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In today’s world, a large amount of information needs to be processed. This large volume of data must be structured and processed by computers. This volume of information is called big data. In this article, we examine what big data is and explain big data in a very simple way.
Big data means a huge amount of structured and unstructured data that has the potential to help organizations improve their operations and make faster and smarter decisions. The number of these data is so much that it was difficult to process them using traditional databases and existing software.
In most organizations, the amount of data is too large or moving too fast and has exceeded the organization’s current processing capacity. Besides these problems, Big Data has the potential to help companies improve their operations and make faster and smarter decisions.
Currently, all big businesses are involved with this concept. Now that we are familiar with the concept of big data, in the rest of the article, we will examine the details and characteristics of big data.
Since big data takes a lot of time and money to load into traditional databases for analysis. Big data analysis has given rise to new methods for data analysis and storage that pay less attention to the pattern and volume of data. Instead, raw data is collected locally and analyzed by machine learning and artificial intelligence to find recurring patterns using highly complex algorithms.
Then these iterative algorithms are used and analyze the data. With this method, there is no need to process all the data independently one by one. It is enough to extract the output results of the used algorithms, and use them for analysis and processing.
Big data is characterized by three main characteristics:
These features are not only related to big data. It also refers to the technology of storing and processing this information. This technology includes tools and processes that need to call very large unstructured data.
Volume: The volume of data is important in big data analysis because big data will include all types of wrong, unprocessed, correct, processed, etc.
Speed: The speed of receiving information is very high due to the simultaneous use of the Internet and data storage.
Variety: The variety of Big Data data is very high because they include a large range of data types such as sound, image, text, video, etc.
Considering the importance of concepts related to big data, it is better to get familiar with its types. Generally, big data is divided into the following types:
It refers to data that has a proper structure and is suitable for use in large projects. For example, data in databases, Excel files, and spreadsheets all fall under the category of structured data.
These are data that do not match the formal structure of data models associated with relational databases or other forms of data tables. However, the semi-structured data contains tags to separate semantic elements and hierarchical implementation of records and data fields.
For example, data in e-mails, report files, and Word documents are classified as semi-structured data.
These are data that are widely available in the virtual space and lack any coherence and structure that we see in relation to databases. More precisely, while unstructured data has an internal structure, it does not follow consistent management patterns or data models.
In general, this data is unstructured. Among the obvious examples of these data, we should mention image, audio, and video files, all of which lack a conventional coherent structure.
Big data information is used for all kinds of business activities, marketing, market analysis, etc. Companies use big data collected on their systems to improve operations, provide after-sales services, and advertise campaigns to increase profitability. Some of the applications of big data are as follows:
Today, co-marketing decisions require big data. Complex data and large numbers cannot be processed with traditional programs and require appropriate technology. Among the effects of big data in digital marketing, the following can be mentioned:
Now that we are familiar with Big Data, it is good to know which sources provide this information.
By entering the age of information and communication, there was a concern that the same type of data is produced every day at a terrible speed in the world. Now how this large and diverse amount of data and information can be managed, controlled, and processed according to the structure that exists in IT.
From 2012 onwards, more than a thousand petabytes of data are generated every day, which requires storage, analysis, searches, data cleaning, subscriptions, etc. It should be done in different areas.
This issue has caused researchers and scientists to seek to create new structures, methodologies, methods, and approaches to manage, control, and process this volume of data. And these efforts have been raised under the shadow of “big data”.
5 main methods are considered for big data analysis:
Choosing the most useful big data analysis tool is very important. In the following, we will name the most well-known big data analysis tools:
All Companies need to manage their vast amount of data in a smart, cheap, and progressive way. One solution is to use tools like Hadoop, an open-source software framework used for large-scale data processing.
In fact, Hadoop is a framework or a set of software and libraries that provides a mechanism for processing a large amount of distributed data. This collection has been launched in 2006.
Hadoop is just like an operating system designed to process and manage large amounts of data on multiple machines. Hadoop managed to break the record for the fastest processing system in 2008 by processing 1 terabyte of data in 202 seconds. And even later announced that it had reduced this time to 68 seconds.
Volume of data: With big data, you are faced with a large volume of unstructured and low-density data. This data can include data with unknown values such as Twitter data, clicks on a web page or data from a sensor. For some organizations, this means tens of terabytes of data.
Velocity: Speed refers to the rate of receiving and in some cases performing actions on data. For example, some Internet-based smart tools need to receive information in real-time and, of course, perform processes in real-time.
Variety: This aspect refers to the types of data used in big data. Traditional data was often structured and stored in a relational database. But with the advent of big data, the data became unstructured. Data such as sound, text, and images that we need additional processing to extract specific meanings from them. In addition, the value and validity of data have also been considered in the past years.
Veracity: With the rapid growth of data in terms of volume and variety, the possibility of false data in them also increases, as a result, if the input is not reliable, the information extracted from it cannot be trusted.
Big data analysis has created a great revolution in the field of information technology. So that the performance of different companies is improved through data analysis. The main factor in this field, as mentioned, is the three key features of big data, i.e. volume, speed, and high diversity.
And then various analytical techniques such as machine learning, data mining, natural language processing, and statistics. Through the use of big data, various operations can be performed on a single platform. For example, it is possible to store terabytes of data, preprocess and visualize it with the help of several big data tools.
To analyze data for business, actions such as data extraction, data preparation, and their combination must be performed. In general, we must say that big data analysis allows organizations to work with their data more efficiently and use this data to identify new opportunities.
Today, there are different techniques and algorithms for predicting data that can be used for the future success of the company, so that they help to line up business strategies and more profitability.
We hope that by reading this article you have become familiar with the concept of big data. If you still have any questions write us in the comment section. we will answer you very soon. Do share with your friends if you like this. Thanks.
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