The internet is flooded with a huge amount of data at high speeds. This is fundamentally Big Data. Volume, range, and speed are the three axes around which this process revolves.
Data everywhere, and counting
To accomplish our daily activities like shopping online, paying at the superstore, or generating a transfer through the banks' Web portal, we all key in data. Additional data can also be extracted from satellites, light and gas meters, and cellular phones. Data can translate into almost all aspects of our daily lives.
Technology agencies have had to develop more advanced data processing unit and computing devices that can store larger amounts of data. Let's take the IBM 3380, the first 1-GB hard drive manufactured in 1980 to illustrate the incredible advancements in this discipline. It took up the same space as the fridge, weighed 250 kilos, and was worth 40,000 USD. At a very affordable price, anyone can purchase an SD card that is the same size as a paper clip.
Facebook accurately reflects the vast array of data that this system can store from its many clients. This includes their sexuality, marital status, age, preferences, and so on. All of this information is extremely valuable, especially for marketing departments with major brands.
Accelerating the Big Data analysis
However, speed is what may make the quantum leap in data management and usage. These applications allow you to run Big Data analysis processes immediately, instead of waiting for them to finish in batches. This opens up a whole new world of possibilities for all companies, regardless of their size. For example, car insurance providers can process claims within hours. This is a significant improvement on the old process that took many weeks. Health insurance companies can also interpret complex data sets about individual health to predict the potential health problems that they may face in just a few minutes. The insurance market has benefited greatly from Big Data processing and analysis when it comes to finding fraud. They can now locate false claims and prescribe ghost treatments.
This phenomenon is also being used by the banking sector. Big financial institutions have begun to use predictive modeling techniques to allow them instant access to Big Data via social media. They can see the entire person on the other end of the line, including their bank profile, personal record, reaction to marketing offers, views over customer service rendered by the business, account status and deals. These were just a few years ago.
Big Data processing is a key component of modern business models and services. Technology giants like Google, Microsoft, Oracle, SAP, and Microsoft have been busy innovating new business models. Document management software market is also not far behind and has been able to integrate Big Data with corporate paper-based records. They have created a text recognition software package that allows you to extract data from physical documents and process it before transferring it into Big Data systems. Big Data refers to information not only on the Web but also all documents and digital files that are kept in a business's file cabinet and contain imperative information.
Big Data processing and analysis: An undervalued potential
So far so good. The next question is where will the obstacles upturn? It is a fact that only a handful of businesses can make the most of all these details. Gartner states that 85% of Fortune 500 agencies aren't prepared to make big data a profit. The potential is huge.
It is important to recognize the skepticism of some businesspeople. They often ask themselves this question: What's the benefit on my financial commitment? There is no way anyone wants to think about five years before Big Data processing and analysis will be realized. Some people are not willing to consider the potential security risks that could occur when dealing with such sensitive and large amounts of data. This is why governing bodies all over the globe have developed data safety rules to reduce the impact and prevent the misuse or dishonesty of information. It is important to remember that users may be harmed by the gathering, saving, and decoding of sensitive information. The people who manage this data do not have to ask permission to use it for their own purposes. The most dangerous hackers are adept at stealing vulnerable data and accessing bank accounts.
Agencies manage a lot of valuable data but few know how to make the most of it. If Big Data processing is done correctly, it can be used to predict weather changes, enhance crops, identify product performance, and speculate capital market activity. This can be extremely useful when creating a custom offering or making faster and more informed decisions. Now we need to wait for a few years to see if agencies can address this issue.
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