Every human being is interested to know their chances of getting sick in the future. This is where artificial intelligence scientists steps in. With the combination of machine learning, natural language processing and text analytics scientists are working to find out some latest concepts and technologies in biomedicine. Each term is then given a score, which, based on the technology's analysis, identified its predicted rate of incline. So based on that, few predictions have been made for 2016.  To know more, follow: http://www.science20.com/news_articles/ai_may_tell_us_whats_going_to_be_big_in_science_this_year-165373

Enormous demand of Wi-Fi has led to transmission of billions of bytes of data every day. Researchers have predicted that by 2019 mobile devices will exchange 35 quintillion bytes of information every month. This is just for mobile devices, just consider computers, IOT devices and you can get an idea how much data will be transferred. But our traditional Wi-Fi can't handle this entire load. So scientists have discovered a new technology known as LiFi. It uses light as a means of data transmission. Using LiFi we can send 224 gigabits per second. They can be also used in healthcare facilities. The idea that light can pass through walls can increase security because one has to be physically present in the room to access the data. Read the full article here: http://www.forbes.com/sites/bernardmarr/2016/01/12/will-lifi-take-big-data-and-the-internet-of-things-to-a-new-level/#2bceb09c346f

Big data is in its adolescence. Companies have started to treat it as a corporate asset. The focus has been shifted to find those data initiatives that will have biggest and immediate effect. Companies are not looking for more data, but the right data. This helps in making better informed decisions. A correlation between good data policies and financial success is also observed. Big data is becoming less about volume and velocity, but more about value. As technology continues to improve, the "bigness" of big data is becoming a less important factor. Read the full article here: http://www.forbes.com/sites/bernardmarr/2015/11/30/big-data-now-a-top-management-issue/#29598044794d

Data analytics is now not only restricted to the IT sector, but also serves other sectors of the society. If we look at the services and other sectors where data analysis can be used then, the list will be very long in today's world. Data analytics is used in each and every sector including sports, politics, medical and financial firms. Some of the predictions of how analytics will shape the business, sports, and political landscape in 2016 are:

Prediction #1: The hottest corporate job of 2016 is data analyst.

Prediction #2: IT will embrace the self-service analytics movement.

Prediction #3: Predictive analytics go mainstream.

Prediction #4: The "Internet of Things" (IoT) will get more organizations interested in geospatial analytics.

To read the full article, follow: http://www.forbes.com/sites/valleyvoices/2016/01/20/five-ways-data-analytics-will-shape-business-sports-and-politics-in-2016/#612ab3395a1d

Nowadays, data analysis and space technology are used to help live crime mapping and is known as Predictive Policing. This has been used by various police departments of the few developed countries. In India, Delhi Police is also developing this mechanism in partnership with the Indian Space Research Organization (ISRO). It is called The Crime Mapping, Analytics and Predictive System (CMAPS) and is used for with ensuring internal security. This will help in crime control, and law and order and security management through analysis of relevant data and patterns, leading to the optimization of available resources. Each police officials will be equipped with Personal Digital Assistant (PDA) device connected to a central processor, with the records of more than two lakh criminals. To read more about Predictive Policing, follow: http://www.indiatimes.com/news/india/delhi-police-join-hands-with-isro-will-use-space-technology-to-predict-and-stop-crime-250432.html

The use of predictive analytics in the Human Resource Management is the recent development. The HR team is taking advantage of the loads of data to keep a check on the employees. Predictive Analytics is changing the relationship between employee and enterprise. Predictive models can easily predict the upcoming trends. The performance of the employees can be judged in an unbiased way rather than gut feelings. The models identify meaningful insights by collecting data from the various platforms. The kind of posts that individuals have on the social networking platforms, LinkedIn profiles all lead to predictions. HR teams use these insights to decide the promotions, pay scale etc. This also acts as a disadvantage to the privacy of workers. Soon there will be a need to redefine the worker privacy laws which will take care of these new technologies. Read more about this in the article written by Rodd Wagner (A best- selling author) at: http://www.stevenspointjournal.com/story/opinion/columnists/2016/01/22/predictive-analytics-transforms-workplace/79116764/

People are actively looking for ways to increase their online privacy and security. So here are five tools to increase that will help you achieve the same.

1. Privacy Badger: It blocks all the tricky ads. It can be used as an extra level of security over common ad block sites.

 2. HTTPS Everywhere: This makes browsing more secure by encrypting communications provided that the sites you are opening have these additional capabilities.

3. Ublock Origin: It's a free and open source extension.

4. Purify Blocker: this application is made for iOS helps in browsing websites without ads and tracking. It will also lower the data usage and will improve speed.

5. Tor: It's a service that can encrypt web traffic and sends it across a series of relays to help maintain anonymity. It can be downloaded on laptop for Windows, Mac or Linux.

Read the full article here: http://www.forbes.com/sites/ygrauer/2015/10/13/five-tools-privacy-security/#5804444e537c

Contextual Integration refers in identifying meaningful relationships between different information types. This gives a multi-dimensional view of the data rather than a single access point. The best approach is to analyze these volumes of data from different perspectives. The traditional way is to follow a fragmented approach. The web teams, marketing and sales team will look at the different statistics offered by data. This lengthens the time to take decisions and also introduces inaccuracy. The need is to look at data from many angles to create a multi- dimensional profile of the customer. Then predictive analytics can assess and lead to intelligent messaging. Machine Learning is also helping to improve these predictive analytics algorithms by checking it on the real time data. Read more about it in the article written by Dominik Dahlem (Senior Data Scientist at Boxever) at: http://data-informed.com/contextual-integration-secret-weapon-predictive-analytics/

There are many CRM solutions available in the market. But, choosing a CRM technology, according to one’s business need is important. There is no absolute checklist for choosing the right CRM. There are some key functions that at the center of CRM. The following functions make a good starting point in the selection process – 1. Intelligence 2. Automation 3. Simple Data Entry 4. Analytics and Reporting and 5. Mobile Access. Read more at: http://it.toolbox.com/blogs/insidecrm/five-important-functions-to-look-for-in-a-crm-71190

Sales management benefits from lead tracking and activity monitoring i.e. keeping an eye on the sales pipeline. But sales staff, however, has a different perspective. CRM features are important to sales people. There are many important CRM features, but, there are some features that are important for the agent closing a sale. They are – Automation, Analytics, Activity Scheduling and Process Management, Offline Sync, and Easy Contact and Pipeline Management. Read more at: http://it.toolbox.com/blogs/insidecrm/five-features-your-sales-team-will-want-in-their-crm-71207

Mobile customer relationship management software is gaining popularity in today’s business world and as mobile CRM is evolving along with the development of Software-as-a-Service (SaaS), more and more organizations will have access to accelerated digital productivity. Data mined from mobile technology also augments the range of information available to CRM systems, which helps in getting more insight. Mobile CRM is also helping to streamline functions. It was also found that the entire sales process, from initial contact to after-sale service, benefits from mobile CRM. Read more at: http://it.toolbox.com/blogs/insidecrm/mobile-crm-accelerates-productivity-in-2016-71273

On premise CRM solutions are fading away and cloud-based CRM systems are the future.  According to Jim Desler, director of corporate communications for Microsoft, “The cloud opens up new possibilities and benefits for our customers”. Most software benefits from the cloud model, but the gains from placing CRM in the cloud are finding more customers. This article link describes reasons why businesses are moving to cloud CRM and how the cloud has changed the space. Read more at: http://it.toolbox.com/blogs/insidecrm/five-ways-the-cloud-changes-crm-71206

Failures in the functioning of equipment are inevitable in any kind of industry. The repair and recovery time often leads to big financial losses each year. But we have machine learning and predictive analytics as a solution. The machine learning models are trained to learn the ideal functioning of the machinery. Then this functioning is compared with how the machines are working at present. So if even a minor change occurs somewhere, it doesn't go unnoticed. Then, with the help of predictive analytics the loss that can take place in the near future is predicted. This adds to the huge advantage of the firms. Learn more about this in the article written by Mike Reed (manager of analytical services for Avantis PRiSM software) at: http://www.intelligentutility.com/article/16/02/saving-money-and-man-hours-machine-learning

Machine Learning is getting easier and accessible because of the computing power becoming affordable. Moreover, big enterprises are making their algorithm open source. This is because data is the food. More data an algorithm gets, the better it becomes. But from step 1, making algorithms, feeding data in humans play a significant role. Sometimes there are outliers which the algorithms cannot interpret. Here human intervention is necessary. They manually check such pieces. But when these are fed into algorithms, they make them robust by identifying outliers. Thus, human intervention is both necessary for accuracy and training. Read more at: http://insidebigdata.com/2016/01/11/human-in-the-loop-is-the-future-of-machine-learning/

Email Marketing is good for business. It is a tool continuously being used for connecting with the customers. Emails are sent comprising of newsletters, best deals, new products, etc. A few ways to enrich your email marketing are written here. Though not everyone opens the newsletter, but still it is important to give a detailed view to the customer of what you deal with. Order follow - ups gives a sense of satisfaction to the customers. Thus making long lasting bonds. It is important to approach the potential customers who aren't aware of your products. They might be in need, but due to lack of information they are inactive. A good conversion rate is observed in this category. The essence of businesses lies in their approach towards their customers. So it becomes a responsibility to bring the customers lost. Moreover, lucrative deals, coupons, discounts work quickly. Read more about it on: https://econsultancy.com/blog/67403-ecommerce-email-marketing-benchmarks-for-2016/

Despite the many differences in application, most people agree on that the disruptive innovation are: 1. Cheaper 2. More accessible and 3. use a business model with structural cost advantages. Due to the presence of these characteristics in disruption, it's difficult for an existing business to respond to competition. To read more above disruptive innovation follow: https://hbr.org/2016/01/how-big-data-is-changing-disruptive-innovation

There is a big gap between what attackers do and what preventions defenders do to prevent it. The general idea is to build bigger and better blacklists for all the threats known or calculated using better threat intelligence.  We always hunt for easy ways, trying to seek out automation of security infrastructure. But these won't' suffice. The reason is because all the defenses are static and accessible to all. All it takes a hacker is to write a script to bypass these security measures. So a possible solution might be RITA, which stands for Real Intelligence Threat Analysis. Its SANS's free new framework that will help in hunting attackers by extending the traditional signature analysis. Read more at: http://www.darkreading.com/vulnerabilities---threats/introducing-rita-for-real-intelligence-threat-analysis/a/d-id/1323244

In the Healthcare industry, what we really need? Better healthcare results to improve our lives. Healthcare industry generally takes decision using data- like case histories. Well the good news is, now we have lots and lots of data. This is the era of big data, where millions of bytes of data are generated every second. And the bad news is we can't keep up with this fast rate of generation of data. Big data is unstructured which makes it difficult to hunt down relevant helpful information. Using data science with health care we can predict epidemics, advance cures and can provide better, safer and more pleasant experience for patients. Read full article here - http://www.cio.com/article/3001216/analytics/4-big-reasons-why-healthcare-needs-data-science.html

Ever wondered if machine learning can be used for Data Driven Marketing. The Intelligent Agent (IA) developed on the concept of machine learning takes a big leap in data driven marketing.  IA technology can learn about the user behavior and suggest most suitable actions. It can identify the most relevant data from the whole lot and can even find out the reasons for the importance or relevance of that data. Artificial Intelligence is revolutionalising the field of marketing. Intelligent Agent would reduce the manual processing and will produce better results. Read more about it in the article written by John Bates(Senior Product Manager for Data Science & Predictive Marketing Solutions) at: http://blogs.adobe.com/digitalmarketing/analytics/data-driven-marketing-ready-for-machine-learning/

Staying connected to customers is the vital thing in today’s business. Nowadays, CRM solutions also focus on connectivity. CRM solutions are mobile now. CRM on-demand solutions are available to meet the need. By providing real-time data, you are able to know your customers and increase your customer base no matter where ever you go. To increase mobility, organizations must look for solutions that are: Cloud-based, Wi-Fi enabled, Responsive, mobile friendly, Geospatial Data, Note-Taking, Message Marketing, Profile Analyzing, and Conversation Listening. Read more at: http://it.toolbox.com/blogs/insidecrm/crm-for-2016-taking-connected-to-a-whole-new-level-71095