What is Big Data? In the most simple terms, it is the new buzzword in the business and scientific research communities. Large data has many implications, particularly in the areas of managing multiple data sources, analyzing the data, storing it, and making sense of it. Big Data has even more promise as it is now becoming an important tool in many of today’s applications.
Why is “big data” so important? It is imperative that business leaders consider the potential applications of big data techniques for improving their businesses. The three main areas in which unstructured data is impacting business activities include: analytics, optimization, and service. What is unstructured data? Structured or semi-structured data are collections of information that have been processed into a meaningful form that can be used in decision-making and/or in operational environments.
What is Big Data’s impact on big data analysis? Data analysis is the process of discovering patterns and relationships from large sets of unprocessed or structured data. With this information, managers and/or executives can gain a deeper understanding of their competition, their customers, their internal processes, etc. By properly analyzing the huge amounts of data being accumulated, managers and executives are better prepared to make wise business decisions, both in reacting to external factors and in developing internally useful products and services.
How does structured data help companies? As opposed to the popular belief that big data analytics refers to data analysis conducted on unstructured data, it actually refers to the integration of both types of data to allow managers and/or executives to make better informed decisions. Unstructured data may consist of sales figures for a specific period of time, inventory levels for a specific day, and various other unprocessed pieces of information. On the other hand, semi-structured data may consist of highly organized set of structured facts, such as customer relationship management (CRM) data, inventory data, and the like.
Why is there a need to distinguish between the two types of big data? Well, the primary reason why this term is often used is because it provides managers and executives with better insights and/or options when making strategic decisions. In fact, only semi-structured data cannot provide managers and executives with the necessary information when making crucial decisions. As previously mentioned, big data analytics results in better insights, and more options. However, this doesn’t necessarily mean that the unstructured or structured types of data are bad or should be ignored.
The next question to answer is what separates the two types of big data analytics? In essence, the unstructured data refers to anything that is not highly structured, while the highly structured data is the structured kind. For instance, sales reports are very structured, while order histories are not. This means that although both statements may hold varying information on which party to take action against, the information contained in the sales report would be considered highly structured compared to the order history, for example.
Lastly, we will discuss the third type, the velocity measurement. Velocity pertains to the ability of a certain entity to alter its speed, or the ability to alter its speed. Now, the unstructured or the semi-structured data may contain a lot of information and may seem to be dynamic, but the truth is that it can only change at a certain rate. And this rate can vary significantly according to different entities.
In the end, the three types of big data analytics are more or less similar. Each has their own strengths and weaknesses. So, in order to make best use of this, managers and executives must identify their needs and identify what they want their data sets to do. After that, they must choose which among the three they feel will give them what they need. Of course, there are many more interesting things to learn, and each of these will most likely become the hot button topic of the next few years. Indeed, I hope you will please consider all this and think on it.