Business Ideas From Big Data

Business Ideas From Big Data

Big Data and all that it entails are among the most important levers of digital transformation that we repeatedly repeat in Our Secure Data. Beyond the analysis and conclusions of value, the trail of thousands and thousands of data left by our digital, personal and professional life offers endless new business opportunities.

To see the exponential growth of Big Data in economic terms, we can look at the information offered by the IDC consulting firm: in 2010, companies based on massive data recorded sales worth 2.3 billion dollars, and only five years later, in 2015, the figure multiplied by 7, reaching almost 17 billion.

Although the potential of massive data can benefit practically any economic sphere, to begin with, the sectors that benefit the most are those that make the most intensive use of data: consumer companies, insurance companies, telecommunications companies, and banks.

Some business ideas with Big Data

Like the benefited sectors, the typology of entrepreneurial projects that can benefit from Big Data to offer new services and generate business is varied. Here are some examples:

Data mining consulting: the value of interpreting Big Data.

Having a lot of data is essential, especially if it is pertinent. But what adds value is the information that can be extracted from its processing and analysis. Generating business value from big data analytics is essentially what data mining consultants do for their clients.

It is about finding patterns, correlations even between unrelated data, and drawing conclusions that can help make better decisions for the direction of a business ( Business Intelligence ). These conclusions can be applied to the creation of new products, the search for new potential customers, the detection of cost-saving opportunities, or the improvement of production efficiency, to name just a few examples. All these improvements ultimately improve the competitive advantage of companies against their rivals.

Market research and customer study: when detail is key

Big Data analysis is already vital for business management in general. Still, it is even more so when we talk about two essential facets of marketing: market research and customer analysis.

If there is more and more data available on all types of companies and markets, the volume is even more significant when discussing potential clients. The search and processing of all this data to obtain valuable information is a service offered to companies that need to know the size and competition of the market they are targeting or that need to know in-depth the preferences and behavior of their customers. Current customers or potential customers.

With this valuable information in their hand, they will have a competitive advantage, being able to anticipate their needs by creating personalized products or services. An example is Amazon and its Amazon Fresh service. Before entering the new and complex fresh market, it analyzed its data in detail to offer the best shopping experience.

Fraud detection service: one step ahead of cybercrime

Businesses are becoming more digital, and as a consequence, so is the risk of fraud and the need for its detection.

Sectors such as banking, insurance, or telecommunications require services that help them prevent this type of crime, and thanks to Big Data and associated technologies such as Artificial Intelligence or Machine Learning, it is already possible with a level of detail and precision that even allows a certain degree of prediction of suspicious behavior.

Human resources: looking for the best talent with Big Data

The trail we leave behind in our digital lives is a precious data source for talent scouts. Thanks to Big Data, human resources managers can obtain a much more accurate portrait of the professional profiles and trajectory of the candidates and even delve into our online reputation in great detail.

The information provided by Big Data can also be combined with neuroscience and gamification to create innovative personnel selection and aptitude validation methods such as those developed by Pymetrics or HackerRank.

Thanks to the potential of Machine Learning, these companies can even make predictions about how a specific candidate might fit into the job.

E-commerce service: when customer data makes the difference

When we talk about e-commerce or online sales, having the maximum volume of data possible about customers and suppliers is key to offering the best service and having a critical competitive difference.
Based on aspects such as the tastes and preferences of potential customers and knowing the availability or profit margin of the products, it is possible to implement an online store with more chances of success.

An example of a service that unites Big Data and e-commerce is Apparatus, a cloud service that adapts to any online store and is scalable.

Survey service with Big Data: beyond opinion

Beyond our almost automatic digital trail, asking users or customers directly for their opinions and experience is still widely used and demanded by all business and government organizations.

Although with the emergence of Big Data, it seemed that surveys would be a thing of the past, the truth is that they continue to be valid as another method of obtaining information.

The interesting thing, then, is to establish a methodology or develop algorithms that automatically and intelligently cross-reference the results of the surveys with other types of data. The information resulting from this crossing can be precious and more complete than that obtained by traditional means.

Some particularities to take into account before working with Big Data

These are just some examples and ideas of the possibilities that Big Data offers to entrepreneurs to create new businesses.

People interested in driving a big data-centric business should be aware that when dealing with data, which is often confidential or sensitive personal data, it is essential to keep in mind how sensitive it is to deal with information that is often sensitive or confidential.

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