As the phrase goes, “everything that can be digitized, will be digitized”, is fast replaced by “If something can be run by algorithms, it will be”. Algorithms are supposed to be performing the following tasks: • Reading resumes: With natural language processing, resumes can be read faster and with more careful eyes. • Using spreadsheets: Soon the analysis made by experts using spreadsheets would be taken over by AI. • Hiring consultants: Since the analysis will all be done by algorithms, hiring consultants is really not needed as before. Hence, for coping up with the changes, one needs to get acquainted with the programs, rent a machine learning expert to design algorithms or make it on your own and invest for the future by learning new software. Read more at:https://www.experfy.com/blog/algorithms-are-replacing-leadership-strategies

NASA has used AI in human spaceflight, scientific analysis and autonomous systems. Multiple programs like CIMON, ExMC, ASE, Multi-temporal Anomaly Detection for SAR Earth Observations, FDL, robots and rovers are currently available at NASA. It is now working on overcoming the barriers that once blocked it from innovations in AI and Machine Learning. Although Machine Learning has been in existence for 60 years, benefits couldn’t be reaped by NASA because according to Brian Thomas, a NASA agency data scientist and program manager for Open Innovation, they are being held back. Read more at: https://www.aitrends.com/ai-world-government/how-nasa-wants-to-explore-ai/

With every passing day, data and not instincts, are used for the expanding of business. Data is the new gold, as it helps in determining trend, offering better customer experience, responding better to market demands. However, given the data size is so big, Data Visualization is opted for, making the interpretations easier. The major reasons that data visualization is crucial are: • Data visualizations amplify a story with pictures and visuals. • Data visualizations makes difficult data comprehensible. • Data visualizations help in decision analysis. Read more at: https://www.experfy.com/blog/the-value-of-visual-data-in-decision-making

Financial analysis s beneficial for businesses in the following ways: • Cutting costs: Financial data relating to investments and cash flows are analysed. • Making investments: Financial analysis helps in predicting the returns from investments, thereby enabling the companies to go for profitable investments only. • Forecasting the future: The future of the company can also be forecasted. • Following business trends: Financial analysis relies upon the current business trends and success rates of businesses in the sector. Such analysis helps in recovering faster in case the market suddenly drops. • Management: Financial management is also tracked by the financial analysts which helps in increasing efficiency overtime. Read more at: https://bigdataanalyticsnews.com/big-data-improve-ecommerce-for-businesses-customers/

Predictive modelling software is known for training the model with the dataset with known results to predict outcomes for the new data. The two common types of predictive models are, classification model (example, predict outcome when a component fails) and regression models (predicts a number). The benefits of predictive analysis are: • Improved production efficiency: It allows for effective inventory forecasting, production rates for meeting demand, and the like. • Improved Decision making: It identifies patterns and trends for the data, enabling easy decision making. • Enhanced risk reduction: Predictive analysis, as the name suggests, enables prediction about the future. This is most helpful for a firm to save it from the upcoming risks. • Enhanced fraud detection: Being aware of the trend, a change becomes helpful in detection of fraud. • Targeted, personalized marketing campaigns: Predictive analysis helps in knowing the structure of the market and helps in closely targeting and personalizing marketing campaigns to attract customers. Read more at: https://blogs.opentext.com/predictive-analytics/

Before the introduction of Big Data, only calculated guesses were made by the companies to optimize pricing and forecast demand. Big Data has contributed big time in facilitating eCommerce activities. Some of the ways are: • Predicting trends: This helps in determining the trend, and the type of customers they will face in near future, and keep the inventory accordingly. • Pricing optimization: It helps in calculating the competitors’ position and make decisions about the set of products. • Demand forecast: Studying the data, the expected time of high or low sales can be predicted. • Flexible pricing policy: Prices can be changed time to time depending upon the concerned factors. Big Data provides the data required by managers for expanding the business, taking into consideration every possible factor. Read more at: https://bigdataanalyticsnews.com/big-data-improve-ecommerce-for-businesses-customers/

Machine Learning and Deep Learning both uses the algorithms fed into them. While in the first, the algorithm needs to be told how to make accurate prediction, in the latter, the algorithms are fed via neural networks, making the operation similar to a human brain and involving lower chances of mistakes as compared to Machine Learning. While Machine Learning gives result for a numerical and text field, Deep Learning also enables face, voice and handwriting recognition. Also, with new data fed into the system, the accuracy rates by Deep Learning are much more than by Machine Learning. Although Deep Learning is anyday better than Machine Learning, Machine Learning plays a vital role in the existing economy. Read more at https://www.analyticsindiamag.com/understanding-difference-deep-learning-machine-learning/

Google’s internet bot detector has evolved over the years from Captcha to reCaptcha to reCaptcha V3. Now, no more boxes need to be checked, nor is identifying objects or alphabets required. Studying the way an individual navigates through a website, conclusions can be drawn on it being a bot or not. This improvement however comes in at the cost of the user’s privacy. According to a researcher, Google uses cookies to identify whether a user is a bot or not; the same cookies which enable us to open new tabs and open accounts without the need of logging in everytime. Another researcher however states that a browser connected with a Google account is more secure than the one which isn’t. Hence, although security is gained, more of the user’s data is also going into the hands of Google. Read more at: https://www.fastcompany.com/90369697/googles-new-recaptcha-has-a-dark-side

Google maps new features not only includes the updates of traffic, but also how crowded the public transport will be. Google has been asking people to fill up forms wherein they are asked about their departure time and number of seats available. This data helped the Google maps in predicting the peak time and the most populated stops. Similar study has been done about predicting the crowds at restaurants. Also, delays in bus and their expected time of arrival is notified by the Google maps, which are available on both Windows and iOS for almost 200 cities. Read more at https://techcrunch.com/2019/06/27/google-maps-can-now-predict-how-crowded-your-bus-or-train-will-be/

With advancement in Internet of Things (IoTs) such as asking the personal digital assistant to read the news, give weather reports, turn on/off the lights, locking up the house and many more, our lives are being simplified, though not as seamless as expected. In Edsger Dijkstra’s words, “Simplicity is a great virtue but it requires hard work to achieve it.” It is analytics that trains the technology for doing hard work so that its virtue can be enjoyed by the people. Hence, with every passing day, as IoT is taking over, Analytics market is becoming more complex since machines have their own languages and specifications and idiosyncrasies. Read more at https://www.experfy.com/blog/to-serve-man-the-internet-of-things-and-analytics

Walmart acquired Flipkart is one of the two biggest e-commerce platforms in India with eight million shipments per month on an average. With ever increasing speed of people coming online each day, Walmart new Automated Guided Vehicles (AGVs) will help in meeting these demands faster. This pilot project of sortation will be applied at Flipkart’s Soukya sortation center in Bangalore, where the 100 self-guided robots will sort the packages according to the delivery pin codes. While these AVGs are expected to increase efficiency by 60%, i.e. 4500 shipments in an hour, the easy mobility of the AVGs will always help Flipkart in expansion of supply chain operations. However, according to Jeff Bezos, AVGs won’t take away employment opportunities but only increase efficiency. Read more at https://www.businessinsider.in/flipkart-announces-delivery-robots-automation/articleshow/68493938.cms

Few factors where data analytics can be seen creating an impact on this sector as stated below: • Reporting and Business Intelligence: With the help of reporting and dashboards, the travel companies can draw inferences. The most important factor for this industry is seasonality, which can be studied by performing analytical operations on the data. • Alerting and monitoring system: Anomalies and rare observations can be detected which is not possible manually due to huge chunks of data available. • Optimization and efficiency building: Analytics help organizations prioritize their investments and redirect them towards high priority factors. • Personalization: Personalizing always attracts attention of customers. • Enhancing business strategy and customer experience: Along with variations in seasonality, forecasting is equally necessary to define the business goals. Read more at https://www.moneycontrol.com/news/technology/travelling-on-data-how-data-analytics-is-transforming-the-travel-industry-4131941.html

Few factors where data analytics can be seen creating an impact on this sector as stated below: • Reporting and Business Intelligence: With the help of reporting and dashboards, the travel companies can draw inferences. The most important factor for this industry is seasonality, which can be studied by performing analytical operations on the data. • Alerting and monitoring system: Anomalies and rare observations can be detected which is not possible manually due to huge chunks of data available. • Optimization and efficiency building: Analytics help organizations prioritize their investments and redirect them towards high priority factors. • Personalization: Personalizing always attracts attention of customers. • Enhancing business strategy and customer experience: Along with variations in seasonality, forecasting is equally necessary to define the business goals. Read more at https://www.moneycontrol.com/news/technology/travelling-on-data-how-data-analytics-is-transforming-the-travel-industry-4131941.html

Increases in data implies more house-keeping of the same for drawing inferences. Robotic Process Automation (RPA) does that easily by automating manual, rule based and repetitive human task for focusing on other important tasks. RPA reads the data of the organization, cleans the data as per the business requirements of the firm, organizes it and sends through an automated workflow process. This data consists of only the relevant data from the lot and are easy to retrieve. This data is thus ready for being analyzed. The major advantage of RPA is, it makes the data strategic, efficient and relevant which keeps guesswork out of the process. Read more at https://www.experfy.com/blog/why-todays-business-decision-makers-need-data-and-robots

Coca Cola is one of the biggest companies and a top brand in its domain. Advertising plays a big role in building a brand and maintaining its reputation. This consistency has been witnessed with this brand which has come with the help of Big Data. Big data was first used by Coca Cola in gauging the effectiveness of their social media posts. Responses to the campaigns showed the user patterns which would indicate the success of the same. Data mining tools help in monitoring brands’ presence over social media and determining its presence in pictures. Hence this led to undertaking many branding strategies, one of them being ‘Bring Back Surge’ campaign. As a result, new flavors were introduced, AI applied in machines, mobile payments, special offers and others like optimizing cost, supply chain management and promotion code scanning using OCR. Read more at: https://www.analyticsindiamag.com/coca-cola-leans-on-data-analytics-ai-for-deeper-industry-insights/

Every brand’s prior importance is designing customer experiences, keeping in mind the self service which is fast coming in trend. Gartner states 81% of the customers try finding the solutions themselves first and seek expert advice only when they can’t. Five rules for creating beneficial self-service options are:

• Making IVR options relevant which enables the customers to easily get to the option needed and can contact an agent in case of need.

• Training chatbots regularly by keeping them updated on information like brand prices, new product, product description etc. Also, availability of real time customer data which would provide assistance. Another step can be analyzing the tone of customers for providing a smoother conversation.

• Keeping agents on standby because computer programs cannot always resolve all kinds of problems.

• Updating the FAQs by analyzing customer feedback and service transcripts

• Using video tutorials so that the customer queries can be resolved having both subtitles and voiceovers in various languages.

Read more at: https://www.vocalcom.com/en/blog/digital-customer-engagement/5-rules-for-giving-customers-the-self-service-they-want/

Overtime the demand for wearables, like Fitbit, are increasing. The owners of the product get the details about themselves. However, at a large scale this data is beneficial for various sectors like the insurance companies, the pharmaceutical companies, doctors, etc. But this aggregate data is available only with the brand owner. Considering the insurance company, it can come into an agreement with its insurers, wherein the insurers would use the Fitbit and report the data to the company, which in return would give special discounts on premium amount. This aggregate data, or the Big Data, can then be used for the cost-benefit analysis. Faced with the fear of being misreported, the insurance companies might also go for vertical integration with the Fitbit companies, ensuring a greater market for the same in return of the Big Data. This would ensure a substantial portion of the market to the firm. The insurance company on the other hand would be successful in maximizing its profits. Hence, vertical integration and Big Data can do wonders in these markets. Read more at http://bigdatatobigprofits.com/2015/12/04/lessons-on-big-data-risk-and-the-vertical-integration-of-wearables-and-startups-2/

Gmail has become a huge platform with almost 1.2 billion monthly users and holds a 20% share of the global email market. However, Gmail is not really secure as they require personal information such as name, interests, who is one talking to, and many more things. Hence, for trusting Gmail, several tips should be implemented for ensuring maximum security. • Big Data plays a big role in cybersecurity and malware protection. Machine Learning tools are capable of understanding newest thus it is advisable to invest in email specific antivirus software. • Enabling two-step verification, again made reliable by the Big Data. Along with this is the easy-to-use update which adds to the security. • Upgrading the browser whenever possible reduces changes of cybercrimes. • Using a sophisticated password. Read more at: https://www.smartdatacollective.com/4-brilliant-ways-to-use-big-data-to-boost-gmail-security/

The main motive of bloggers is getting traffic to their websites. They therefore focus on competitive high-volume keywords. But, unfortunately, it is not these, but longtail keywords that will serve the purpose. There are two reasons behind preferring such keywords are: • Keywords not targeted by other bloggers can be used. This uniqueness will automatically increase traffic. • Many a times people are specific with certain keywords. Acknowledging and using them will also be a smart move. After longtail keywords have been used, the machine learning helps further in increasing the traffic. With machine learning, keyword research tools are getting more efficient at finding better contextual relationship between the terms. This therefore enables the bloggers to have access to a much more exhaustive list of longtail keywords to choose from. Although limitations still exist, improvements are faster. Read more https://www.smartdatacollective.com/machine-learning-helps-bloggers-secure-more-traffic-with-long-tail-keywords/

Building good relationship with customers satisfies them with their purchases and makes them recommend it to others. With increasing competition in the online market, personalizing customer experience is one good way to attract customers. Success rates are as high as 77%. The ways to personalize experience are: • People tend to search for goods online and purchase in store. Hence, by using geological tools, customers can be notified about nearest shops and the ongoing deals which provokes them to make an early purchase. • Saving information like card details, shipping information, preferences saves time and gives customers a good experience. • Studying the customer preference and making personalized recommendations attracts more customers. • Determining the geographical location of the customers and using their native language and quoting prices in their local currencies gives the customers a clearer overview and therefore convincing them to make the purchase. • Customers are more driven by personalized videos of the products as compared to written description as watching a video involves almost no effort. Read more at https://www.vocalcom.com/en/blog/customer-experience/5-innovative-ways-to-personalize-the-customer-experience/