Data is the backbone of business operations in the digital world of the 21st century. Particularly, data analytics and insights generated help firms make smarter, data-driven decisions.
The field of data analytics is constantly evolving, and it is necessary for firms to understand key terminology. Two of them that will help firms utilize data appropriately are small data and big data.
Also Read: Data Privacy in the Digital Age: Protecting Your Personal Information
Discover the key differences between small and big data and some upsides and downsides of both.
By developing a thorough understanding of the differences and the pros and cons, a firm can make valuable use of costly data.
Distinction Points Between Small and Big Data
The name itself gives away a major distinction point, which is definitional. Small data are where traditional data processing methods can be used for an individual to understand it. It can be handled by Excel and is much easier to analyze and visualize.
Big data is defined by the volume and complexity of the dataset. Processing this data cannot be completed by an individual with traditional methods. Apart from the size, the speed at which data flows and the variety also contribute to its complexity.
Some other key differences between the two are:
Storing the Data: Small data can be easily stored on on-premises servers and local machines. Big data requires specific storage systems (like cloud storage) to process and manage its sheer volume and pace.
Applications: The use case of small data is limited to a single firm or industry’s use for, e.g., performance metrics or sales growth. Big data is for industries with large volumes of data for, e.g., e-commerce and healthcare.
Each type of data has its own set of upsides and downsides.
Pros and Cons of Small Data
Small data is significantly easier for firms to collect, process, analyze, and manage overall. Thus, it is cost-effective for the firm. Additionally, since the database is small, insights can be generated faster, which allows for quicker decision-making.
However, the detail and level of these insights are restricted. It will give a brief overview of the data and might not dive into narrower patterns. It becomes an issue when complex situations are oversimplified.
Pros and Cons of Big Data
It allows for a complex analysis of the complex database. Supported by advanced technology, it provides insights from various sources for better business decision-making.
However, gathering these insights requires investment in expensive software and hardware. Additionally, running these systems requires its own team of experts. There are also concerns about maintaining data confidentiality and integrity.
