NASA is working on big data analytics to facilitate their mission mars more productive and informative. They are using big data analytics to understand the environment of the mars. That is they are using modern technology to collect and analyze environmental data and based on that it will give a predefined signal to the Curiosity rover currently operating in Mars. These data points help to generate a more specific road map for upcoming 2020 mars mission for NASA. One of The expert in NASA JPL laboratory says these huge analytic modelling defines an easier way to resolve the problem. 

To read, follow: http://www.forbes.com/sites/bernardmarr/2016/04/14/amazing-big-data-at-nasa-real-time-analytics-150-million-miles-from-earth/#1cbda1b371dd

Social media is providing endless opportunity to grow our popularity as individuals. But, for business enterprise the best thing is to divulge itself in social media networks. But social presence should have some purpose. We post a lot of daily stuffs in our social wall. In one way that is good because you are one step closer to your distant audiences. We often follow social platforms like twitter, Facebook to get more exposure to what is happening. Social platforms like YouTube, Pinterest provide extensive peripheral knowledge. So in one word these platforms, providing our enormous facility in the learning process, business expansion and lifestyle development, but there is a point when social media becomes an addiction. So, it is high time that we define our position in social media. 

to read, follow: http://www.irishexaminer.com/lifestyle/features/do-we-share-too-much-on-social-media-389859.html

Graphs are not just nodes or links. They are powerful data structures anyone can use to represent complex dependencies in their data. Graph applications are used in various places ranging from cancer research to large-scale cyber threat detection to collaborative filtering recommendation systems. In the world of data-intensive analytics, memory bandwidth is the primary performance restrictor. Because graph algorithms display non-locality and data-dependent parallelism. When you crisscross a large group, you are constantly asking for from main memory. For these problems, GPUs provides superior bandwidth to memory and can deliver significant speedups over CPUs. GPUs are very fast for graph processing and analytics, where memory bandwidth is a problem. The memory bandwidth of GPUs provides a new way to speed up data-intensive analytics and graph analytics. For more read the article written by Brad Bebee ( CEO, Blazegraph) : https://devblogs.nvidia.com/parallelforall/gpus-graph-predictive-analytics/

Computer systems are quite similar to living organisms. The living part of the system is not so much the hardware or even the software it is the data. We seek to build computer systems based on ourselves and take this as models. Non computer science based behavior patterns and structures provides a language for discussing the patterns, behaviors and structures of systems. An artificial neural network is inspired by the biological nervous systems, such as the brain. It is composed of a large number of highly interconnected neurons to solve specific problems. An Artificial Neural Network or ANN is configured for pattern recognition or data classification. For more read the article written by Bruce Robbins (CEO, Xcipi) : http://www.smartdatacollective.com/bruce-robbins/397616/data-alive-through-deep-learning-and-intelligence

Cryptology plays a crucial role in cyber security. There could be use of sign language and different cypher code to encrypt the sensitive data. The decipher mechanism helps to decode the message. In ancient times, Julius Caesar used to send his secret messages to his army in cypher code. Later this process is followed by Germans during the Second World War. In modern organizational context, cyber security is the most important parameter. So, to protect organizational data they can adopt cryptology to encrypt their data and hide them from the normal visibility level. The reader can go through the article written by Mark Ward (Technology correspondent, BBC News) and understand more about cypher process and the levels of challenges at:

http://www.bbc.com/news/technology-34312697

The challenges faced by the insurance industry are same as other companies. Insurance industry involves generating, storing, and making large & complex sets of data to create efficiencies and improving their bottom line. In a recent survey, 54% of 48 U.S. and P/C insurance executives said they use predictive modelling for underwriting/risk selection, and that usage is expected to grow by 40% over the next two years. Predictive modeling helps in claims triage, underwriting appetite and strategy, market-share analysis, and litigation propensity. Predictive analytics can boost companies' profitability by: 1. Developing a clear analytics roadmap across business units. 

2. Monitoring their outputs against what is happening to avoid the situation where underwriters push back on predictive models.

3. Developing an enterprise-wide model monitoring program to ensure models are recent and recalibrated on a consistent basis. 

4. Looking outside the industry to see how other organizations measure ROI.

For more read the article written by Loren Trimble and Michael Kim(Contributors) : http://ww2.cfo.com/risk-management/2016/03/predictive-modeling-can-make-insurers-better-risk-managers/

The need for wearing body cameras for police personnel has increased. Police departments are also taking the help of specialized data mining solutions to predict and prevent misconduct. The problem with this, is that, it leads to officers being treated differently based on actions they are yet to take, and might never take at all. Predictive analytics is playing an important part in modern policing and in ending crimes which are less serious than police misconduct. For more read the article written by Graham Templeton ( Writer ): http://www.extremetech.com/extreme/224560-new-analytics-can-predict-and-possibly-prevent-police-misconduct

Nowadays, new solutions are based on IoT, analytics, and business intelligence and we are surrounded by more applications of big data, analytics, sensors, and business intelligence. According to Mary E. Shacklett (president of Transworld Data) writes in her article about some examples of behind-the-scenes technology that is redefining the world. Some of them are - 1: Weather and political prediction systems for global supply chain and financial market impacts

2: Merchandising

3: Police suspect identification

4: Robots for cleaning your floors and your carpets

5: Medical patient demographics

6: Helping the blind see

7: Crime scene forensics

8: Building information modeling (BIM)

9: Self-driving vehicle systems

10: Inventory management . To know more, read the article written by Mary E. Shacklett (president of Transworld Data) : http://www.techrepublic.com/blog/10-things/10-ways-big-data-analytics-and-sensors-are-helping-behind-the-scenes/

To understand the crime pattern, data are used by police from the past. The objective is to predict acts of terrorism based on the large amount of surveillance data. The technology will collect data on ordinary citizens, including information on their jobs, hobbies, consumption habits, and other behaviors and will flag unusual behavior that could signal a potential terrorist attack. Police in both Los Angeles and Manchester ran trials using a computer algorithm to predict where crime would most likely to take place. Their aim was to find patterns in criminal behavior by analyzing crime data to prevent crime through predictive policing. There is a need for research into machine learning and other artificial intelligence technologies to identify human faces in surveillance video. The police can analyze large amounts of crime data, i.e. 'big data'. Enterprises are now using big data technologies to detect and fight cyber threats. Big data analytics and shared threat intelligence can increase the organization's effectiveness in security measures. For more read: http://www.cxotoday.com/story/how-big-data-can-be-used-to-predict-crime-patterns/

The Internet of Things (IoT) generates semi-structured or unstructured data in real time. Organizations take advantage of cloud because big data can be best managed in the cloud. By utilizing fog computing, organizations can decrease time to action; reduce costs, infrastructure and bandwidth; and can get greater access to data. The advantages of the decentralized method of fog computing and IoT analytics cover both the organization and the end user. One of the benefits of centralization is to focus and understand the data location and the accessibility. The decentralized method is associated with flexibility and agility. This tends to describe the data management trends and applications. Read more at the article written by Jelani Harper (blogger) : http://data-informed.com/the-internet-of-things-and-the-necessity-of-fog-computing/

The development of mobile, IoT, and the cloud has increased the need of analytics to solve challenges in the customer, product, operations, and marketing domains. The established companies need to restructure their business and technology to increase their sales. Organizations need to involve cross-functional teams to establish data governance. Analytics 1.0 was data warehousing and business intelligence; Analytics 2.0 was big data, Hadoop, and NoSQL. Now in the era of Analytics 3.0, when tools make decisions and measure the impact. For more read the article written by chandramohan Kannusamy (Technical Architect) : http://data-informed.com/analytics-3-0-and-data-driven-transformation/

The best way to improve the probability of desirable outcomes is to predict the unknown future results. Predictive analytics help organizations to become forward looking and proactive. It uses a number of predictive modelling and analytical technique for the prediction of the future. One of the modelling techniques is a response model which doesn't predict influence. It only predicts the desirable outcomes of one method without making any prediction of alternative method. Healthcare organizations will be more successful if the predictions for treatment decision results in the desired outcome. For more read the article written by Eric Siegel (founder of the Predictive Analytics World Conference):

http://data-informed.com/drive-influence-with-uplift-modeling/

A proposed framework focuses on the development and application of electronic healthcare predictive analytic (e-HPA) applications. The framework is built on "earlier frameworks of model development and utilization" to show opportunities for e-HPA, ways to address challenges and ideas for motivating stakeholders to adopt and refine the framework.

Five areas provide the structure for the framework, which includes:

1. Data barriers and model development

2.  Transparency and model evaluation

3. Ethics

4. Regulation and certification

5. Education and training. 

It is the task of healthcare leaders, e-HPA practitioners and other stakeholders to ensure an infrastructure .The infrastructure promotes effective use of predictive analytics to improve patient outcomes, satisfaction and the value of healthcare resources. For more read the article written by Katie Dvorak(an associate editor for FierceHealthIT and FierceHealthcare) at : http://www.fiercehealthit.com/story/proposed-framework-focuses-electronic-healthcare-predictive-analytic-applic/2016-03-08

Cyber security is the biggest issue for the business enterprises who is in the field of networking and cyber space. But, problematic situation is arising where there is a mismatch of investment in cyber security than the growing threats in cyber space. This indicates that most of the organizations are either not aware about the upcoming threats or financially reluctant on investment. Security budget is not easy to predict and more skillful persons are required to predict the upcoming threats. 

To read, follow: http://www.computerweekly.com/news/4500279662/Cyber-security-budgets-not-rising-in-line-with-threats-say-security-pros

In order to make management decisions, all companies in various industries work on large transactional data. For example: healthcare, retail, pharmaceuticals and so on. Some of the benefits big date provides:-

1. Big data analytic makes operations more efficient and frequent.

2. It appreciates the quality of services by analyzing the whole data and not just sample subset. As a result, the companies make more precise decisions.

3. Marketers target the right customers using big data. Through focusing on data based strategies

4. It gives an opportunity to new companies because they can analyze the existing industry data.

5. It also gives a competitive edge to those companies who use it decision making.

To read more: http://timesofindia.indiatimes.com/tech/it-services/How-Big-Data-is-changing-the-way-we-do-business/articleshow/50417589.cms

Cyber-attack on Sony pictures in 2014 has clearly indicated that the hacktivists have enough technological supports to sabotage one of the most secured service section and business giants. The U.S government suspects that Chinese hackers are penetrating the government's Office of Personnel Management (OPM) last summer as it exposed almost 4 million Federal employee records, including social security numbers. These all instances which prove that these hacktivists are mostly concerned about the sensitive data. The Department of Homeland Security's (DHS) Einstein system is used to find out who committed breaches. Deeper insight in cryptography is therefore required.

To read, follow: http://www.extremetech.com/extreme/225114-the-cybersecurity-threat-are-we-protected-yet

A recent study by MIT University shows that there is a 78% increase over the past three years in the job posting related to analytics and this led universities to launch specialized program in Master in Business Analytics. Nowadays, data analytics are used in marketing, finance, health care, logistics, insurance ecommerce, manufacturing and government services. To know more, please read the article by Michael Norton (Writer at lowellsun.com)-: http://www.lowellsun.com/business/ci_29635724/mit-reports-spike-analytics-job-postings

In the aviation industry, aircraft maintenance and safety is always on high priority. With the increase in air traffic and air passengers, aircraft maintenance and repair firms are utilizing predictive analytics integrated with the Internet of Things (IoT) to predict component failures and pilot stress level. Firms are developing a solution that can predict the likelihood of a component failure which can help to replace the part before it fails. In future, by analyzing breathing patterns of pilots before they board the flight, will help to monitor the stress level. To know more, please read the article by Jonathan Ananda (Writer at The New Indian Express) -: http://www.newindianexpress.com/business/news/Data-Analytics-to-Make-Flying-Safe-for-Pilots-and-Passengers/2016/03/16/article3329532.ece

Image Source - : https://pixabay.com/en/oldtimer-aircraft-take-off-aviation-1010805/

Wave analytics platform is one of the key product sets of Salesforce. When Salesforce first launched the Sales Wave analytics app it had an inbuilt packaged application Wave platform. A platform seems to be quite challenging in terms of its requirements, implementation, price of entry etc. So the company doesn’t sell only wave platform but also the analytic app and it has brought a radiant result. The app can be implemented very quickly and it has reasonable price. The company has significantly matured the tooling and product to render dashboard and make the platform easier for business analysts. But the main challenge is getting the right data and taking advantage of machine intelligence to automate elements of the analysis. Salesforce has introduced a self-service data prep console in the Wave platform. It focused on user specific cases. To capture the enterprise analytics, market vendors must do the part of building an analytics application. For more read : http://diginomica.com/2016/03/08/salesforce-wave-and-the-future-of-enterprise-analytics/

Cyber-security is becoming the most trending topics in organizational context. So a proper understanding of cyber-security measures and preventive learning is necessary. Institutionalization of security methodology should be in the key priority. Some institutes provide a set of free hands-on, e-book lessons designed specifically for teens to learn cyber-security and critical Internet skills. This training enables the learners to challenge hacktivist with improvised measures and safe guard protocols. Some Cyber security company provides free five weeks training on how to secure online browsing. We need to list all possible threats and nullify by secure web browsing and cyber activity. In a research it was also found that there are one million cyber security jobs in 2016 which is growing at a rate of 36.5% through 2022. Read more at: 

http://www.forbes.com/sites/stevemorgan/2016/03/20/hacker-high-school-teaches-cyber-security-skills-to-teens/#41440ab669b6