Big data refers to huge amounts of structured and unstructured data; however, processing such huge amounts of data through traditional data management tools is inefficient and impossible. To understand big data, you need to realize the devices that collect it today, for example, barcode scanners, mobile cameras, CCTV cameras, motion sensors, smoke detectors, web analytics tools, CRMs, etc. You can see from the examples that these devices collect a wide variety of data types, hence the structured and unstructured part in the definition. The sheer speed at which the data is produced cannot be controlled and processed with traditional methods and tools.
However, the use of big data and the integration of big data analytics technology gives companies a competitive advantage over their competitors.
Big data and small businesses
It will only be a thing of the past when terms like big data and business intelligence were only associated with large companies. Today, small businesses need to leverage the data they collect to stay competitive. For years, cost has been the main reason why small businesses haven’t adopted big data analytics technologies, but this has now changed. Budget-friendly tools are available for small businesses to take advantage of the data they collect today. According to some experts, small businesses can take better advantage of big data because they can make necessary changes much faster than large enterprises, i.e. respond in real time to insights from available data.
According to a 2016 IDG survey, 78% of large enterprises agree that a big data strategy can change the way companies have always operated. This shows the adoption of big data technology and strategies for large enterprises and reinforces the fact that small businesses can become irrelevant if they do not adopt the same strategies.
Benefits of big data analytics
Large Data and Big Companies, a report by IIA Director of Research, Tom Davenport, reveals that companies benefit greatly from big data analytics, especially in improving their products, making business decisions faster, and reducing costs. Here are some ways small businesses can benefit from big data.
• Cost savings
The initial cost of implementing big data tools and strategies is undoubtedly high, but the long-term benefits are unparalleled. Healthcare is a good example of how leveraging large amounts of data can help companies reduce costs, regardless of size. Using predictive analytics, Medicare and Medicaid Services have prevented more than $210 million in healthcare fraud with just 2 years of using the aforementioned technology.
In addition to preventing fraud, small businesses can also reduce their costs by avoiding creating more inventory than necessary, including better partners in the supply chain, etc.
• Improved decision making
This is the biggest advantage of large amounts of data. It enables companies to accelerate decision-making by processing the data quickly and providing timely insights. In the past, business decisions were reserved for future strategies in light of available data and the trends observed therein. The amount of data companies sit on today is huge and so more powerful insights can be extracted from it.
This huge amount of data requires the use of modern big data hardware technologies. Once both are in place for a company, they can better understand customers, create products that better match what customers want, and build a brand based on the most respected values.
• Impenetrable security
Businesses today are more focused on leveraging large amounts of data to enhance their core capabilities, but less focused on more serious concerns such as cyberthreats and security breaches. Almost every small, medium and large business today is connected to the internet. In addition, the Internet of Things has expanded the attackable security surface for businesses, making it easier for cybercriminals to attack networks and penetrate corporate databases.
The biggest concern for modern businesses is that they have to “respond” to cyber-attacks that have already happened rather than being able to prevent them. The use of big data and big data analytics tools can be a game changer in this area, enabling companies to prevent security attacks long before they happen.
Key technologies that help companies get the most out of big data
As a small business, you will need to familiarize yourself with various technologies that help you store, analyze and take action on big data. Here are some important ones:
It is a framework that supports the storage of large amounts of data using an open source approach. Once data is stored, Hadoop enables the use of a variety of applications using “clustered hardware” at its base. The cluster of basic hardware makes it possible and easy for companies to process big data despite the increasing volume.
• Data mining
This is the technology that enables entrepreneurs to capture insights, patterns and trends from big data that cannot otherwise be obtained with a traditional approach. Data mining allows you to jump into a large sea of structured and unstructured data, make sense of it all and produce analytical insights that help companies make real-time and future decisions.
• Predictive analytics
Predictive analytics go side by side with data mining. Artificial is at the heart of predictive analytics, allowing business owners to adjust their current strategies by making predictions about what will happen for the business based on existing data.
• Text analysis and mining
A major concern for modern businesses is analyzing the noise on various web platforms such as forums, blogs, social networks, etc. to understand what customers expect from a particular brand. Learning more about brand mentions and understanding customers’ impressions of your brand can help you adjust your marketing approach to win customer loyalty. Text mining helps small to large businesses sift through text data from emails, blog posts, social networks, etc. and hear the “voice” of customers.
With the rise of smartphones, artificial intelligence and IoT (internet of things), it has become clear that companies will now have to process mountains and mountains of data and leverage big data analytics and processing technologies to stay ahead of the competition.