About Motifworks

At Motifworks, we are AZURESMART. We are one of the fastest-growing cloud solutions providers, specializing in Cloud Adoption, Application Innovation, and Effective Data Strategies. Our passion is to empower you to accelerate your digital transformation initiatives using the Microsoft Azure cloud. We’re here to simplify your path to explore what’s possible.

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Applications of Big Data Analytics in various industries

How Big Data Analytics can be Applied in Various Industries

While about 41% of companies globally utilize big data analytics for making more informed business decisions, a significant 53% of these enterprises are situated in North America alone, as per research conducted by BARC.
Are you, like many others, intrigued by the potential applications and benefits? Do you find yourself wondering how this technology can drive growth for your business?

Use of Big Data Analytics can help you gain:

  • Better Data Visualization
  • New Business Opportunity
  • Marketing Optimization
  • Deal Personalization
  • Operational Intelligence
  • Security & Risk Management

Application of Big Data Analytics in Industry


Conventional analytics tools enable companies to track conversions, demographic statistics, average time spent by users on each page, pages that have highest bounce rates, etc. Companies have also been using heat maps to make changes in page design as well as arrange call-to-actions.  The user data captured can be used to recommend which travel solutions would be relevant for a particular passenger, or which hotel would be the most appropriate for a young couple who booked their flight for summer holidays. Sentiment analysis of reviews and recommendations on blogs and social networks can help gauge the polarity of those posts and contribute to understanding customer requirements. Big Data can also be used for real-time analysis of competitor’s prices to devise an effective pricing strategy.


The financial services industry has seen unprecedented changes in the last few years.  It is more critical than ever to ensure the integrity of data provided to regulators and executive management. Improved data quality and analytics offer a chance to gain competitive benefit by changing the way decisions are made. With big data and business analytics, complex algorithms use a broad range of data collected from a variety of sources to support trading decisions. Live and historical data can be used to notify new opportunities as well as predict if a customer is likely to default.  Thus, big data can play a significant role in the recovery of bad debt as well. Understanding customer circumstances better can improve recovery targeting and affect recovery rates while reducing cost.


Having data-driven insights can help energy companies make provisions more efficient. By analyzing historical data, power plants can forecast energy demands for any season or time of day. If data regarding electricity usage, outages, transformers, and generators are available, automated predictions, optimization of grid devices’ performance and visualizing energy usage trends can be done easily. Also, a software that uses big data analytics can predict when trees growing around a power grid may fall on power lines, thereby needing maintenance. Such predictions would mean power companies can save money by avoiding outages.


With the vast amount of customer data available to telecom companies, it has become easier to understand customer needs and behavior and offer services for which users are looking to obtain. With personalized deals, chances of conversions are higher.  It can help segment the market more accurately, providing insight into services that customers might be looking for as well as providing a better understanding of frequency utilization, switching and capacity use.


In the agriculture sector, being able to forecast pesticide quantities, crop prices and the health of livestock can largely improve profitability. The sooner farmers get access to this information, the better it will be for them to develop a clearer picture of their expected costs and profits. To reduce waste, farmers can use predictive analytics to have an idea of exactly how much stock they will need to feed their livestock.

At Motifworks, we know how Big Data Analytics can be used to overcome the challenges of competition, reach, and service quality.  Feel free to reach out to us in case you have queries.