Big data is still data, but it is large or massive. It is a collection of data that is complex, massive in size and continues to increase with time. It is challenging to process big data if a person or institution uses traditional methods. Due to its size and complexity, traditional methods of managing data become inapplicable for storage and processing. Some common examples of big data include social media, NY stock exchange, jet engines, and satellites.
There are three critical types of big data.
- Structured data – It is called structured because it is processed, kept, or retrieved in an organized format. Big data can be stored in names files, memory cards, hard drives, or hard disks. Nevertheless, data continue to grow exponentially, and this is posing a considerable challenge to its storage, processing, and retrieval. Fundamentally, data needs to be appropriately structured for it to be processed with ease. Data can also be quickly retrieved if it is structured appropriately. In addition, structured data can take a format that includes rows and columns.
- Unstructured – This is data that does not have a fixed format. It is the opposite of structured data. Unstructured data can contain various text files, videos, images or audios that are just mixed up. If big data is stored in an unstructured format, it poses significant challenges, especially during retrieval.
- Semi-structured big data – This kind of data has both a structured and unstructured format. The best example of semi-structured data is the one in an XML file. This structure is somewhat organized, is less complicated than unstructured big data that, in most cases, poses serious challenges, especially during retrieval.
Nonetheless, several characteristics can help one recognize particular data as big. These characteristics are:
- Variety (heterogeneous source of data, its nature, and format)
- Velocity, the speed at which data can be generated
- Availability, inconsistent at some point.
THE ART BEHIND A CYCLICAL INVENTORY SYSTEM
Cost Benefit Analysis should be the driving force when speculating. There are many different methods available to manage inventory. The most effective will always involve attention to detail, offer a precise accounting of the volume at any given point in time, and...
Break the Crystal Ball: Consult the Business Intelligence Software
Have you ever gone to a psychic or a gipsy with a magic crystal globe to see your future? No? But you must have seen it on TV or in cartoons at some point in your life, so you know how the story goes. The globe reveals the future and provides a guide on what’s to come...
HOW TO DEPARTMENTALIZE FINANCIAL STATEMENTS?
With smart break-downs, everyone’s job is easier. Insight: Many organizations struggle to gather and process their financial information because they utilize only one system to process every transaction. The following flawed system represents for example, the usual...
DEVELOP EFFICIENT QUALITY CONTROL STANDARDS
Quality Control Standards (QCS) ensure excellence in the delivery of products/services. With strong QCS, a company will remain competitive and grow its consumer base, and therefore develop a strong brand. The reason why many companies do not favor a complete...
Artificial intelligence, is machine intelligence. Unlike that of animals or humans, Artificial intelligence is anchored on human innovation, creativity, the invention as well as knowledge. These machines are programmed to think and process data like humans. These...
DEVELOP OPTIMUM DISTRIBUTION CHANNELS (ODCS)
Selling is a Route with multiple shortcuts. Optimum Distributions Channels (ODCs) represent the best supply avenues a company can establish. ODCs are extremely critical in the operational process of an organization because the decisions to set up specific avenues will...