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

Usage of technology, right tools and knowing the significance of people and organizational components is necessary for the successful functioning of data and analytics(D&A). The malfunctioning in any of these may cause the D&A initiatives to falter. A successful D&A function encompasses more than a stock of technologies and D&A should be incorporated into all key decisions across sales, marketing, supply chain and other core functions. For the effective building of D&A capabilities a clear understanding across all sectors is required. The American sports leagues being the best example where the D&A function is used the most. They used D&A to predict the various statistics during the game. Usage of D&A was a success that the league had not achieved in the past. Keys to success included a clear strategy , a commitment across the organization to seeing it through with an unwavering eye on improving the experiences for everyone involved and also to avoid allowing strategy setting and decision making to occur in organizations, which can shadow technologies, competing versions of the truth and data analysis paralysis. It should be taken into consideration that D&A function should be a key contributor to the development & execution of business strategy, the importance of leadership should be recognized and checks should be put on cultural factors. With all these factors incorporated D&A can not just achieve growth but also let business leaders to anticipate what customers will want/need before they even know they want/need.TO READ MORE GO TO: 

 https://hbr.org/2017/06/how-to-integrate-data-and-analytics-into-every-part-of-your-organization 

Neural network algorithms are stochastic by design and the source of randomness can be fixed to make results reproducible. The random number generators can be seeded in NumPy and TensorFlow which would make most of the Keras code 100% reproducible. But, there are some cases of additional sources of randomness and we can use these ideas on how to seek them out and perhaps fix them too. Read more at: http://machinelearningmastery.com/reproducible-results-neural-networks-keras/

Google's Accelerated Mobile Pages (AMP) now represents 7% of traffic for top publishers in the US which would likely increase in the coming years, especially as smartphones have become the dominant way for consumers to interact with the world around them. Digital transformation is upending the media industry in so many ways, and brands will have to keep a close eye on developments like AMP to make sure the experiences they deliver are stellar. It will be interesting to watch AMP in the coming years as it is setting itself up to disrupt not only the mobile web for the media industry, but also the mobile web as a whole. Read more at: https://blogs.adobe.com/digitalmarketing/analytics/google-amp-one-year-later/

According to authors , a recent global survey from the medical industry workforce, threw light on the following for a business to flourish:

1)80% of the workforce in the remote counterparts, pointed out that Management/Managers should stay in touch with them, via instant messaging apps and frequent conversations over phone.

2)56% of them, stressed on video calls once a week .

3) Mandatory face-to-face interaction, via  attending monthly meetings with managers .

4) Utilizing IT system for both tracking and measuring productivity per worker.

5) Research and evaluation of tools and techniques on a regular basis to stay notified about the new techies .

6) Assuring full support and engagement of the employees in the remote areas. 

 Read more at https://www.processexcellencenetwork.com/pex-tools-technologies/articles/remote-control

According to authors, target  marketing  strategy  is the key to success ,which propels new technology into action to communicate effectively and quickly with the customers. Understanding the intricacies of both changing technology and Artificial Intelligence, is crucial for achieving success, as much of this is happening through machine learning and taking advantage of robots and AI. It’s the responsibility of the Chief Marketing Officer(CMO) to transform and spot out the same, thereby, changing the company’s identity. This requires skilled manpower, who can understand and effectively combine human interaction with machine learning. According to stats, the top revenue generator in the upcoming years will be marketing. Therefore leveraging AI is crucial to amplify the potential gains. Read more at https://www.forbes.com/forbes/welcome/?toURL=https://www.forbes.com/sites/blakemorgan/2017/06/30/how-the-cmo-can-leverage-ai-internally-and-externally/&refURL=&referrer=#6974b0db367d

According to authors, digital disruption, is an unavoidable deluge of new digital tools  that is implemented to refine the business process on the digital front. Categorising the vast arena of business, technology, industry and social changes and planning the technological stack to identify digital disruption over time, helps an organisation in escaping its adverse effects as well as flourish. Following measures will nullify its adverse impacts:1) Maintaining  lean and agile technologies, thereby ensuring flexibility to adapt to the changing environment 2) Staying connected to market research, customers and business partners 3) Implementing formal innovation management programs must be prioritised 4) Regular brainstorming sessions across different departments and teams to strengthen cooperation 5)Provisioning the requisite internal resources to ensure compatibility between existing and upcoming systems. Read more at https://www.qmarkets.net/digital-disruption-businesses-can-best-leverage/

According to authors, MLBox is a powerful  Automated Machine Learning Python library ,but, weighing  the following pros and the cons is crucial before using  it.Pros:1)Automatic identification  and classification of task 2) Pre-processing of data while reading and removing the drift variables, thereby cleaning  files 3) Fast and accurate hyperparameter  optimization and aims at low validation score 4)Constructing a Machine Learning Regressor  for forecasting  using minimum lines of code 5)Uses Entity Embedding for encoding categorical variables for creating new informative traits.  Cons: 1)Things may collapse suddenly since it’s under active development 2) Unobserved Learning enjoys no support 3)Basic Feature Engineering ,requires creating own features 3)Selection method being purely mathematical drops out variables significant on the business front 5) Not truly an Automated Machine Learning Library.Read more at https://www.analyticsvidhya.com/blog/2017/07/mlbox-library-automated-machine-learning/

MercadoLibre one of Latin America's biggest e-commerce sites, with 130 million registered users and an average of 4.6 purchases made every second of the day. It uses Google Analytics 360 to help the advertisers improving their programmatic direct campaigns. MercadoLibre started by creating audience segments for popular product lines and then made those Analytics 360 segments available to advertisers. Advertisers using DoubleClick Bid Manager could then negotiate the impression volumes they wanted at fixed CPMs for each of their priority segments. With the Programmatic Guaranteed deals, advertisers are guaranteed reach and precision, as their ads are targeted to well-defined audiences who are likely to buy their products. The results were pretty much satisfactory. Read more at: https://analytics.googleblog.com/2017/06/mercadolibre-uses-unique-audience-insights-from-analytics-360-cs.html

According to authors, the remarkable impact of Application Programming Interfaces(APIs), is in the analytics front. From accumulating data from new root to evaluation, it has radically changed the face of analytics and the core role of the citizen data scientists ,by gathering right and reliable datasets ,thereby simplifying advanced analytics and enabling them to devote more time behind identifying and interrogating new and valid questions about data. Developers can borrow functionality from other apps by allowing interaction between two pieces of codes , thereby bringing different bits of software together. Efficiency depends on use. Whether APIs will replace citizen data scientists or not, in future, is unpredictable, as, on one hand, business users will have easy access to analytics without their support and on the other hand, their role will also evolve. Read more at http://blogs.sas.com/content/hiddeninsights/2017/06/23/apis-data-scientists/