Both terms web analytics and digital analytics are interchangeable. But there is a difference between two of them. When Web analytics association changed its name to the digital analytics association then the word digital analytics came up. During the early days of the internet, Web analytics were analyzing the website data, such as users, visitors, links and many more alike. When other forms of online came like emails, search, social, etc., then a new term called digital analytics came into being where all these channels were analyzed. Now all the online channels have been transformed from web analytics tools to digital analytics tools. Web analytics is the analysis of website data, whereas digital analytics is an analysis of all data from digital channels that includes websites also. But till now web analytics are still searched more than digital analytics according to Google Trends chart. Read more at: http://webanalysis.blogspot.in/#axzz4hutH4lMG

Few challenges being faced in translating the lessons of predicting analytics from other verticals in manufacturing. The objective of this predictive analytics is to get the correct business decisions and it will impact the design and service of the product. The data is being updated continuously through their supply chain. The predictive models are used to connect the real world data to digital twin models of the virtual world. This helps in better understanding and working of their business plus with the on the factory work. Predictive analytics help to find the issues related with the product quality, performance and its features. These helps in better designing the product features and make it to optimum use of it. The predictive model is quite accurate in giving information about the risk failure, improving the machines to put in a better use as well as it gives the best correlation between job characteristics and job failure. Models are being trained through environmental data and IoT data and few factors which affect such data too such as environmental hazards, weather and many more. Its benefit for the business to take predictive analytics into consideration. https://www.ngdata.com/ways-to-improve-customer-experience/

According to authors, innovations in the areas of Artificial Intelligence(AI),Machine Learning and Deep Learning are beginning to dominate the technology landscape but the actual user experience and concerns about privacy and security are obstacles that can prevent AI from reaching its potential. Despite it’s negative implications, a Consumer Intelligence Report by PwC, revealed, that most consumers believe AI will help humankind, by solving complex problems, like fatal diseases, city traffic, cybercrime, infrastructure and fraud, that plague modern societies , thereby helping people to live more fulfilling lives. AI could revolutionize  personalized healthcare by analyzing data thus helping in maximizing life expectancy and enhancing wellbeing.AI will expand access to financial, medical, legal and transportation services to those with lower incomes thus emerging  both as a process and a product that instills trust and transparency in consumers. Read more at https://aitrends.com/security/consumers-welcome-ai-despite-lingering-privacy-concerns/

According to authors, modern-day marvels are the result of machine learning, which are programs that combine through millions of pieces of data and start making correlations and predictions about the world , by using machines that uses cold hard data to make decisions that are sometimes  more accurate than a human’s, thereby reducing biases. Computers don’t hold any inherent biases, as machine  knows only one approach i.e. the objective analysis and are capable of analyzing massive amounts of information, thus having  a distinct advantage over humans. Utilizing the data for machine learning, can uncover contradictory and surprising results by making data more accessible, more understandable and  enabling the organization to achieve a new level of business intelligence, thus empowering decision makers at all levels with a powerful tool. Read more at https://aitrends.com/machine-learning/machine-learning-cure-decision-bias/

According to authors, the implication of big data is the quantity is paramount, the returns generated do not match the quantity of data generated. Experts point out, it is not per se the data that should be big, but the primary factor that counts is the diversity of data, the amount of richness they provide and the focus on accelerating human understanding of data , which has the potential to create output subject to increasing returns. More data retards innovation, the speed of experimentation and iteration. However IT teams helps in bringing order to chaos, in data and analytics, by managing data infrastructure, such as data warehouses and production processes . Data scientists, who’re occupying the space between IT and business consumers , have made enormous strides in getting grip on their data, analyzing and acting on it, thereby avoiding imbalance. Read more at https://aitrends.com/big-data/three-big-data-developments-no-one-is-talking-about/

According to authors, the development of Artificial Intelligence (AI) creates several opportunities for retailers to improve their customer services , insights and business processes. AI makes it possible to generate insights on a scale like never before, it does this by combining customer data  across all platforms( from social media to CRM) like past purchases, search habits, click behavior, age, gender, season of the year and various other variables and self learning algorithms. By crawling the web and aggregating various forms of customer data, AI gives retailers the opportunity to engage with customers on a more personal level. Through chat applications such as Facebook and Messenger and by using chat bots on websites, the potential customers can communicate with the retailers using speech or text, that will assess and answer customer queries, thereby assisting in the selection process and helping in the execution of simple tasks. Read more at https://aitrends.com/retail/robots-ai-retail-8-things-must-know/

According to authors, the days of journeying to a travel agency and sitting at the desk of an agent to book a trip have all but disappeared as technology is increasingly putting that level of personalised service in the palms of our hands by launching travel apps that incorporate artificial intelligence and technology .One such app is the Green Card app, that simplifies the process of getting a green card to  enter  into a foreign country, on the basis of a bot, that files out a questionnaire ,which when answered,  generates  a package of documents that can be filed with U.S. Citizenship and Immigration Services to complete the application process. This saves ample time. Another personal travel assistant Mezi,  designed for travel management companies, corporate and travel agents was launched two years ago and claims to have AI capabilities that customises travel suggestions based on past searches and online habits. Read more at https://aitrends.com/mobile/a-i-innovation-finds-a-home-on-mobile-devices/

According to authors, two of the machine learning APIs introduced by Google in the month of March, has moved forward into a new dimension i.e. open beta status. Cloud Natural Language APIs which analyses syntactically and assigns a constituent structure to the meaning of texts, helps in finding out the sentiments expressed via texts and online reviews, the syntax of the text and assists in understanding  entities like people, places, events, products, and media. New York used this techie for exploring sentiment analysis of  the stories published in The  New York Times and it was found that relevant updates about news didn’t enjoy a favourable environment, whereas, the arts stories enjoyed positive support. Read more at https://aitrends.com/business/googles-cloud-adds-machine-learning-apis/

Deep Learning(DL) is a subfield of Machine learning concerned with algorithms inspired by the structure and function of the brain called Artificial Neural Networks. It  interprets the raw data through multiple processing layers, where each of these layers, uses the output of the previous one as its input, thus  creating more abstract presentation, tackling conceptual problems ,like image classification and natural language processing  and helping to infer logically. Industries that leverage Machine Learning at present , can switch over to DL approaches in future as it’s an approach of AI , which is showing great promise when it comes to developing the autonomous, self-teaching systems which are revolutionising many industries. DL drives sales, increases engagement  and improves user experience, thus it  will be the future of Personalization, which enables a business organization to enjoy amass customer appreciation. Read more at  https://aitrends.com/deep-learning/deep-learning-personalizing-internet/

Business analytics and business intelligence are like two sides of a coin. But there is a difference between them. Business analytics is like an umbrella term and intelligence is a part of it together with other aspects of business applications. Once a person runs a business, that person will be able to understand the difference between them, that is, business intelligence is like accessing to all kinds of business related data and software's and put them into the analysis. Business analytics is something using your business intelligence into your data and optimizing the performance of the business. To have a successful business, it is important to follow both. Business intelligence is generally used to look over the previous data, whereas business analytics look to the future needs of the business. It's necessary for a businessman to understand its difference for making any business decisions or predicting for the future. Read more at: http://www.analyticbridge.com/profiles/blogs/business-analytics-and-intelligence-compared

As from the past record, Indian retail industry transformed a lot. It can cross over USS $1.3 trillion by 2020. It accounts over 10 per cent of the Indian GDP. And now as GST implementation brings over greater transparency, reduced trade barriers and improved credit. 1.) pricing and promotions: Due to GST product pricing will be affected and also companies in B2C segment will be significantly affected. GST will impact prices of goods at every stage in the supply chain and retailers will need to review their prices studies by vendors. 2.) EOSS(end of season sale): there will be difficulty in clearing the stock of last year.3.) reduced rates of apparel and  changing purchase pattern. Read more at:  http://analyticsindiamag.com/can-retail-analytics-step-game-big-box-stores-rush-embrace-gst/

So you have heard of these 2 brothers (Chetan and Rishi), but you didn’t know how they re-built the success of their family business. So Chetan did Bachelors in petrochemical engineering, & MBA . Rishi did Bachelors in Science and Business Administration. But they came to re-built their family business of manufacturing ceramic tiles, Kajaria Ceramics Limited. It was an year of 2000, IT revolution in India had just started, and Rishi started an online platform Floortoroof.com to combine the agents all over country. After their visit to China, they found out, they can easily import and sell the tiles into India, of course they have to cut off certain costs. Also to expand Chetan added partners to increase their reach to the local market. Also with introduction of SAP and IT integration, Rishi transformed day to day business. And it turns out all in favor with the highest profitability margin of over 18 percent and now it is all set to open a new plant in Rajasthan. Read more at: https://www.entrepreneur.com/article/296656

We all know Watson(IBM computer) ‘s prowess already been tested in cancer research. Watson has proven its worth in editing a thriller film trailer, composing music, providing excellent customer service. But has Watson proven its worth in the field of fashion? The fact that IBM is betting big on Watson is abundantly clear and it is now being leveraged by big fashion houses to utilize social data to better interact with customers, improve sales with highly targeted marketing campaigns and predict customer orders.  The AI-based collection, aptly titled Future of Bollywood Fashion was created by analyzing around 600,000 publicly available historical fashion runway images from the last decade. Read more at: http://analyticsindiamag.com/future-indian-fashion-ai-watson-makes-splashy-debut-indian-runway/

There are lot of challenges faced by HR, from slowed hiring to restructuring, after the layoff  from IT industry. HR has considerably lagged behind in the use of big data and analytics in India. And according to a study, only 5% of big-data investments were in made in human resources. HR analytics is critical not just from talent acquisition and management perspective, but also cost optimisation. According to Arjun Pratap Singh, “AI and analytics are the driving force behind HR technology and this will drive the new employment economy. From talent acquisition and workforce optimisation to workforce transformation, AI be the strategic enabler to HR”. Data-backed decisions lend transparency to processes such as annual reviews. In case of retrenchment, data-driven decisions lend validity to the process. It is the absence of the data that HR analytics is lagging behind. Read more at: http://analyticsindiamag.com/can-hr-analytics-solve-major-talent-challenges-times-mass-layoffs/

According to a report by ET , Tata Group buys a controlling stake in beleaguered national carrier Air India. Irony is, it’ll go back to same group which had built and nurtured it into one of the world’s finest airlines. Tata Sons set up Tata airlines in 1932. JRD Tata, the legendary entrepreneur, himself flew the first flight between Karachi and Mumbai.Then it became a public company and was renamed Air India. In 1953, prime minister Jawaharlal Nehru, a Fabian socialist, decided to nationalize Air India “through the back door”. Living upto Nehru’s sentiment, Air India today reels under a debt of about Rs 50,000 crore and has never made a profit in a decade, despite eating up Rs 24,000 crore of a government bailout package. Even Tatas are concerned now over its huge debt. While there is no certainty if Tatas can turn Air India around if they decide to buy a controlling stake. Read more at : http://economictimes.indiatimes.com/industry/transportation/airlines-/-aviation/how-history-will-come-full-circle-if-tatas-buy-air-india/articleshow/59253577.cms

According to the authors, data and analytics should be the backbone of every area of organisation, and in order to build a strong D&A function, it is required to take help of organisational people and other components. In order to  meet the business goals, it is important to adopt a strategic measure to initiate the data analysis which can be done by a team of skillful data and software engineers, who can be amalgamated with the existing users and providers of D&A and can work cohesively with the non-D&A fellow colleagues, to work towards achieving the goals in a more realistic way. According to KPMG’s 2016 CIO Survey, data analytics is the most sought-after technology skill which should be utilised to its best. Read more at https://hbr.org/2017/06/how-to-integrate-data-and-analytics-into-every-part-of-your-organization

According to the author, in this age of technology and machines, where almost everything is being replaced by the machines for avoiding errors and for the simplification of work, the old definition of being smart is no longer valid. The new definition of being smart is the one that makes us improve our high order thinking skills. The new definition of being smart is determined by the quality of our analytical skills, effective listening and the ability to relate for better understanding of the goals. Read more at http://smmry.com/https://hbr.org/2017/06/in-the-ai-age-being-smart-will-mean-something-completely-different#&SM_LENGTH=7

Natural language processing is the amalgamation of artificial intelligence and computational linguistics so that there can be smooth conversation between the computers and humans, and it does so by empowering the computer to analyze the input, that is, what is being said by the user and processes the contextual meaning. Following are the areas where NLP is being used efficiently: 1) NLP is used for the purpose of communicating meaningful information extracted from the complex big data sources 2) NLP is used for data privacy, in comparison to the traditional old methods, it helps the businesses to detect the phishing and malware sites in a much easier way. 3) NLP is used for the better understanding of the questions of the users and answering them in a seemingly natural human language. Read more at http://www.dataversity.net/natural-language-processing/

Telecom companies these days should be very active in providing their services and shift their attention from customer acquisition to customer retention in order to survive the head-to-head competition in this extremely fickle market. The companies should use the right technology to study their customers and make the right business decisions. Understanding the consumers would help the companies in efficient targeting and positioning in the market. But, the sheer magnitude of the data in the telecom industry might be a problem while storing and analysing. So, to acquire a more practical information, the companies should ask the right questions and find the correct software to be used for data analysis, so as to reach their goals efficiently. Read more at

https://www.smartdatacollective.com/customer-behavior-analysis-telecom-arena/

Personalized Marketing is all about using customer information- their interests and behavior and to deliver the valuable information at the right place, at the right time, to the right person. It is valuable because we are barraged with so many generic ads that it gets fade away into the background. Furthermore, personalized marketing filters out all the gratuitous information and gives control to the consumer. It takes into account that customer is a narcissist. There are certain benefits of personalized marketing. Its main goal is to increase sales. It helps in building strong relationships with the customer and improving their experience with the brand. Personalized marketing technology works on analytical data. So, the more data we use, the easier it will be to make informed choices.  But, it is a major challenge to gather the right data and understand the customer's interest and behavior. Read more at: http://www.business2community.com/marketing/what-is-personalization-in-marketing-01871212