Big Data for SMEs ? Do small and medium businesses really need solutions to manage a huge amount of data? Probably many managers of small businesses and emerging projects do not fully understand that the transmission and use of data are very involved in our current daily lives.
From a simple query on our bank’s website to interaction on social networks, these are operations that generate computer data. Not to mention the use of Artificial Intelligence and the Internet of things , among other technologies that work through the exchange of information on the network.
But the truth is that it is about more than just transmitting and storing data . Every day the number of companies of various sizes that take advantage of the potential of data for many different purposes increases. For example: to get to know your customers better, optimize products and offers or launch new ones and even improve your processes.
Certainly as a small business manager, you too can benefit from the valuable insights and increased capabilities that Big Data provides . Here we will remind you of the concept of this technological advance and its scope of application. In addition, we will explain the advantages that this type of solution offers your company.
Big Data: A Complex Definition
When we hear or read the expression Big Data , it is natural that we think of the collection, storage and processing of amounts of data already expressed in Terabytes. Although very soon they will also be in higher units of measurement such as Petabytes and Zetabytes. It is obvious that conventional IT solutions do not have the capacity to manage such a volume of information quickly.
Consequently, this explosion and expansion of the use of data through the Internet required effective tools. Hence, various technology developers focused on creating a set of solutions and infrastructures suitable for assimilating and managing so much data. All of them comprise what is known as Big Data .
However, this concept would be insufficient if we do not understand the importance of extracting value from this information in real time. Value contained in indicators whose analysis facilitates and optimizes the performance not only of companies, but also of public administrations.
Five Variables That Define The Dimension Of Big Data
Experts in the matter at hand agree on complementing the concept of Big Data with the relevance of five variables. Curiously, all of them have the letter “V” as an initial:
Specifically, the condition of “Big” or “massive data” does not come from exceeding a certain amount of information. Rather, it arises when processing and taking advantage of the data becomes a challenge for the company.
Obviously the intensity with which the data is generated is highly variable and tends to increase regularly to critical levels. That is why it is necessary for organizations to respond to this circumstance immediately and efficiently.
It is obvious that the capacity of Big Data solutions is not limited to the amount of information they can manage. Its versatility to process the great diversity of formats in which the data is contained is also relevant: texts, databases, audios, images, videos, etc.
Today, fake or incorrect data not only proliferates, but also becomes an obstacle to making correct decisions online. Undoubtedly, one of the functions required of Big Data tools is to filter and guarantee the reliability of the information captured and processed.
As we have already said, what is interesting about all the data captured and processed is the number of advantages that organizations can obtain from it.
Big Data: A Quick Classification
Based on the above, it is pertinent to briefly present a classification of “big data”. Two criteria have been accepted for this: origin and structure.
- of personal communication. Data generated by people through emails, messaging applications, voice messages, etc.
- From web browsing and social interaction. This includes the data provided by web content, user navigation and search, as well as their interaction through social networks.
- Shopping, banking and billing.
- Biometric data. That is, those obtained through human identification technologies, whether by fingerprint, face, voice and others.
- Institutions , generally public: statistics on the economy and population, medical histories, among others.
- IoT: Obviously, it is the data generated by communication between machines (M2M) and between machines and people (M2P), through sensors and other Internet of Things devices.
Depending on how it is structured, the data can be:
- Structured. These are the ones that have defined format, length and size. They are usually displayed in columns and rows and can be processed with any data mining tool , such as databases.
- unstructured. On the contrary, unstructured data is binary data with no identifiable format or structure, but which can be stored as such in the system. Here they enter: text files, emails, PDF, images, videos and audios.
- Semi-structured. They are data that do not have a fully defined structure, but do have a precise organization in metadata that describe objects and relationships. For example: HTML and XML.
Big Data For SMEs, How They Can Take Advantage Of The Potential Of Data
Definitely, for any company -but especially for SMEs- Big Data solutions can give a decisive boost towards expansion and high profitability. Let’s look at three key applications of this technology:
By processing data obtained from email marketing, content marketing, ecommerce transactions, geolocation and other sources, it is possible to personalize products and offers. Precisely “tailor-made” goods and services are changing consumption patterns and generating a positive impact on target audiences.
In this regard, Big Data solutions help achieve a better understanding of customer behavior, demographics and status. Therefore, in addition to facilitating personalization, it allows you to optimize or reorient marketing strategies to achieve more conversions and effective sales. Likewise, the technology we are dealing with is a valuable support in the identification of opportunities and in the creation of new lines of business.
Improvements In Operability And Processes
IoT solutions complemented by Big Data solutions make efficient monitoring of the supply chain and production processes possible. These solutions contribute to the control of the location and use of tools and machines, but also determine vital actions such as preventive maintenance. This reduces costs for unplanned downtime and major repairs.
Fraud And Risk Prevention
Indeed, there are Big Data tools designed to prevent fraud by identifying situations such as the alteration of customer purchasing patterns. Thanks to access to data and its analysis in real time, this technology enables immediate responses that minimize damage. Furthermore, it establishes predictive models that allow anticipating risk situations.