Insight into Fan Preferences- Analytics can advance the sports fans' experience as teams.

• Career Opportunities for the Blended Sports Fan and Numbers Whiz- Bryan Colangelo, former president of the Toronto Raptors, says "There are mountains of opportunity in analytics now"

• Influence Coaching Decisions- Data analysts could help to transfer the most requisite data sets to coaches for better outcomes on the field.  Read more at:

http://www.cio.com/article/2377954/data-management/8-ways-big-data-and-analytics-will-change-sports.html

20-30% of the business decisions really need the use of advanced techniques like predictive analytics.   70-80% of marketing decisions can be judiciously carried with simple analytics techniques. A CMO broadly expects 3 key outcomes for his business:

• Bring more “future” customers in the most cost-effective manner.

• Convert those who come to the door into customers.

• Maintain the current customers “buying.”

Predictive Analytics need advanced skills and constant maintenance. A product manager or an operations manager equipped with the right “Data to Decisions” framework and easy access to data can optimize 80% of their daily workflow on their own, without having to depend on little and costly analytics resources. For 20% of decisions, where the potential ROI justifies the use of advanced techniques, they can work with their analytics counterpart. In summary, a smart CMO knows that a marketing team equipped with a “Data to Decisions” framework and easy access to data without the company of a data science team would emerge much better than a marketing team lacking data skills supported by a large data science team.  Read more at: 

http://www.forbes.com/sites/piyankajain/2013/05/26/the-8020-rule-of-analytics-every-cmo-should-know/

Big data analytics has attracted the interest of the security community for its promised ability to correlate and analyze security-related data judiciously and at unprecedented level. New big data applications are beginning to become part of security management software because they can help prepare, clean and query data in incomplete, and noisy formats efficiently. Fraud detection is one of the best uses for big data analytics. One of the main results from big data technologies is that they’re supporting a large variety of industries to build affordable infrastructures for security monitoring. In particular, new big data technologies are enabling the analysis of large-scale, heterogeneous datasets at unprecedented scales and speeds. Now big data tools are improving the information available to security analysts by consolidating, correlating and contextualizing diversified data sources for longer periods of time. Big data tools are also particularly suited to become basic for advanced persistent threat (APT) detection and forensics. Hence big data is changing the landscape of security technologies for network monitoring and forensics.  read more at: 

http://www.infoq.com/articles/bigdata-analytics-for-security

Growth in social media networking with increased logging into Facebook and twitter accounts has been accounted to be about 37 % in 2013 according to trends in digital marketing, media and commerce. Though the global rate might be less the growth rate in India of social networking has been high especially in urban areas. India has recorded the second highest number of Facebook users and is likely to become the largest number of Facebook users in 2016. A survey by Internet and Mobile Association of India found that there has been a 50% increase after 2012 in Facebook use, 33 million in Twitter and 20 million on LinkedIn. Social media being the next being frontier is definitely unavoidable and has become an imperative part of a holistic marketing strategy benefiting businesses reducing costs and improving customer services. Corporate and B-schools give latest promoting strategies and marketing strategies through social media. Read more at: http://www.hindustantimes.com/technology/socialmedia-updates/india-records-highest-social-networking-growth-study/article1-1244761.aspx 

There has been a transformation and a creation of positive impact on the social and economic relationships across the stakeholders. Thus companies today need to treat Big Data and analytical tools as an asset. However data presents inherent challenges in adoption. Companies are grappling on how to contextualize information, and presenting the data in a lucid manner is another challenge. Without making inroads into old processes and investing in the right kind of people to tap into data's hidden potential, a company can never fully realize the scope data offers. According to several research studies, Big Data is a top business priority that can transform processes and organizations. Thus a good data miner always finds a right balance between machine and man. Data visualization is another important tool to help management and reflect how businesses and markets are changing. To know more, please follow:

http://www.informationweek.in/informationweek/perspective/297284/-challenges-opportunities

Nowadays we are witnessing an enormous data explosion which is set to continue and even accelerate. The volume of data is growing at a very high velocity and is rapidly becoming more varied, complex and less structured. As a result, the word Big Data has grown strong on the mind of every business leader who wants to extract critical insights and business benefits from data. Many organizations are planning to implement Big Data related initiatives or have got them already. However most organizations lack an articulated strategy for Big Data execution. Thus there is a strategy gap between high potential and risk about investing in Big Data initiatives. Although, the essential mix of technologies may deliver on the promise of Big Data, what leaders must choose and incorporate for interlocking the set of available data sources and technology is a specific business goal which makes the initiative unique. In response, Big Data providers have prepared a strong ground through the use of cloud computing at the core which address these issues. Organizations can analyze the feasibility and cost of investing. Termed as "Big-data-as-a-service" (BDaaS), it basically refer to services that provide analysis of enormous or complex data sets, typically over the cloud platform as a managed service. The adaptation of Big Data on above grounds precedes with Hadoop which was a major stepping stone, but it still has its own limitations, specifically for Small and Medium Businesses (SMBs) that do not have the resources to create a Hadoop infrastructure in house. Thus, on a conclusive note, It's difficult to predict which Big Data solution businesses will freeze on, but having a majority of Big Data service providers now providing a version of their platform in the cloud, it will emerge a safe bet for SMBs to venture, in wherein cloud will play a major role in building Big Data an integrated part of their business strategy. Read more at:

http://www.informationweek.in/informationweek/perspective/297257/cloud-leveling-playing-field-smbs

There is a blending of the system administrator and network administrator roles as a result of emergence of cloud computing and software defined infrastructures. Historically, the demarcation of the two, happened at the RJ-45 socket on the NIC. Anything that involved the cable, switches, routers etc. was not the concern of the sysadmins. Likewise, if the light was blinking on the NIC, anything happening inside the box was not the problem of network admins. Now, sysadmins, particularly application administrators, must now be cognizant of network technologies and operations, network admins who want to keep networks in top shape must now have an awareness of what application traffic is flowing across the network and how to design and implement networks to support those needs. Thus the roles are merging and in the near future, they both can be together known as "cloud administrators". Read more at: http:

http://www.informationweek.in/informationweek/news-analysis/297170/rise-cloud-administrator

Social media is an ever changing scenario where social media marketers are increasingly using predictive analysis to ensure longevity. Various brands are using predictive analysis technologies to trawl through social media chatter to identify upcoming trends. It will also ensure that your brand be one of the first few to take advantage of the trend and gain maximum exposure. Your social media campaigns will also be much more refined compared to those of brands that don’t use predictive analysis. With predictive analysis, your brand will be able to pick out the right news, items, etc. that could become the next big thing on social media landscape, giving you ample time to prepare. Now smart brands are realizing that predictive analysis can be used in social media marketing to understand what consumers are looking for. Predictive analysis tools ensure that brands understand consumer behavior on social media.

Read more about this article at:

http://www.simafore.com/blog/bid/205332/How-Predictive-Analytics-Can-Boost-Your-Social-Media-Campaigns

Many investors think whether or not investing in stocks is worth. Inspite of the real problems, the following common myths often arise.

 • Investing in Stocks Is Just Like Gambling.

Investors often mistake that stock represents the ownership of a company. Gambling on the contrary takes money from a loser and gives it to a winner.

• The Stock Market Is an Exclusive Club For Brokers and wealthy People.

Most brokers are notoriously inaccurate. Furthermore, the discovery of the internet has made the market much more open to the public.

• Fallen Angels Will Go Back up, eventually.

Buying companies entirely because their market price has fallen will get you nowhere.

• Stocks that go up must come down.

If you find a renowned firm run by excellent managers, there is no way the stock won't keep on going up.

• A Little Knowledge Is Better Than None

It is important in the stock market that every investor has a compact understanding of their investment.

 Read more at: 

http://www.investopedia.com/articles/02/061902.asp

While some industries are beginning to see the transformational capacity of big data and predictive analytics, these methods haven't quite panned out for supply-chain managers. The reason is that the largest obstacles happen to be the cost of hiring experienced employees. Researchers Matthew Waller and Stanley Fawcett write in a paper that the convergence of predictive analytics and big data has the capacity to change the way in which supply-chains managers lead. The goal is to increase the understanding of how to utilize big data efficiently and develop a new breed of supply chain leaders that are experienced in using data and analytics judiciously. A recent Wall Street Journal article quoting a survey by The Economist points out that while most companies see the value in using predictive analytics and big data to eliminate increasingly complex issues within their supply chains, they still perceive the cost of deployment as too high.Read more at: 

http://sloanreview.mit.edu/article/are-predictive-analytics-transforming-your-supply-chain/

Over the past two years, one of the seminal issues regarding Big Data was storage, especially with respect to the exponential growth and size of unstructured data that did not fit into databases. Today, however, the competitive landscape is very different. Proper storage is merely a pre-condition to finding the real jewels in Big Data-turning data from massive streams into knowledge, and thereby actionable intelligence in real time as events unfold. The following five steps are imperative to master Big Data and drive business growth:

1. Infer, Infer, Infer- Inferences transform data into knowledge, which results in greater process transparency and improvements.

2. Empower a C-Level Data and Predictive Analytics Champion. - With big data analytics changing rapidly and straining information structures, corporations and governments need “executive horsepower” behind its data initiatives.

3. Assess And Modify Your Supply Chain In A Multidimensional Global Context. - Analysis of supply chain will ultimately include relationships with parties such as customers, manufacturer, etc. 

4. Give Your Data Time-Critical Situational Awareness. - Analytics help a business line identify potential points of improvement.

5.   Rely On a Core Platform That Creates Derivative Intelligence and Knowledge in Real Time -statistical inferences can turn data into actionable intelligence that supports reasoned decisions. Read more at: 

http://www.forbes.com/sites/benkerschberg/2014/01/03/five-steps-to-master-big-data-and-predictive-analytics-in-2014/

Sales and marketing platforms can easily be combined to generate a closed-loop approach to marketing analytics whereas business analytics understands the structure of the past to estimate what might happen in the future. Through marketing analytics, marketers can easily measure all aspects of their marketing efforts. Business Analytics can measure everything from warehouse efficiency and manufacturing. Business Analytics typically incorporate high level data from each department to gain knowledge of how the organization works. What makes marketing analytics different from other business analytics, is its concentration on real market output. Marketing analytics go beyond measuring strictly online performance and provide representatives from sales, customer service and senior business management with real market feedback that helps guide decisions on where to invest and how to prioritize. Thus marketing and business analytics are really a two way street - without marketing data business analytics wouldn't tell the whole tale, and vice versa. Read more at: 

http://blog.hubspot.com/insiders/marketing-analytics-vs-business-analytics

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There are many parts to a customer service strategy. The benefits of social media is overlooked. In today's world, an existence on social media is as important as having a toll-free phone number. Here are just a few of the reasons why. The benefits of two-way brand engagement. Customers like it when commerce shares information, instructions, thoughts, and humor across social media.  Social media an addition of contact data: clients remain for  reply to their comments or distress fast. Pinch complaints in the sprout with ease: ignoring  social media won't discontinue clients from talking on Twitter or Facebook.  Spot trends as -- or before -- they occur: Responsive brands pay close notice to what consumers are discussing about in order to mark movement before it's too late. have additional admission to customers: Social media conduit shouldn't be measured an publicity prospect. . Read more at:

http://www.socialmediatoday.com/content/how-social-media-impacts-customer-service