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

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

The field of AI is largely unexplored and we have only scratched the surface of what AI is really capable of.Understand the AI types will allow us to gain perspective on its capabilities and impacts in future.The degree to which an AI system can imitate human performance is used as a criterion for determining the type of AI.Based on this, AI is classified into two types-One type is based on classifying AI enabled machines based on their resemblance to the human mind , ability to think and feel.According to this system,the four types of AI are-reactive machines,limited theory machines,theory of mind and self aware AI.The second type of AI classification usually used in tech has three categories- Artificial Narrow Intelligence(ANI),Artificial General Intelligence (AGI), and Artificial Superintelligence (ASI). Read more at: https://cognitiveworld.com/articles/7-types-artificial-intelligence

Big businesses have huge repositories of data.Each company is in the race to draw more value from this data so that they are not competed out.Data is unorganized,metadata initiatives have been falling and unearthing and extraction of data has become more difficult. Data protection regulations have exacerbated the problems.Lack of data management, renders data inefficient. IO Tahoe has published on Data Catalogs-a metadata management tool as a solution to this problem. The speed of AI coupled with human learning will help companies to overcome challenges of data management.There are several kinds of data catalogues and this report is a guide on which will be best for your company.

Read more at: https://insidebigdata.com/2019/06/18/ai-driven-data-catalogs-right-business/

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/

The existence of a gender based price discrimination where women’s products are typically more expensive than men without any reasonable cause is widely known as ‘’pink tax’’. Lately, this gender discrimination has extended to car insurance with women paying more despite men being risky drivers. A recent study concluded that women especially older ones pay higher care insurance in at least 25 states. The Consumer Federation of America (CFA) revealed that insurance company not only charges different rates based on gender but also on the city in which a particular person lives in. While some countries including California, Massachusetts have already prohibited gender based car insurance pricing, we can hope that greater reliance on big data can provide some solution. Big data is greatly helpful in determining fairer and accurate insurance rates based on relevant factors. Read more at: https://channels.theinnovationenterprise.com/articles/inconsistent-correlations-between-gender-car-insurance-rates

Business intelligence (BI) tools, used to prepare, present and analyze data are now transforming the small businesses. The chief role of BI is to convert tons of raw data into useful information that the business executives can use. Small businesses will grow if and only if it can break down and analyze the information available on its server. BI tools help businesses make smarter decisions and also in Customer Relationship Management (CRM). Businesses must always find ways to understand their customers better. This is where BI solutions like YellowFin and Looker play a massive role.BI tools also help in boosting data governance and compliance. Thus BI helps small business owners avoid mistakes by keeping data accurate and up to date.Read more at: https://www.business2community.com/business-intelligence/how-business-intelligence-tools-are-transforming-small-businesses-02208030

The most powerful algorithms extensively used in the field of deep learning are neural networks. Here we focus on the artificial neural networks which are nothing but the computing system based on the structure of human brain. It is a type of machine learning which is used for detecting patterns in unstructured data. A lot of business applications today depend on neural networks to solve various complicated problems. However companies use neural networks in various ways. For instance, as explained by LinkedIn’s Deepak Agarwal, neural networks are used in LinkedIn along with text classifiers to detect spams. Neural networks are widely used in activities like marketing, finance, operations management, insurance etc. Thus the capabilities of artificial neural networks are inexhaustible. Read more at: https://www.cmswire.com/digital-experience/what-is-a-neural-network-and-how-are-businesses-using-it/

Implementing Big Data in Manufacturing innovation, the integral part of our economic success, allows for great industry gains. With respect to the objective of the manufacturers of improving their systems, big data reduces inefficiency by probing meticulously into the supply chain. Big data solves the trade-off between managing reduced cost supply and customization. It provides real-time insights to customer data which improves order-to-fulfilment times and delivers demand predictions looking at historical data sales trends. Predicaments like breakdown of manufacturing assets can be avoided using big data’s power of predictive maintenance. Big data replaces guesswork with connected supply line thereby improving strategic decision making. Before extracting the advantages of big data, it is essential that accurate data is gathered and stored, cleaned and analysed, mined and monitored besides ensuring that it is actionable.

Read more at: https://www.smartdatacollective.com/heres-how-to-implement-manufacturing-analytics-today/

Are you a frustrated blogger? Has your website traffic come to a standstill? Have your dreams of earning a six figured income been shattered? Worry not! Machine learning can come to your rescue with its releases of keyword research tools that help bloggers find profitable longtail keywords. Longtail keywords are a set of less competitive or less targeted keywords which have higher conversion rates and can maximize the visits to a website. ML driven keyword research tools provide keywords that are at least related to, even if they don’t include the exact phrase that bloggers use to run their reports. Drawbacks like omitting relevant keywords and including inapt ones exist. Nonetheless, implementation of ML is any day more effective for a successful blogging career.

Read more at: https://www.smartdatacollective.com/machine-learning-helps-bloggers-secure-more-traffic-with-long-tail-keywords/

Bad data generally refers to the faulty or flawed data. All the marketing strategies and tactics become futile if the business falls prey to bad data. Studies have found that bad data are expensive and can cost upto $3.1 trillion per year. One of the important contributors of bad data is the reliance on traditional lead generation tactics by the companies. Third party intent data is a savior to the bad data problem. It helps companies overcome the inaccuracies that might have existed in their Customer Relationship Management (CRM) for years. Companies must ensure that the data provider is a trusted one. To overcome bad data problem, the intent data must be accurate, actionable and targeted. Read more at: https://www.business2community.com/marketing/solving-the-bad-data-problem-in-marketing-02210818

Contrary to the common belief that Big Data and green business have little intersection, the former provides an array of solutions to sustainability issues faced by businesses. Benefits of big data can alleviate threats of climate change in future. According to Annie Qureshi, the author of the original blog, following the IPCC report on climate change in October 2018, businesses are expected to shift their investments to green tech companies from fossil fuel resources. Prospective investors can be attracted if local investors focus on big data and predict to yield high return for investors or by launching social media campaigns. As more and more companies are meeting UN sustainability goals, big data is making the world greener. Hence investing in big data should help green companies flourish.

Read more at: https://www.smartdatacollective.com/how-to-use-data-analytics-to-launch-sustainable-technology-business/

Big Data is facilitating the marketing profession by giving marketers the advantage of detailed analytics capabilities. Visual social media networks like Pinterest and Instagram collect enormous data on their users, optimizing which, marketers can reach potential customers. This is where big data’s role comes in. In order for tracking the performance of different posts to derive patterns, online tools use machine learning to help marketers develop more engrossing pictures. Big data helps in keyword analysis as well where marketers look at the monthly search volume of different keywords to reach more customers. Shrewd marketers use big data get more views and hence expand their audience. Marketers using social networks need to keep up with new trends which be forecasted and prepared for using predictive analytics.

Read more at: https://www.smartdatacollective.com/data-optimization-facilitates-pinterest-and-instagram-marketing/

In order for fast procession of data, companies today increasingly demand for stream processing. Big data is an enormous collection of structured and unstructured data which are analysed by companies for making smart decisions, reducing cost and time, developing new products and optimizing offerings. Being a means of reviewing real time data while it’s still in motion, Stream Processing, which finds its application in financial institutions, is beneficial as it accelerates data delivery and enhances real time analytics, deepens data cognizance of companies by working together with machine learning, etc. With big data stream processing, emerging companies can quickly transform time into innovation, respond to issues faster besides realizing the game changing ability of real time data. In this era of continuous evolution of technology, emerging markets and businesses should equip streaming applications to resolve business problems. 

Read more at: https://www.smartdatacollective.com/big-data-sets-standards-in-stream-processing/

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/