Big data analytics refers to the complex process of using advanced analytical tools to make sense of the vast amount of information that can be gathered from sources such as IoT devices, social media, and cloud applications.
Deriving usable information from big data can help small businesses improve their management models, rise against competitors, and make strategic business decisions.
The roots of big data can be traced back to 1663 when John Graunt used statistical data analysis for the first time in dealing with bubonic plague studies.
From the early 1800s to the 20th century, data evolved at lightning speed, bringing new tech innovations like the Tabulating Machine and modern computers – and of course, the development roadblocks like data security issues and data silos as well.
Modern big data is defined as structured, semi-structured, or unstructured data that is sizable in volume, velocity, and variety; the three Vs of big data.
Industry analyst Doug Laney associates volume with the exponential amount of data inflow from business organizations, while velocity is the speed at which data comes in.
Lastly, information is available in a variety of types such as documents, images, videos, and numeric data, among others.
That said, MongoDB database provider explains that big data analytics works by analyzing big data to get actionable insights, uncovering patterns, and finding correlations in any information gathered.
Currently, veracity and value are two additional Vs that are also taken into account when dealing with data, because of the fast-paced nature of data storage and integration, mining, cleaning and transformation, analytics, and visualization.
Utilizing big data in the best ways possible can give both big and small enterprises a better chance of outperforming competitors.
However, leveraging big data can make or break a small business, because it can enable entrepreneurs to improve operations, make intelligent business decisions, and level up company performance. Many real-world use cases also make use of big data analytics.
For instance, businesses in the e-commerce and trade industry can track delivery trucks to figure out the best routes for efficient delivery.
Customer information such as purchase habits and preferences can also allow you to automate product suggestions and discounts.
There is also data analytics involved with manufacturing software as it deals with information like inventory levels, production schedules, and even office communication.
Besides e-commerce, big data analytics is also prevalent in different industries like entertainment, health, transportation, and many others.
According to SmallBizTrends, 67 percent of small businesses spend up to $10,000 a year on data analytics solutions.
Additionally, 60 percent use a web or cloud-based data analytics system. Most see it as a necessary investment that will grant them more power over their resources in the long run.
In conclusion, there are many benefits to big data analytics. Although it has its challenges to overcome, its developments have been nothing short of impressive, which is why it has become such an important part of growing small businesses.
Big data analytics can allow small businesses to:
- store, access, and process huge volumes of data in a cost-effective method;
- make better business decisions;
- leverage market data to identify trends that can apply to products and services;
- aid in creating automated marketing plans, customer offers, discounts, and so on; and
- manage human resources and keep employees productive.