The world population in 2018 was 7.6 Billion. This directly indicates the fact that planet Earth produces large data volumes in multiple and irregular forms. All of the above simply refers to all a rudimentary description of Big Data in these simplistic terms. (source)
With the developments that the world has witnessed after the internet revolution and what the internet technologies have brought about in changing the shape of the world, the world has woken up to an important fact that we produce a very large amount of non-consuming data that needs expensive and large storage methods.
According to IBM, as of 2012, it creates 2.5 quintillion bytes (2.5×1810) of data per day.
Thus, the necessity of analyzing this data and making use of it to the maximum extent in managing facilities, improving business and improving the quality of life.
The International Monetary Fund (IMF) has coined the phrase “data in the new oil“. So, what does it mean by data and can it revolutionize the way oil did?
What is Big Data?
You can learn the term of Big Data, as is evident from data and information such as resulting from data that appears in the spread of modern electronic almost.
Definition of the Gartner Foundation, which is specialized in the market research and study:
Big Data is data that contains a very large number of diverse data and that reaches increasing size and speed.
This is known as “3V”. Simply put, Big Data is larger and more complex than regular data sets. These datasets are huge to the point of processing programs conventional data is unable to manage it. However, these huge amounts of data can be analyzed and used to address the problems facing enterprises in all fields.
Features of Big Data:
Big Data are graphic resources that can be described as “data of such great quantity, speed and diversity that require innovative and cost-effective forms and understand it more deeply and use it better in the decision-making-process”.
In 2001, data analyst Doug Laney gave Big Data a new definition, describing it as that data is characterized by three characteristics: Size, Speed, and Variety.
- Volume: The name Big Data itself indicates that it contains a large amount of data. The size of data is very important in determining whether the data is “Big Data” or not.
- Velocity: velocity is the speed at which data is generated. Velocity in Big Data is a measure of the efficiency of the data. The faster data is created and processed, the truer potential the data will be.
- Variety: Data come in a variety of forms, structured, unstructured, digital, etc.
Benefits of Big Data and Data Analytics:
- reducing costs.
- save the time and save effort.
- Make the best decision.
- Determine the causes of failure and avoid losses.
- Developing and improving facilities predetermined by big data.
How is big data collected in facilities? “big data big data sources”.
There is an enormous number of data produced every day, and with the increasing number of technology users, the number presented can be double in a short time. For example, Facebook deals with more than 50 billion images from its users! (The source of the information). But the sources of Big Data are not limited to one source. Such as:
such as the citizen data. Base the governments provide open to all. Such as: records of phone numbers, mail addresses, hospital records, and others…
Such as bank-service, Bank service records.
such as: satellite imaging, road sensors, and climate sensors.
Such as: Smartphones, and global navigation system (GNS) data.
for example: times Internet searches for a product or service or any type of information, and time views of a page on the Internet. For example, Google handles about 100 million reaches a month.
for example: comments social media.
The concept of big data analysis:
What we mean by big data analysis is to create tools with specific techniques and algorithms that scan large amount of data to reveal different patterns, Interrelationships, and other insights.
Benefits of big data processing:
Companies that want to survive and be competitive need the best analysis software.
Data analysis is the way for companies to understand the strategy they should follow, while predictive analysis is what helps companies look into the future and see all possible market patterns.
Only the application of the data to analytic and predictive algorithms can show how consumer behavior is it changing and what will be wanted in the future to create unique offers that attract customer.
Big data analysis helps organizations:
- Get advanced business intelligence: Before the advent of Big Data, business intelligence was somewhat limited. Integrating advanced big data analytics with information systems is an important step towards achieving a full return on investment. Now many companies are preparing to hire data analytics experts as they help take the company to the next level.
- Targeted marketing: analyzing big data can help predict products that customers may need in the future. Imagine how your company might benefit from being able to market products that you know your customers need a know enough information about them to customize them for specific needs.
- Productive customer service: With the big data analysis, companies know exactly what your customer needs before the customer raises the query. This type of a productive customer service will revolutionize the business world that wants to differentiate itself based on its customer service such as creating a “Chat to” that anticipates customer inquiries.
- Products that align with customer “desire”: Big Data promises not only to improve customer service, but also to allow companies to create products that respond to customers’ needs. Product design can help meet customer needs in ways that were not possible before. Instead of customers telling you what there’re looking for in a product, you can use data analysis to predict what they’re looking for in the product.
- Improve business efficiency: Big Data analysis provides organizations with rich information about every product or service. This analysis helps her to conquer the market. Engineers are analyzing Big Data and looking for ways to make the processes run more efficiently. when defects are detected and removed, it improves work performance.
Who use big data analytics?
With the volume of new developments and technologies that have appeared in the world of technology, data has become invading the world, and the statistics indicates that by 2020, every person on Earth will produce 1.7 megabytes of data every second! And it is possible to exploit All these amounts all data in several areas, or if you will, in all fields.
practical examples of using big data for the benefit of enterprises:
- Big Data and the Banking sector: With the revolution in the field of Big Data and the benefits of its analysis, it was necessary for banks to exploit their big data and benefits from it in: risk management, security and fraud opportunities, and bank would able to analyze in deeper and broader needs of each client separately, which would improve the quality and experience of the customer.
- Big Data and Governments: Governments, regardless of which country, have an enormous amount of data on an all most daily basis. The reason is, they have devices and databases related to citizens. Big Data have a tremendous impact on government. Governments try to make all the Is that information they receive meaningful and help them make vital decisions that affects millions of people. Case in point: big data analysis played a large role in US President Barack Obama’s 2012 reelection campaign.
- Big Data and Healthcare: the contribution of big data to healthcare has grown exponentially. With medical advances there was a need to store a large amount of patient data. Big Data Is widely used to store patient’s health histories.
This data can be used to analyze patient’s health status, prevent any future relapses, and detect malignant diseases early.
- Weather conditions: Big Data technologies are used to forecast weather forecasts. a large amount of data about the climate is stored and through its analysis it is predicted the weather situation, and this can be useful for forecasting natural disasters like floods, etc.
- Social media analysis: The best use case for Big Data is the data that continues to flow to social media networks like Facebook and Twitter, etc. Data is collected and monitored in the form of comments, photos, social situations, etc.
Companies are using Big Data technologies to understand customer requirements and check what they say on social media.
This helps companies analyze and devise strategies that are beneficial for the companies’ growth.
- Fraud detection: fraud detection and prevention are one of the many uses of Big Data today. Credit card companies face a lot for fraud and use Big Data analytics techniques to detect and prevent them.
- Improving the Internet of Things: IoT Networks are not new; this concept is based on connecting devices Over the Internet that communicate With Other Thus Creating A fully functional digital network. An example of The Internet of things product in the smart home system.
Business uses of Big Data
- Cost saving: Big Data tools can bring benefits to businesses when large amounts of data are stored these tools also help identify more efficient ways of business.
- Time reductions: The speed of analyzing Big Data Can help make critical, accurate, and fast decisions.
- Understanding the market conditions: By analyzing the buying behaviors of customers, the company can know which products are selling the most and produce products according to those accurate reports.
- Online reputation control: Big Data tools can analyze People’s opinions of your business. So, by analyzing Big Data, you can find out what people think if you want to monitor and improve your business’ online presence.
- Use big data analytics to enhance customer acquisition and retention
- Use big data analytics to solve the advertising Problem and Provide appropriate marketing insights.
- Analyzing people’s opinions on your product and their reactions and opinions.
This contributes to finding out the defects of the product and developing weaknesses in your organization.
Conclusion
Statistics show that 97.2% of companies are starting to invest in Big Data technology. Analyzing Big Data is no longer a secondary option, but rather a necessary in order to be able to remain within the competition in the market, improve the quality of facilitate and predict future events according to accurate analyzes.
Now That is no longer something limited to large western companies. Many Arabs institutions give a large amount of their attention to field of big data analysis.
The latest statistics of the SAP center indicate that 80% of digital institution in Saudi Arabia invest of Big Data.
The future of Big Data analytics technology exceeds expectations, and it is worth nothing that the size of Big Data market is expected to reach $103 billion by 2013.