Understanding Big Data

Get To Know: Big Data

Data is a term referring to facts and statistics collected together for reference or analytical purposes.
In this digital world, everyone leaves a digital footprint. Be it through lifestyle documentation, entertainment media, content creation or even posts on social media, the number of internet-connected devices we interact with daily record vast amounts of data about us and our environment.
This "vast amount of data" has been tagged Big Data.

Defining Big Data

Big Data, is a term used to describe large, hard-to-manage volumes of data. It refers to large, fast and complex data that is difficult, if not impossible, to process using traditional methods. It requires new and innovative ways to be collected, stored, processed and exploited.

Characteristics of big data

The innate characteristics of big data include;

• value
• variety
• volume
• velocity
• veracity

These characteristics are often referred to as the 5v's of big data

Value: this refers to the benefits collected data possess. It relates to what organizations can do with acquired data and is the major reason organizations spend time and effort studying big data.

Variety: this refers to the type and nature of the data. Data today could be in various formats(text, image, video or audio). Variety aims at the diversity of data and its sources (such as people, machines and organizations).

Volume: this refers to the scale or increase in the amount of collected and stored data. It is the basis of BIG data as it refers to the size and amount of data collected.
The volume of big data is mainly composed of data gotten from sensors, devices, social media, enterprise data and voiceovers.

Velocity: Daily, data is being generated at a fast rate in a never-ending process. The speed, at which this data is being generated and processed is referred to as velocity. This is a very important aspect for companies that need their data flowing as quickly as possible.

Veracity: this refers to how trustworthy the sources of data are. It accounts for the quality and origin of data, conforming to facts and accuracy. Attributes such as consistency, completeness and integrity play a huge role in determining the veracity of data.

Benefits of Big Data

Big data comes with a handful of benefits which include:

• improved operational efficiency
• improved problem-solving approaches
• optimized product development
• enable smart decision making

Application of Big Data

By combining big data with high-performance analysis, certain business tasks can be addressed. These include:

• Early detection of fraudulent activities
• Calculation of risk portfolios
• predictive maintenance of machines and equipment
• improved customer experience through user specification and advanced client interaction

Challenges of big data

Like every other field, big data is not without its challenges and limitations. It is important to understand these challenges to avoid getting stuck at the initial stages of big-data-driven projects due to a lack of awareness or capacity to tackle their challenges.

Some of these challenges include;

• Inadequate storage capacity for big data: This is a pressing challenge for industries and individuals alike as the amount of data stored in data centres and databases continues to increase exponentially.

• Rapid change of big data technologies: keeping up with the latest data technology could prove to be a challenge to certain individuals who have already familiarized themselves with certain methods of processing data.

• Lack of data professionals: Data professionals such as data scientists, data analysts and data engineers who are experienced in working with appropriate data management tools are of great importance to a data-driven industry. However, these professionals are currently in short supply.

conclusion:

This article has allowed you to understand;

• the definition of big data and what differentiates it from normal data.

• the characteristics of big data and how they affect an industry

• the benefits and applications of big data and lastly,

• the current challenges and limitations faced by big data professionals and industries.

If you are aware of any other challenges, or better still, possible solutions to the challenges listed above, share your thoughts using the comment section below