Big Data and AI Are Helping the Aviation Industry Reach New Heights

| January 31, 2018

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Could Big Data be supercharged by advances in hardware, software & the strategies data scientists use to unlock amazing user experiences? You bet! Here’s how. The aviation industry remains a true behemoth in the economic world, as it continues to grow at an incredible rate year-over-year. In fact, it experienced something of a golden age between 2009 and 2014, when the industry grew at a compound annual growth rate of around 9.5% before reaching a cumulative value of $751 billion. While the industry experienced a brief decline between 2015 and 2016, it enjoyed a stellar 2017 and  is set to achieved record peak commercial revenues of $824 billion by the end of this year. Much of this growth is based on sustained demand, as consumer spending continues to increase across the globe. Similarly, the market has also thrived on the back of innovation and new data analysis technologies, which have helped brands to enhance the customer experience, personalize discounts and create safer aircraft for travelling. Big data and AI are already powering exciting innovations in the aviation industry. In this post we’ll look at how they will become even more influential in 2018, across a broad range of industries.

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OpsVeda, Inc.

OpsVeda Business Execution Platform provides CONTINUOUS, RELEVANT & PRESCRIPTIVE insight to enterprise customers. We enable real time 'actionable' visibility into exceptions across execution processes spanning order fulfillment, supply management, shipment logistics and channel operations. OpsVeda Application Suite, powered by SAP HANA, brings big data predictive analytics and deep business process expertise together, to deliver outcomes for customers out of the box. Our customers span the high-tech, consumer goods, apparel & footwear and life sciences industries, typically with revenues greater than $200M. OpsVeda provides the complete solution stack – real time data streaming (back-end ERP/ carriers/ external partners/ legacy systems), data discovery, rules management, end user visualization, collaboration, and alerting. Deployed on cloud or on-premise, and accessed through desktop or mobile. All in On Platform. Deployed in 30 days…

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Predictive Analytics in Finance: Understanding What 2022 Holds

Article | August 9, 2021

The financial industry has been going through digital transformation for years. Digital technologies have helped to automate manual and tedious tasks like processing and reporting of historical data to forecasting and financial predictive analytics. The financial services industry owes its success to data. Data is constantly evolving in the form of market trends, client investment, customer service, campaigns. Data gives a boost to banking strategies. As reported by Accenture in a recent survey, 78 percent of banks have made the shift to using data for operations; however, only seven percent of them have extended to using predictive analytics in finance. Predictive analytics in finance has had a slow but steady start. It is an area of growing interest for banks and other institutions as new newer technologies launch in the market. To complete your company’s digital transformation, data analytics in finance will make a difference in that process. To be successful, organizations must have the ability to adapt to changes. Having predictive analytics on your side, your organization can deal with ever-changing circumstances with less to no difficulty. Understanding Predictive Analytics: What is it? Predictive analytics is a process of interpreting data to measure any possible future outcomes. It is carried out with the help of statistical modeling, historical data sets, and machine learning. The collected historical data is fed into an algorithm that recognizes patterns and forecast trends and possible future behavior from days to years in advance. Analyzing historical data and predicting the future has been an old practice in the finance sector. Banks and financial institutions have been evaluating past events or historical data for a long time now. Making precise forecasts in trends and analyzing data becomes easier due to predictive analytics. There is a wider scope to predictive efforts with more speed and accuracy and apply them throughout strategic and tactical business practice areas. Predictive Analytics in the Financial Sector: What are the Benefits? Many organizations are ready to accept the positive applications of predictive analytics but remain skeptical about the return on investment. It is worth understanding the potential of predictive analytics to any business big or small. It doesn’t matter if you are not in the banking sector to benefit from taking a peek into the future of financial performance. Any finance and accounting department can take advantage of advanced predictive analytics for the following reasons: Precise Monitoring The technology keeps a regular track of the consistency between expectations and reality to warn you about possible gaps. Risk Alleviating Analytics accurately helps you identify any possible threats to your business and warns you. Enhanced User Experience Predictive analytics guides you to recognize the strengths of your business and lets you know how to maximize customer satisfaction. Analyzed Decision Making You can understand your customers better with predictive analytics. With this information, you can correctly match your customers with the product in a better way. Importance of Predictive Analytics Most successful banking and financial institutions depend on predictive analytics because it simplifies and integrates data to increase profits for companies. Predictive analytics can improve different finance processes. But the importance of analytics goes beyond just banking services and actually goes into a better quality of customer service. Better customer service is only possible because of the advanced technology that shares customer feedback and preferences throughout the organization, in turn giving relevant information to every employee to make necessary product enhancements. To understand the importance of predictive analytics, below are some of its use cases: Customer first Predictive analytics in financial institutions and banking give you a complete profile of your customer base. It is impossible to contact every customer and interview them about their likes, needs and wants. This is where big data analytics in finance comes into play. It gives you the whole information about your customers regardless of the services they subscribe. Customers usually don’t have the same needs throughout their lives. As they grow older and have families, their financial needs change accordingly. For instance, a young person considering getting married will always try and save monetarily to buy a house, life insurance, college funds, whereas an older couple will save that money for their retirement. Apart from enabling different financial services, predictive analytics empowers you to serve individual customers with ease. Let’s take an example. When a customer applies for a loan, predictive financial services can help you analyze if the customer can repay the loan. Predictive analytics also helps offer alternative services like secured loans to customers who may not qualify for the originally applied services. Online Banking Made Better Consumer interest fluctuates in spikes. Predictive analytics informs managers enough in advance so they can set up online infrastructures in those areas. Predictive analytics has made it easier to identify a possible customer base. For example, it can provide metrics to the marketing teams. In turn, the marketing teams can target the customers with ads for probable mortgage loans or business loans in hopes of converting them into their customers. Data analytics in finance also helps in preventing and detecting fraud and abuse. Although detecting fraud doesn’t necessarily fall under predictive analytics, it can inform the IT department about potential scammers and which online services must be protected. Foreseeing Market Variations Predictive analytics can predict market variations and changes. By combining internal and external data, your organization can predict revenue growth in particular market sectors. For nascent or growing companies, predicting market changes is an important ability. Profitable companies should also be reviewed through predictive analytics to generate demand projections owing to the uncertainties caused by the Covid-19 pandemic. Your return on investment can grow or reduce even with the minutest changes to the growth plans that would seriously impact investor confidence in the future. Predictive analytics also help to establish which marketing campaigns are working and which strategies need to change. Predictive Analytics and the Future: What Next? Technological improvements have allowed predictive analytics in finance to improve and change constantly. Any organization can use customized data solutions to meet your customers’ needs and reach new ones efficiently. Your organization can use predictive analytics to move your business and products ahead and understand how the market will thrive, giving you the much needed heads up you would need to change your strategies and tactics. Frequently Asked Questions Is predictive analytics is the future of finance? Predictive analytics is called the ‘future of financial software,’ which means it can provide accurate planning and cost-effectiveness. How can analytics be used in finance? Analytics helps in predicting revenue, improve supply chains, identify trouble spots, understand where the company is bleeding money, and fraud detection. How do predictive analytics benefit financial institutions? Predictive analytics can help financial institutions and customers detect fraud, financial management, predicting markets, improving products, better user experience, etc. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "Is predictive analytics is the future of finance?", "acceptedAnswer": { "@type": "Answer", "text": "Predictive analytics is called the ‘future of financial software,’ which means it can provide accurate planning and cost-effectiveness." } },{ "@type": "Question", "name": "How can analytics be used in finance?", "acceptedAnswer": { "@type": "Answer", "text": "Analytics helps in predicting revenue, improve supply chains, identify trouble spots, understand where the company is bleeding money, and fraud detection." } },{ "@type": "Question", "name": "How do predictive analytics benefit financial institutions?", "acceptedAnswer": { "@type": "Answer", "text": "Predictive analytics can help financial institutions and customers detect fraud, financial management, predicting markets, improving products, better user experience, etc." } }] }

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3 analytics misconceptions holding your business back (and how to overcome them)

Article | August 9, 2021

It’s game on for digital transformation. Success in this hyper-digital world requires meeting market demand and exceeding customer expectations. And without the use of advanced analytics and AI initiatives to deliver predictive, guided insights, organizations will fall behind. According to IDC, a whopping 83% of CEOs want their organizations to be more data-driven, and the top priority for 87% of CXOs is being an intelligent enterprise. Yet that urgency is often stymied by perceived—but often inaccurate—obstacles.

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COMBINATION OF VIRTUAL REALITY AND DATA ANALYTICS

Article | August 9, 2021

Virtual reality is an innovation with boundless opportunities. These can be seen when it is combined with another tech to make new opportunities. At the point when paired with gaming, for instance, VR has empowered the user to enter the virtual universe of the game, for example, in an online casino where the user can enter a virtual casino from the comfort of their own home. When utilized in marketing, property developers can demonstrate houses to potential buyers any place they were on the planet.

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Splunk Big Data Big Opportunity

Article | August 9, 2021

Splunk extracts insights from big data. It is growing rapidly, it has a large total addressable market, and it has tremendous momentum from its exposure to industry megatrends (i.e. the cloud, big data, the "internet of things," and security). Further, its strategy of continuous innovation is being validated as the company wins very large deals. Investors should not be distracted by a temporary slowdown in revenue growth, as the company has wisely transitioned to a subscription model. This article reviews the business, its strategy, valuation the sell-off is overdone and risks. We conclude with our thoughts on investing.

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Spotlight

OpsVeda, Inc.

OpsVeda Business Execution Platform provides CONTINUOUS, RELEVANT & PRESCRIPTIVE insight to enterprise customers. We enable real time 'actionable' visibility into exceptions across execution processes spanning order fulfillment, supply management, shipment logistics and channel operations. OpsVeda Application Suite, powered by SAP HANA, brings big data predictive analytics and deep business process expertise together, to deliver outcomes for customers out of the box. Our customers span the high-tech, consumer goods, apparel & footwear and life sciences industries, typically with revenues greater than $200M. OpsVeda provides the complete solution stack – real time data streaming (back-end ERP/ carriers/ external partners/ legacy systems), data discovery, rules management, end user visualization, collaboration, and alerting. Deployed on cloud or on-premise, and accessed through desktop or mobile. All in On Platform. Deployed in 30 days…

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