Big data analytics and data science. What they consist of and what value they bring to SMEs

Digitalisation has enabled the creation of new channels, the blurring of geographical barriers and the automation of multiple processes within SMEs. However, one of the great advantages it has brought is the ability to collect, analyse and store customer data. This has given companies a better understanding of their preferences and enhanced communication with their customers. This translates into greater satisfaction of their needs and their experience in the purchasing process.

The term big data refers to the large amount of data currently accessible thanks to new technologies and the development of the Internet. This data must meet three characteristics to be considered big data: large volume, high speed and wide variety. There are multiple areas of study in this field due to its importance, although in this post we want to talk about data science and big data analytics, and everything it can bring to your SME.

What is the difference between data science and big data analytics? 

Data science is a branch of big data that focuses on applying algorithms, methods and systems, or using complex software to access, manage and obtain knowledge from structured and unstructured data in order to make predictions and obtain insights. The main difference between big data and data science is technological, since in order to carry out big data processing, programmes, platforms or devices with sufficient capacity to process macro databases are needed, which means a problem in many cases.

In the case of data science and big data analytics, the key difference is that the latter focuses on analysing specific business information in order to offer solutions and enhance business strategy, seeking to provide a competitive advantage.

Big data analytics will allow you to better analyse and understand the situation of the different areas of your SME, create more personalised links with your customers based on their preferences and establish behavioural patterns that drive your business strategy, among many others. 

Data analysis will allow you to better understand your SME and enhance your business strategy.

Below, we will look at some of the benefits they provide in some sectors to give you a better understanding of their scope and applications, based on the report Data Science in the New Economy: A new race for talent in the Fourth Industrial Revolution, produced by the World Economic Forum.

• Automotive 

In this industry, data is used, for example, for customer segmentation and personalised promotions, better control of the supply chain and predictive analytics in a variety of areas, such as product maintenance.

• Consumer industry 

In the consumer industry, it enables you to, among many other things, acquire, retain and enhance customer loyalty with all the data and insights you have at your disposal. It also helps you optimise the frequency and size of purchases, and improve the return on your marketing investment. The information allows you to create targeted actions that provide more guarantees of success. 

• Financial 

Data analytics, coupled with other models such as machine learning, has enabled the automation of risk management and customer data, monitoring the influence of certain financial trends and market developments on historical customer data. Many firms have been able to predict movements in the stock market, as well as detect fraud or anomalies in customer behaviour.

• Health 

Data collection from reports or clinical forms together with new sources of information such as wearable devices (smart watches, mobile devices, pedometers...) allow rapid identification of any alteration in the person's behaviour or vital signs.

• Insurance 

This knowledge enables further personalised products, price optimisation, risk assessment and prediction of potential claims, among other things. In this way, the industry can identify, attract and retain customers in a more optimal way. 

• Industry

Some of the activities in which big data analytics is most commonly applied in industry include: 

1. Predictive and conditional maintenance to prevent machine failures. 
2. The performance, quality assurance and defect identification of your products. 
3. Forecasting demand and performance, being able to cover your stock, optimise your supply chain and ensure that orders can be fulfilled efficiently. 
4. Automation and the design of new installations to increase productivity. 
5. New processes and materials for the development of products and production techniques, achieving customer specifications.

As we have seen, big data analytics provides a lot of information from which great benefits can be derived. This type of technology is not only available to large companies. More and more systems are starting to be developed so that any SME can enjoy these benefits.  

The multiple applications it provides will allow you to introduce big data analytics in your SME to boost those areas you want to promote. Moreover, if you want to go a step further, you can combine it with new technologies such as artificial intelligence, the internet of things, augmented reality or machine learning to multiply your profitability. Its implementation will help your SME to grow in a secure way, as your decisions will be based on the information you have managed to acquire.