Over the past few years, as the use of big data has increased and become popular, two other features have emerged in addition to the three features mentioned above: Value and Accuracy.
Each data has its own value. However, this value does not provide any benefit until this value is discovered or analyzed. Let us consider this value as a mine within a gold reserve. What value remains unless you uncover and process the gold mine?
It is important to recognize that data accuracy as well as data value is equally important. How much of the information you get throughout the day can be said to be accurate and how much can you fully trust?
Nowadays, big data has become a global capital. Think of some of the world’s largest technology companies. Much of the value they produce and present is made up of continuous analysis ethics data to provide greater efficiency and develop new products.
The latest technological advances have significantly reduced the cost of data storage and analysis. This has made data storage easier and cheaper than in the past. It is now possible to make very accurate and precise business decisions thanks to the large size and accessible large data.
Searching for information within Big Data does not only mean analyzing. (Accessing data through analysis is another advantage of big data) Big data research includes knowledgeable analysts, business representatives; It is a process of discovery where experienced, conscious and predictable managers can ask the right questions.
Challenges of Big Data Usage
The opportunities mentioned above are for business and scientists, engineers, doctors, etc. It is worth mentioning that it has some difficulties when talking about the big data that offers. First, the big data is pretty big as above the name. Although new technologies for data storage have been developed, data volumes have doubled in about two years and there are difficulties with data storage. Organizations are still struggling to find effective solutions to keep up with the data they have acquired and to store them effectively.
But the job doesn’t end with just storing the data. The data must be valuable in order to be used, and the value of the data depends on the condition of improvement. Therefore, the data must be extracted from unnecessary information. It is also worth mentioning that it is useful to organize the data in such a way as to address customers and researchers and provide meaningful analysis. Of course, these stages require a lot of work. Data scientists spend 50 to 80 percent of their time developing and preparing data before they are actually used.
Finally, big data technology is changing rapidly. A few years ago, Apache Hadoop was a popular technology used to process big data. Then Apache Spark was introduced in 2014. Today, ORACLE which is a combination of two systems seems to be the best approach. In short, keeping up with big data technology is a constant challenge.