Big Data refers to data that is voluminous in size and is continually growing with time. It is essentially huge chunks of complex information that standard data management tools can’t store or process.
Are you still confused? Let’s break down Big Data to its basics to understand what it’s all about.
What is data?
Data is the characters, quantities, or symbols used by computers for numerous operations. They are recorded on optical, mechanical, or magnetic recording media and stored and transmitted as electrical signals.
Big data, as we’ve established, is voluminous in size. That is perhaps its one defining feature. Hence, the tag ‘Big.’ However, there are also several other characteristics or attributes of Big Data besides its sheer volume. They are:
Diversity of Data
Big Data is composed of diverse types of data from different sources and in various formats. It’s no longer just databases and spreadsheets but pictures, videos, emails, audio files, PDFs, and so on. And this is what makes Big Data quite challenging to sort out and mine.
Variability of Data
The other defining feature of Big Data is its variability. Owing to the volume and diversity of data, Big Data can have certain data inconsistencies which can be very hard to handle. It can often lead to the damaging of data during extraction or sorting.
Velocity of Data
The velocity of data means the speed or pace at which the data is generated and processed. In Big Data, the rate of flow of data is almost unceasing, owing to its massive size. There is a constant movement of data from source to storage.
Varied Structures of Data
You can find Big Data in three basic structures. That is, structured, unstructured, and semi-structured.
- Structured Big Data- Structured Big Data is where the data type is predominantly one that can be accessed, stored, and processed with a fixed format. This kind of Big Data is comparatively easier to handle than the unstructured and semi-structured. An example would be an employee table database.
- Unstructured Big Data- Unstructured Big Data has no single fixed format through which it can be accessed, stored, or processed. It is heterogeneous with a mix of different types of formats like images, audio files, videos, PDFs, etc. A good example is a Google search output.
Unstructured Big Data has the potential to be of great value. A lot of leading organizations and companies have access to unstructured Big Data but do not possess the adequate tools to benefit from them.
- Semi-Structured Big Data: Semi-Structured Big data, on the other hand, is a mixture of the two. You will find large chunks of structured data as well as unstructured data. This form is also challenging to access, store, and process. An excellent example of this type of Big Data would be an XML file.
The Potential of Big Data Processing
As challenging as it is to work with Big Data, processing it can reap numerous benefits for those who can access it.
Processing Big Data allows all stakeholders involved to access data that might help them improve products and services with ease. And instead of the traditional way of attaining data through customer feedback or surveys, stakeholders can analyze Big Data and streamline their performance effectively.
Processing Big Data can potentially improve customer service, sharpen marketing skills, contribute crucial data to the resource pool, etc.
Companies, organizations, and businesses can make better decisions on high-stake issues knowing that factual data can back their decisions. Big Data processing, in a nutshell, is potentially the next big step in more proficient socio-economic processes.