Statistics is everything now days. We believe in numbers not in assumption. How digital marketing is so relevant these days and why can be answered by all these seven key statistical figures.

1. According to “Brandlive”, 44% out of 200 executives use live video streaming activities to generate leads. 25% of them has evidenced a progress.

2. The social network said 3 million businesses have now advertised on its platform, up from 2.5 million just six months ago. A year ago, Facebook had 2 million advertisers.

3. Internet connectivity in the smart phone section has increased by 200% in one year

4. BuzzFeed chief Jonah Peretti said the viral site now has 6 billion monthly content views, up from 100 million in 2012.

5. E reader market is streamline with fast pace of growth and apple finally joined the social media arena to increase brand salience

6. Lead generation techniques via digital media increased by 61%.

This all figures shows we are venturing into digital era.

To read, follow: To read, follow: http://www.adweek.com/news/technology/9-interesting-digital-marketing-stats-past-week-169993

Artificial intelligence is like machine learning. But they are completely different and some concepts related to it has to be cleared.

1. Artificial intelligence refers to a broad set of methods, algorithms and technologies that makes the software 'smart' that seem human-like to an outside observer.

2. Machine learning has some elementary engineering sensibility whereas artificial intelligence is more correlated to automation and sophisticated data handling.

3. Machine learning covers multiple technology, whereas AI is a process which only refers wide variety of algorithms and methodologies that enable software improvement.

4. Machine learning is more into deeper analysis, segmentation and networking in contrast to standalone operation of artificial intelligence

5. Cognitive understanding is more prominent in artificial intelligence because analytics and forecasting play a clinical role. So, accuracy in automation required cognitive learning.

To read, follow: www.cio.com/article/3040600/five-things-you-need-to-know-about-ai-cognitive-and-neural-and-deep-oh-my.html

Artificial intelligence opened a new horizon to give reply to E-mail instantly. Reading long emails in a busy life is a tough. So an automated answering system can reply a mail by analyzing the tone of a particular mail. A particular word based sentiment analysis can be a useful tool to facilitate this process. Google has already started to offer 'robot email' AI in its Google Inbox online extension for Gmail. The new service is called the Smart Reply and it will help answer some of your emails for you. There are still some constraints. This automated system has some issues regarding long multi sentimental messages. These messages has to be replied manually. 

To read, follow: http://www.forbes.com/sites/adrianbridgwater/2016/02/18/can-artificial-intelligence-answer-our-email/#4e1fd3197bc2

In case of an upcoming cyber-attack, there is a chance of huge cash outflow and there is no alarm mechanism which will caution. The only way to find and eliminate the new set of undetectable tools is computer behavioral analysis. AI can adapt itself based on what it sees to both better identify and more quickly eliminate a threat. The scanning can be far more comprehensive, the response faster and the result itself far more secure.

To read, follow: http://www.cio.com/article/2886748/security0/artificial-intelligence-may-save-us-from-new-breed-of-cyber-threats.html

Google has developed a new artificial intelligence system which can recognize the geo-location of a picture. It can also identify a particular monument and area by using sophisticated mapping techniques. This will not only improve an intelligent image search, but also provide a more accurate mapping facility. The system doesn’t exactly spit out GPS coordinates. Instead the team divided the globe into about 26,000 squares of differing sizes based on how many photos from the data set were taken in the area. Huge image search and detailed mapping system is space consuming and particularly troublesome for smaller devices like smartphones and tabs which have space constraints. In order to minimize these issues they are trying to compress huge data within 377mb only.

To know more, follow: http://www.forbes.com/sites/ericmack/2016/02/25/this-google-a-i-can-figure-out-where-that-photo-was-taken/#1bff3c4e34f7

Customer service is the most effective part of any company. It not only helps to improve customer retention rate, but also helps to understand new market trends. Big data analytics and business intelligence play a crucial role here. Simple web crawling into a social site helps to understand the on-going sentiment and current market trend. Different social responses, video hits, ads and newsletters help to optimize the search results. In other word this process facilitates smother recommendation system and customer centred predictive modelling. To make a better prediction we can use –

1. Connectors help to integrate diverse data sets in different formats

2. Lightweight search facilitates even non-technical data analysis

3. Queries optimizes the search dynamics

4. Enterprise search also scores with its semantic search, which means that the context is recognized and included in the analysis and structuring of the data.

Using all these parameters business enterprises can design a better profitability model.

To read, follow: http://www.computerweekly.com/blogs/Data-Matters/2016/02/search-driven-business-intelligence-intelligence-for-a-customer-centric-business-world.html

The most important issue in IT industry is a cyber - attack these days. Advanced security measures and sophisticated firewall systems are not free from bugs. Hence it is not difficult to crack complicated coding and launch a potential cyber-attack. Sometimes it is observed that these attacks take around one month time to get sorted out. So the question is how did these hackers are getting access to data of a particular company? The answer is simple, it's an in-situ type attack, i.e. hackers stay inside the firm and get familiar with encryption pattern, firewall dimensions and sophisticated filters. The solution is to identify these red flags. That can be only managed if all small potential deviations are identified and listed. These create a huge data pool which can be implemented to automate the alert system. By this process small attacks can be taken care off in no time and protect company from higher damage.

To read, follow: http://www.informationsecuritybuzz.com/articles/data-analytics-in-the-early-detection-of-cybercrime/

Chemical industry deals with lots of data sets. Some of these data are relevant to product development and the rest of them mostly helps to identify external parameters governing the production process. Generally, big data help to facilitate cost cutting issues. It brings a new product to the market and improves industry environment. Intellectual sensors are integrated with the research and material related informatics. This process minimizes the time required for new innovation. Sensitive sensors can also help to predict the upcoming situation by measuring current situations. Big data works in the back end. This ensures worker's safety by analyzing the toxic level, heart rate, etc. Intelligent sensors diagnose the past chemical data and all possible combinations to predict the new combination. It smoothens the R&D process. Therefore, automation, safety guide and intelligent forecasting are the key mantra for success in the chemical industry.

 To read, follow:  https://www.environmentalleader.com/2016/02/23/how-big-data-is-changing-chemical-manufacturing/ 

Teaching profession is facing lower job satisfaction, unclear idea related to a particular subject. Inaccurate teaching processes are generating slack in the education industry. To manage such issues we can use big data as used in famous movie "Moneyball". It can predict the future outcome by using simple statistics and work according to forecasted outcome. Proper mining could help us to find undervalued personnel with higher potential to attain a high success rate. So in educational context we can segregate major characteristics. These attributes can be:

1. High level of optimism, enthusiasm, sense of humor

2. High standard of expectation from their students

3. Continual self-evaluation

4. Self-criticizing, understanding and updating.

These attributes can be well observed if a bigger pool of educators is created and their continual behavioral attributes are analyzed. In this way future prospective educator’s list can be predicted and deploy them in proper institutional scenarios.

To read, follow: : http://www.brookings.edu/blogs/brown-center-chalkboard/posts/2016/02/03-teacher-moneyball-big-data-analytics-murray

Big data analytics can analyze the past behavioral data of humans. It is highly correlated to future outcomes.  The most important task is to understand how much emotional extent can be predicted accurately. By analyzing critical reasoning and judgmental decision, there will be higher chances to predict more efficient human behavior. Social media plays an important part by providing more sensitive data having higher emotional quotient. Search dynamics also help to predict future trends. Therefore, combining big data, transaction data and social data along with shopping behavioral data opens a new horizon which enables marketers to influence human behaviors and perceptions. To read, follow: : http://www.forbes.com/sites/forbesinsights/2016/02/02/has-big-data-taken-the-human-out-of-human-behavior/#2280493b170c 

Big data analytics plays an important role in supply chain management. 97% of supply chain executives have reported how big data analytics helped them to grow their business and only 17% of any particular industry have implemented this process. This process generates higher visibility and deeper insight to the customer behaviour and demand supply scenario. It also helps to discover and manage supplier relationships more effectively. Big data help to understand customer needs and make a 360 degree analysis regarding marketing channel, segmentation and acceptability. Predictability helps to create more efficient supply chain progress (increased ~10%). It identifies supply chain risk by considering the previous demand, supply scenario almost accurately. Supply Chain Traceability and recalls are data-intensive and highly correlated to supply chain risk. The ability to quickly meet customer fulfilment is an important driver. It helps in competitive advantage across all industries which can be achieved by big data analysis.

To read, follow: http://www.computerworld.com/article/3035144/data-center/overcoming-5-major-supply-chain-challenges-with-big-data-analytics.html

Data analytics are the most essential part of any organization these days and requires efficient personnel having a greater skill set in data science. But, there is not enough parity between demand and supply. According to a recent study, it was found that there is demand for computer programmers with a background in data analytics, but out of the 332,000 computer programmers in America, only 4% had the necessary skill sets. So to bridge the gap, the online training method can be a helpful process and is flexible and this in turn enhances productivity. This is a continuous process of development and helps to figure out new talent within the organization. But all these processes can only be possible if colleges and universities encourage their student to learn data science and master in those skillet.

To read, follow:  :  http://www.cio.com/article/3033887/careers-staffing/can-online-training-bridge-the-big-data-skills-gap.html

Optimization of CRM is highly correlated to the social media presence of a company. Customers frequently generate queries via social media. So there are some steps that can be followed to create a position in the customer's mind by establishing good connections between social media and CRM.

1. Right platform should be chosen.

2. Must have a dedicated human resource to handle the social media activity and patch them up with marketing team who handles CRM.

3. Instead of putting one liner FAQs, try to personally resolve critical issues in time.

4. If you have a different presence in multiple social media, then deploy time understanding the importance

5. Start listening your customers’ point of view about you and react proactively.

6. When you are segmenting your customer, you should be prepared for queries. Centralize them and solve them in real time

7. Reward your customer by discount offers, free e-books and promo offers.

To read, follow: https://www.cmscritic.com/10-steps-to-social-crm-success/

Investment in shares requires analysis of huge historical data. Analysis is the primary phase and it forecasts the future investment process. Broking house plays a clinical role in this context and charges a percentage of hike in shares. But these days such information is frequently available in different websites and are updated on a regular basis. The usage of technology for predictive analysis is hugely correlated with big data. These are limited to institutional buyers. The automation in predictive analysis requires a huge precision which is cost effective, but its implementation could be a game changer.

To read, follow: http://www.thehindubusinessline.com/markets/stock-markets/big-data-robo-analytics-to-drive-next-phase-of-growth/article8249330.ece

Any decision pertaining to designing products, environments and brand experience is closely connected to the use of colour because it depends on the buying behaviour of customers, brand perception, strategic differentiation, and user experience. But availability of information related to colour perception is limited. Organizations are using big data to analyse colour preference and perception which contains over a 100 years of data. They divided their study into four categories regarding colour data, analytic and insight:

1. Colour competitive intelligence is relevant for aggressive in brand competition.

2. Colour legal intelligence helps to identify the colour norms available to different countries.

3. Colour Research Intelligence collates colour studies that have been conducted over the past century, world-wide, about the industry and product segments.

4. Colour listening intelligence signifies how much buzz about a particular colour is popular in the market.

These all studies benefit other companies by creating their own colour mix to attract new customers, branding and dictate consumer preference trends.

To read, follow: http://www.forbes.com/sites/michellegreenwald/2016/02/17/a-new-comprehensive-4-in-1-big-data-resource-to-aid-color-innovation/#6e729df04012

The major basis of all the enterprise lies on IT system and services. What will happen if there is a major shutdown in IT section? The solution does not lie on the questions whom to contact or how to fix! But a well prepared process may lead to quick remedy. According to columnist Gene Rogers we can follow eight easy steps to manage:

1.How much time should be taken to manage the crisis so that the sudden shut down do not disturb your business model, revenue generation, customer loyalty and HR system.

2. Prepare a quick action team with at least one primary and secondary back up in each service area.

3. Create a crisis checklist where we can anticipate any upcoming issues.

4. Create predefined templates as email, text message to facilitate the process faster and smarter.

5. Devise an automated alert mechanism.

6. Separate conference line for tech staffs and business personnel to facilitate the smooth crisis management situation.

7. Create a script for the conference line to keep order.

8. Practice in regular basis to stay updated and ready for any situation.

To read, follow: http://www.sixsigmaiq.com/pex-tools-technologies/columns/are-you-ready-for-a-major-it-outage/

The stability of financial services in Asia is at stake because of the growing threat of cyber crime. The challenge is the high cost of defending mechanism against low cost cyber-attack ($1million/$1000). These attacks fuels the expansion of the cyber security market with a CAGR of 14.1%, which will be worth $33 million by 2019. Major drivers could be. 1. Financial gain through theft of money or information.  2. Politically motivated attack. And 3. Destructive attack to core business.  Unfortunately, financial sectors in the Middle East and Asia are mostly threatened by cyber threat. So to combat this crime, there must be a community defense model, i.e. sharing of cyber threat info among Financial institutions in an effort to identify and block attacks which are already initiated by US and European companies and followed by Hong Kong, Singapore, Japan & Australia. To read, follow:  http://www.scmp.com/comment/insight-opinion/article/1912324/asias-financial-services-industry-must-unite-against-threat