The comprehension and size of the data have evolved as a human got evolved in technology and culture. At any situation or time, when the data becomes too big and uncontrollable, then we create systems to analyze and interpret the data. Devices like Abacuses are the instruments, which can help us calculate or analyze the data in hand.
Though, the amount of data used by human society has increased beyond the imagination in the last couple of decades. The conception of such a huge volume of data is not possible without technology development. Even with these advanced technologies, it becomes impossible to practice all the data. The evolution of Big Data technologies is explained here in three different phases:
ADBMS or Data Base Management System is an origin of the Big Data as well as Data analytics. The methods like extraction, storage, and optimization utilized in the RDBMS or Relational Database Management System depended heavily on Database management during that time. The initial phase of the evolution of Big Data analytics consisted of database warehousing and database management.
The contemporary data analytics later created an evolution of database management system and different methods are used like database processing, database queries, as well as reporting tools.
The commencement of the Internet as well as WWW has started introducing new and exclusive opportunities for data analyses and collection. The commercialization of personal computers through companies like IBM, Microsoft, Apple, etc. as well as the accessibility of the internet, has made it easier for more and more people to use the internet that has amplified the web traffic using this roof.
This enormous increase in the data amount by HTTP-based web traffic was mainly unstructured and semi-structured data from the data analytics viewpoint. Because of this nature of data, different organizations are required to search new methods to interpret, store, as well as analyze new data types. The requirements are there of interpreting the huge data from e-commerce websites and social media platforms. Then they can transform them into meaningful data.
A lot of organizations in the data analytics study these unstructured or semi data as their focus. The new opportunities for retrieving important data from the mobile devices have made an entirely new world of options. This third phase of the Big Data is controlled by the biometrics data through IoT devices. Different devices like wearied activity trackers permit companies to trail health-associated data. Together with the user’s location, tracking permits them to study new and useful data. Due to these internet-based sensing devices, the generation of data is at a different level.
The sensors get implanted in all types of machines. From everyday appliances like refrigerators and washing machines to trucks, cars, to warehouses for tracking the inventories. Different possibilities of using these data are infinite. The finest part is that we have just started to analyze or extract the data from these resources.
Use Cases of Big Data
It’s time to go through some use cases of Big Data. Different organizations use various Big Data tools like Apache Spark, Hadoop, Pig, Hive, etc. to deal with Big Data as well as get insights from that.
Here are the key use cases of Big Data for different domains:
1. Financial Sector
Let’s go through Big Data applications in the Banking &Finance sectors. Financial service organizations utilize Big Data for different uses:
a. Fraud Recognition
Banks as well as financial firm’s utilize the evolution of Big Data platform to distinguish fraudulent interactions and genuine business transactions. Using Big Data analysis and Machine Learning, they can differentiate the usual activity as well as unusual behavior representing frauds based on a customer’s history.
If strange behavior is detected, the analysis system will recommend immediate actions like blocking the irregular transactions as it will stop the fraud before it happens.
b. Risk Valuation
Financial organizations manage customer’s risk using Big Data Analysis through analyzing the customer’s portfolios. This Big Data analysis helps real-time alerts so that in case, the risk onset exceeds, the system notifies the firms.
c. Consumer Segmentation
Consumer segmentation is the finest way of transforming banks from product-based to customer-based businesses. Big Data allows the group customers to bank sectors into different segments well-defined by the data sets, which include everyday transactions, demographics, etc. Then promotions and marketing campaigns are targeted to the consumers as per their segments.
2. Healthcare Sector
A lot of companies utilize the evolution of Big Data in healthcares the healthcare sector is amongst the most well-known areas in which Big Data is having profitable success to shape the normal practices.
a. Patient Forecasts
The healthcare sector uses Big Data analysis for predicting the number of visits to recognize the frequency of avoided appointments and the complete time of surgery. With Big Data analysis, you can forecast if the doctors have sufficient medical supply or not. So, the procedure superior quality of assistance to the patients that helps them recovers quickly
b. Real-Time Health Checking
Having the advancements in IoT, you can have different wearable devices including wristbands, fitness trackers, etc. to monitor the health of the users. However, with the monitoring device, you need to analyze the generated data by devices for monitoring the user’s health in the real-time mode as well as offer data to doctors. Therefore, data from different devices get analyzed immediately and, if anything goes wrong, an alert would be sent to a doctor or other specialists automatically. Consequently, the doctor could contact the patient immediately and offer them all the required instructions.
c. Forecasts of Mass Epidemics
With the evolution of analytic scalability in Big Data, a scientist creates social models about the population’s health. The doctors may create analytical models of epidemics. Through data analysis and algorithm usage, they can predict the infection outbreaks. Therefore, before the spread of disease, the doctors would have the opportunity of creating targeted vaccines quicker which will stop the disease epidemic. This is a great advantage for the world population.
3. Transportation Industry
Big Data has proved to be gainful for the transportation industry also. Big Data can be used in the transportation business to make transportation easier and more efficient.
a. Route Planning
Transportation companies are using Big Data for understanding and estimating the users’ requirements on various routes as well as on various transportation modes. They create route planning for reducing the waiting time.
b. Crowding Management with Traffic Control
Big Data assists in combining the real-time traffic data composed of video cameras, road sensors, as well as GPS devices. Therefore, traffic difficulties in compressed areas could be resolved by adjusting the public transport routes in real-time. For instance, people use Google Maps for locating the least condensed routes.
c. Traffic Security Level
The real-time handling of the Big Data as well as predictive analysis could be utilized to recognize accident-prone areas that can assist in decreasing accidents as well as increase the traffic safety level.
4. Government Sector
Big Data has a very important role to play in the government sector. Big Data technologies are playing a key role in fields like national security, public services, defense, cyber security, national security, crime prediction, etc.
In the public services, the evolution of Big Data analytics has an extensive range of apps like health-related search, financial market analysis, environmental protection, fraud detection, and more.
The Social Security Administration utilizes Big Data for analyzing a huge amount of social incapacity claims, which arrive in the unstructured formats. This analytics assists SSA to quickly procedure medical data as well as helps in quicker decision making or noticing fraudulent claims.
The FDA or Food and Drug Administration utilize Big Data to detect and study the patterns of food-related illnesses and diseases. It offers quicker responses that result in quick treatment as well as reduces death.
Big Data analytics plays a key role in making the future of retail industries. All the retailers, offline or online, are implementing the data analysis tactics to understand the purchasing behavior of the customers as well as mapping them for various products and plan marketing tactics to sell their products as well as increase the profits. They use Big Data Analysis to:
a. Generate Recommendations
Retail industries depending on the customer’s buying history forecast what they would likely buy next. They utilize machine learning models, which are skilled in the historical data to make forecasts.
b. Strategic Decisions
Retailers gather data from different resources and examine them to take profitable decisions.
c. Market Basket Analysis
They utilize Market Basket Analysis methods to discover what products are likely a consumer would buy together. With Apache Hadoop, the retailers analyze a huge amount of data.
Big Data analytics has a very important role to play in the airline industry. The airline industry uses Big Data Analysis to:
a. Monitor the Flight Rate of Popular Destinations during the Festive Seasons
During the festive season, people visit the popular destinations more so the airline companies need to monitor the flight rate of popular destinations during the festive seasons so that they can analyze the competitor’s strategies and decide their flight ticket rates accordingly.
b. No. of Flights are Being Operated Between Source to Destination
It’s very important to know how many numbers of flights are being operated by your competitors between the source to destination as you need to make your strategy accordingly about how many flights you will operate from the source to destination and you can analyze it with the help of Big Data Analytics.
c. Price Comparison among Different Airlines
Airline ticket pricing can be a very important factor for how you stand against your competitors in the market. To stay in the competition, you should monitor your competitor’s prices and decide your pricing accordingly and Big Data Analytics can help you in that.
7. Car Rental
Big Data analytics plays an important part in the car rental industry. The car rental industry uses Big Data Analysis to:
a. Monitor the Car Rental of Popular Locations during the Festive Seasons
During the festive seasons, car rental services get very busy as people hire cars on rental to visit different locations. In different locations, there are some popular locations where people visit more. Monitoring the car rental of popular locations during the festive seasons can help you decide your car rental price and lead the market.
b. How Rentals are changed During the Peak Hours and Normal Hours
In car rental, normal hours and peak hours have different rates per hour. In peak hours, the charges are higher compared to normal hours. With Big Data Analytics, you can analyze the different rates of competitors during the peak hours and normal hours and change your rates accordingly.
c. Availability of the No. Of Vehicles at Different Locations
Using Big Data Analytics, you can check the availability of the number of vehicles at different locations and make a strategy accordingly to decide whether to provide more vehicles at particular locations.
8. Hotel / Accommodation
Big Data analytics plays a significant role in the hotel or accommodation industry. The hotel or accommodation industry uses Big Data Analysis in different ways:
a. Hotel Price Monitoring Services
Big Data Analytics helps in price monitoring of the hotel prices. It helps you monitor the price of the competitor hotels and help you decide your service prices.
b. Availability of Hotels/Vacation Rentals in the given destination
It’s easy to check the availability of hotels or vacation rentals in the given destination with Big Data Analytics. You can check whether the hotel rooms are available or any hotels available in the given destination.
c. Review Different Amenities Offered by Hotels
All the hotels have different amenities and many people choose a hotel by the amenities available there. Using Big Data Analytics, you can review different amenities provided by hotels and use that to help your business do better.
9. Food Delivery
Big Data analytics has an important role to play in the food delivery market also. The food delivery industry can use Big Data Analysis in various ways:
a. Aggregate the Food Menu Data at Modifier Level
You can scrape the food menu data at modifier level with the help of Big Data Analytics. You can scrape the food menu data of your competitors and set your price accordingly.
b. Review the Offers, Delivery Fees & Service Charges Offered by Different Food Delivery Platforms
There are many different food delivery platforms available and with the help of Big Data Analytics, you can review the offers, delivery fees, and service charges offered by different food delivery platforms and make your marketing plan accordingly.
c. Availability of Food at the Popular Restaurants
Using Big Data Analytics, you can check the availability of food at the popular restaurants as well as availability of restaurants in a particular area.
10. Social Media
Big Data analytics plays a vital role in the social media and online industry also. The social media industry uses Big Data Analysis in diverse ways:
a. Monitor the Social Media Trends Toward Specific Topic
Social media has quickly changing trends so it’s very important to keep an eye on the ever-changing social media trends on specific topics. Big Data Analytics can help in monitoring social media trends and give you the right picture of what’s going on in the market.
b. Analyze the Post For Popular Hashtags I.E. Positive, Negative, Neutral
Websites like Twitter and Instagram use Hashtags to tag people, subjects, etc. It’s very important to analyze these Hashtags to get a clear picture of the latest market trends. With Big Data Analytics, you can easily analyze these Hashtags and see if they are positive, negative, or neutral.
c. Review The Social Media Post, Comments, Tweets, Retweets, Likes, Followers of Famous Personalities
It’s has been a trend to follow the social media posts, comments, tweets, retweets, likes, and followers of the famous personalities. With Big Data Analysis, you can easily review all these things and scrape these data for your business use.
Data is the most powerful and important commodity in the contemporary world. At X-Byte Enterprise Crawling, we play our role in the evolution of Big Data technology by servicing the companies, which need web-based data. We offer enterprise-grade, well-managed, and end-to-end data scraping solutions. We ensure to use this 3-part series of the evolution of Big Data and its features and its developments in the last final part that will soon get published.