Top 10 Industries Big Data Will Disrupt

  • 6 September 2017
  • Dylan Dedi

Big data is changing the way we see the world. What was originally a byproduct of the internet came to give us statistics that can track patterns of humans and interactions on a global scale. It is a raw, unprocessed gold mine for researchers and companies who want to use its information to benefit them in some way. The Internet of Things birthed itself in the ideas that were brought to humanity from big data: collecting raw information from the physical world will find patterns that can help us understand the world. Each day (as of now) the internet produces 2.5 quintillion bytes of data. To give perspective, this would fill 10 million Blu ray discs with information. Every day, as we develop technologies to process this data, we find that big data will be changing the way industry functions. Here are ten industries that big data is on its way to disrupting:

1. Banking

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As volumes of customers for banks increase to the millions, it gets harder for these giant companies to stay personal to each client. Big Data has helped banks gather the resources they need to keep their relationship on a personal level. Big Data can show the point where customers tend to feel the most frustrated, whether on the phone or looking for an answer to a question. There is also a huge set of data that banks contain, that can be a rather pricey chunk of information for buyers: payment data. Nothing says better about what people buy than their bank accounts. Banks use this data to understand better their users, as well as advertising companies who wish to target their audience better.

2. Construction


The construction industry takes on some of the largest tasks in the physical world. Skyscrapers cost billions in materials and labor. Estimating for this requires an entire team of itself. Construction firms are using big data to help slim down costs and boost efficiency. With big data and 3D modeling, technology groups in construction companies are learning how to learn from past sketches and material counts to find slimmer averages in cost. With a combination of Big Data/ IoT, they can also look at what kinds of materials and build are more efficient and last longer.

3. Retail


The retail industry is using big data to predict what you are going to want to wear next season. “Trending” has become a relatively new result of big data that shows what is getting popular at an exponentially fast rate. Retailers have many tools at their disposal to analyze these trends and predict what a customer will want at any given moment. Ozon.ru, a Russian online retailer, puts out more recommendations for books on their website when the temperature drops. They've noticed a trending search for books whenever it is exceptionally cold out.

4. Real Estate


Big data is not only for large enterprises to see. Zillow gathers big data so members can access all kinds of information about any property around the world. It is a great way of understanding how humans and AI collect massive amounts of data from all sorts of places (maps, online records, etc.) and translate it into natural language that any computer literate understands. This also helps with gathering information about upcoming foreclosures, which has always been tricky to find. Big Data is disrupting the role of real estate professionals, as many people are now taking into their own hands to buy homes. On the contrary, real estate professionals still believe even if their client finds the home, they can help their client get the best deal possible.

5. Legal


The legal industry hasn't been affected as much by Big Data as other industries have, Daniel Lewis of Ravel Law believes. Which is why he and his partner created the technology-based law firm that will bring the legal industry into the digital age. Ravel Law imagines the digitization of all legal documents, to create less clutter in a law firm and allow for an easy search of cases that could help the tech-lawyer win the case. One day, there's the possibility that lawyers and judges will become augment AI, using Big Data to draw up all past cases in an unbiased way to find the most justice.

6. Agriculture

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Sensors placed on drones and the fields of large farms are amassing large amounts of data for farmers to understand better what will make their crops grow more efficiently. RFID chips are placed on shipments of food to improve supply chain efficiency. We are now able to gather data from the farm to the supermarket. This is creating a giant industry in farming analytics, that is becoming a necessity to ever large farmer out there. The Farmers Business Network is leading this data industry by connecting farms with smarter buys and “agronomic intelligence.”

7. Insurance


Insurances companies play a bit of a game, and Big Data is helping insurance companies understand human behavior. Data aggregators can find all kinds of information on people to predict if that person is more likely to be involved in an accident.  Social media and IoT wearables like Fitbit give the companies a better understanding of where the person is; in return, many insurance companies offer discounts to those who wear and have IoT smart devices in their homes, cars, and on the road.

8. Airlines


Flight attendants can now use apps that aggregate Big Data from their passengers, to look at previous flight experiences and where they prefer to sit, allergies, food preference and more. Delta is also offering an app to the passengers that can help track their baggage in real time.

9. Energy


AutoGrid is an analytics company that draws data related to energy. The grid is huge, powering almost everything in the world. We can use Big Data to understand patterns in home energy usage, find automated predictions, and optimize performance. It also helps create backup scenarios for power outages.

10. Telecommunications

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Call centers can compile thousands of documented case studies from their archives into Big Data records.Their customer service representative can quickly pull these records. This saves time that each representative is on the phone with a customer, and in turn saves the company money. Data can also predict when the heaviest periods of network usage is going to be used and can target the audience using big data to understand if the customer will be more of a problem (somebody who doesn't pay on time), and steps to remedy the situation.

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