Big Data is the game-changing opportunity for marketing and sales. Airlines are spending on advertising. With the help of big data and analytics airlines can see how to allocate ad dollars. Marketing mix is one example of analytics which helps us understand which media vehicle works best. Following are the three key aspects of marketing mix-

1. Examining the noise- Airlines should take into account the impact of noise.

2. Normalizing the data- This means to adjust the data for external factors (those outside marketing campaign).

3. Performing a regression analysis- To calculate the return on each investment made for marketing and to know the mean impact of each campaign analysis of data is necessary.

To know more- http://revenueanalytics.com/blog/airlines-can-maximize-return-on-marketing-spend-with-predictive-analytics/

Big data is an emerging phenomenon. Nowadays, many organizations have adopted information technology (IT) and information systems (IS) in business to handle huge amounts of data and gain better insights into their business. Many scholars believe that Business Intelligence (BI), solutions with analytics capabilities, offer benefits to companies to achieve competitive advantage towards their competitors. But this journey of increasing adoption of analytics requires much more thinking with an organization.

1. Promotion of decision making based on business outcomes: 

Investment should focus on implementation of analytics rather than infrastructure. Great companies link analytics to results to ensure gains.

2. Data –led decision making: 

Adoption of analytics should be encouraged and intuitive decision making should be discouraged.

3. Technology and business move together: 

Capabilities are built by amalgamating data, technology and business talent.

Therefore, decision makers should realize the importance of big data analytics in improving their business. Changes should be created in organizations for successful adoption of business analytics.

To know more- http://analyticsindiamag.com/successful-adoption-of-analytics-the-journey-from-good-to-great/

Hospitality industry has not been concerned about technology and big data which resulted in widening of the gap between customers and industry. Big Data can result in improved customer satisfaction and personalized marketing campaigns. In addition, Big Data results in a boost in employee productivity and more efficient operations. The advantages of Big Data for the hotel industry are enormous.

1. Improving Customer experience through Personalization  

To improve customer experience, businesses must work towards gauging preferences .There is likely to be an enormous amount of information about every person on the Internet, so the key is to mine this information, and get the most relevant details out of it

2. Marketing Strategies

Big data can help companies devise the best marketing strategies for each target segment, based on their activities and preferences. When businesses understand their customers well, they can devise the right strategies to reach out to them. For example, if a company knows that a particular target group is spending an average of thirty hours a week on social media, they can devise their marketing strategies through social media channels. Such a strategy will give the greatest visibility for the company within their target group. 

3. Competitive Advantage

Companies that make use of big data have edge over others. They are able to foresee trends and make pricing strategies accordingly.

To know more- http://analyticsindiamag.com/how-big-data-is-leveraging-the-hospitality-industry/

There is a great potential in “unadvised assets”. The necessary growth rates for a profitable business are close to hundreds and millions of AUM increase per month. Alternative steps needed to be taken by the businesses are:
• Substantial growth in terms of AUM has to be made.
• Varying customer acquisition costs will have to be taken into account during profitability calculations.
• Shift to adjacent markets; from pure online to more sophisticated hybrid services.
• Separated commoditized investment management services and focus on areas of finance and estate planning.
• Get rid of proportional fee model.
Read more at: http://bankinnovation.net/2015/07/half-a-dozen-possibilities-in-automating-asset-management/

Actionable data to support or automate decision making is used by predictive and prescriptive analytics. Prediction of a quantity i.e. regression is required by many use cases. The actions based on the predictions is more important than the actual quantity predicted. Predictions of future events in the context of predictive and prescriptive analytics needs a full probability density distribution. The predictions might give some estimated value of expected fluctuations, but details will still be hidden in the full probability density distribution. In this case, advanced predictive models can be used to derive best point estimator for a given scenario.
Read more at: http://www.blue-yonder.com/blog-e/2015/07/20/predictions-as-a-probability-density-distribution/

In healthcare, the main challenge when big data is concerned is to ensure that both healthcare providers and patients are benefiting from the huge flow of information, and are not getting confused by it. Big data is not to be forced and is to be adopted by the healthcare system, in a stable and efficient way. There is a need for targeted and personalized data to improve service quality, even at doctors’ levels. Restricted accessibility to information often creates hurdles for healthcare organizations. The healthcare providers are now deriving both medical and financial information from the insurance sector. EHR data can act as a major playground for big data analytics, as the healthcare sector are adopting more and more e-measures. Read more at: http://healthitanalytics.com/news/how-healthcare-big-data-analytics-drives-systematic-improvement

New companies prefer to wait for a few years, exploring their profitable opportunities first, before focusing on their financial stability. There are associated risks, of ensuring continuous availability of funds throughout the initial phase. Again, in order to stay in the competition, it is also important to prepare the business model at the earliest. When firms delay in preparing their business models, there remains a scope of further innovation in the model, but it can be costly too, if a model is rebuilt from scratch. In each business model it is important to understand the tradable values, that may include brand value of a company, the company’s intellectual property rights, user circles, user circle data, and information regarding the stakeholders. Read more at: http://venturebeat.com/2015/07/12/how-to-define-your-business-model-when-your-business-is-still-up-in-the-air/

The rate, at which virtual reality is undergoing evolution, it may soon be possible in the recent future to virtually teleport from one place to another, via remote reality, even at the most distant corners of the earth. Networking is the most important factor required to make this possible. High speed internet must be accompanied with advanced audio and visualization technology, to make the media feeds, received by the users more realistic and communicable. Drones and robots will come handy in the age of remote reality and it is important to match the system response speed with the immediacy of real world actions, to avoid motion sickness of users caused by the deferment. Read more at: http://venturebeat.com/2015/07/13/omnipresence-and-the-coming-age-of-remote-reality/

A recent survey on how organization's active data is growing on a year on year basis, looked at two distinct groups:
• Companies experiencing data growth exceeding 50% annually.
• Companies experiencing data growth of 10% or less annually.
So what did the survey reveal?
For starters, companies experiencing rapid data growth were more likely to uncover business opportunities and drive growth. These companies were better able to leverage a wide variety of data types that are both structured and unstructured. And, in comparison to companies with lower rates of data growth, rapid data growth companies:
• 64% more likely to have an executive champion for their Big Data initiatives.
• 68% more likely to have the ability to discover and classify all relevant business data as it arrives.
• 4.3 times more likely to have defined a chief data manager role.
All evidences points to the conclusion that there cannot be a case for excess data. When it comes to data – the more the better.

For more information visit:
http://www.attunity.com/blog/data-growing-out-control-that%E2%80%99s-good-news-your-business

All that glitters is not gold – and the same is true for data as well. To be frank, there is a lot of ordinary in our data management world.
And the most worrying part is that most companies do not actually realize this threat, which is not particularly surprising to be honest, with most companies sticking to well defined data rules which have been in places for quite some time now. This is because data is living under outdated data policies and rules. Data processes and systems are persisting single-purpose data. These outdated processes have given rise to zombie data, which when used can prove to be detrimental rather than beneficial to your corporation.
The only solution is to reassess the founding blocks of data analytics to crush zombie data and ensure progress in the field of data analytics.

For more information visit:
http://blogs.forrester.com/michele_goetz/15-07-14-is_zombie_data_taking_over

Continuously evolving technology in the healthcare sector is creating immense pressure on the healthcare providing concerns, to meet their highly demanding service quality and financial goals. Organizations are trying to develop step by step connections, by keeping track of all the different stages a patient has to go through, once he enters into the concerned healthcare system. The healthcare industry has been giving a lot of effort in the development of the health information system and big data analytics, in order to improve the healthcare service. As, more and more stages of the healthcare cycle becomes electronically recordable, the easier it becomes to keep track of the patients and their health situations. Read more at: http://healthitanalytics.com/news/health-data-interoperability-requires-patience-persistence

Health care providers, lose track of patients as soon as they relocate from the healthcare facilities. The process of relocating within hospitals is equally complicated for patients. A well-defined IT infrastructure can be used to address both the issues. It is important to match patients with their appropriate health care facilities, by collecting and analyzing the data on the patients’ needs. It will also be possible for healthcare providers to draw valuable insights, by collecting and analyzing data on patient transfer procedures. Hence, we have both big data and data analytics, coming into play, by increasing the operational efficiency, but dampening the revenue earnings of the healthcare industry. Read more at: http://healthitanalytics.com/news/big-data-on-patient-transfers-raises-quality-snags-revenue

Increased life expectancy in the Asian region means plenty of business for insurers, with need for health insurance etc. Insurance premiums are growing faster than Europe and North America yet still largely it remains underinsured. Culture dictates that majority build up savings themselves rather than pay someone else to bear it. Innovative products are offered for specifically for Asian countries because of the demographic dividend. The growth of the insurance market is typically fuelled by innovative product design and population pressure. Many global insurance tycoons are joining hands with Asian tech firms, banks to launch their products in the large expanding markets.
To know more: http://www.economist.com/news/finance-and-economics/21654086-insurers-asia-cauldron-innovation-also-competition-astounding?zid=300&ah=e7b9370e170850b88ef129fa625b13c4

Metrics are performance indicators for the markets. The rules in choosing the right metrics are:
1. Easy to use and understand
2. Easily replicated
3. Metrics should provide useful, actionable information that impacts the business.
With the availability of a wide variety of advanced analytics, it is easy to get sidetracked. Pressure to measure to many things makes it difficult o determine where to focus. Background data on customer is a useful metric. Effectiveness of targeting is related to marketers identifying customer personas. The right metrics such as calculating the potential lifetime values of various customers can help differentiate who is most likely to be profitable over the long term.
To know more: https://hbr.org/2015/07/identify-the-marketing-metrics-that-actually-matter

More often than not estimates, analytics, data-driven predictions seem confusing and overwhelming. But now the situation demands that benefits of data interpretation is vital. Statements such as data too difficult to access, understand or use are common and so are ignored while making business decisions. Fear of failure affects productivity and trying out new ideas. To dispel fear of data usage, managers need to promote better work ethic; data interpretation must start at the basic level with simple tools and incorporate the habit. To incorporate the total picture in a business decision, every perspective regarding data must be addressed.
To know more: https://hbr.org/2015/07/dispel-your-teams-fear-of-data

The Financial crisis in Greece has led to the worst economic meltdowns in modern times. The ripple effect is projected to hit the US shores as:
1. With plunging global markets, analysts claim that the situation in Greece could end the six-year bull market in the US. But this scare is pertinent if the crisis spread to other countries of the Euro zone too.
2. Since the Euro is plunging against the dollar, European holidays will become cheaper. Travel agencies are advertising deals on European vacations.
3. Mortgage rates are projected to be stagnant as it is closely follows the global markets.
To know more: http://www.washingtonpost.com/blogs/wonkblog/wp/2015/07/05/3-big-ways-the-crisis-in-greece-could-affect-americans-personally/

Time and money are the two determining parameters for small businesses. Entrepreneurs often have to fulfil many roles and handle over some responsibilities in exchange for welcoming in others. HR tech lightens this burden. In small businesses, huge workloads are handled by a few individuals. Hence embracing technology is rewarding, using HR tech lessens time spent on administrative tasks and costs too. Small businesses look for technology which is cost effective, and can be applied by effective small teams. Data and records help in deciding the process confirmation, as successful projects must be repeated.HR technologies are the bridge of efficiency and cost reduction. To know more: http://www.business2community.com/small-business/why-are-more-small-businesses-turning-to-hr-tech-01272723

While you sit reading this article, if you stretch your arms, you would have electronic help all around you. A smartphone which could pay your bills, plan your schedule and tell you it’s time for a meeting or showing you the nearest food joints when you are hungry. These interruptions imply that we are surviving on advanced, analytics driven machine intelligence. All this said, for machine intelligence to be more powerful, we should be ready to accept a higher level of intrusion. For example, a patient detected with a heart disease, his device could suggest him to take a nap or hit the gym, or could wake him up when he is feeling anxious or stressed. Read more at: http://www.forbes.com/sites/teradata/2015/07/16/why-machine-learning-is-the-next-penicillin/

Flash vendors advocate the use of de-duplication and compression technologies combined with smaller space and lower power consumption. This means that when you buy 20 TB of raw flash capacity, the effective capacity is actually greater. But according to Michael Gunton, GM for Data Center Services, flash does not really reduce data footprints. Apparently data Scientists have seen trends of higher density infrastructure from the cloud providers. The benefits of consolidation are not apparent to ordinary business customers so they are not buying much flash to put in data centers. To know more, read: http://www.forbes.com/sites/justinwarren/2015/07/16/flash-not-reducing-data-center-footprints/

 After big data and internet of things, the new buzzword is the Analytics of things. Though on a similar note, we do not have an exact definition, we know what it means for the economy and the world, as a top strategic trend in technology. As better algorithms for IOT digital infrastructure are being built to index our world to every smaller level, connection based analytics can be used to better predict future conditions and prescribing future actions. AOT fuels the process as new devices are created, there is a potential for new analytics further leading to modification.  Read more at: http://www.forbes.com/sites/teradata/2015/07/15/analytics-of-things-what-does-it-mean-and-where-is-it-taking-u