Outsourcing Big Data: The Outsourcing of Data Analytics

In general, outsourcing is a practice whereby a company uses another company or individual to perform certain tasks, take over operations or provide services in its place. The subcontractor will then order its employees or computers to perform the tasks or services directly on the company site, or from outside.

The reasons to hire a contractor can be multiple. It can be cost-saving, time-saving, or simply compensating for a lack of in-house skills.

Many companies rely on outsourcing for IT-related services such as programming, application development, or technical support. Some even go so far as to replace their entire IT department with subcontractors: this is called Business Process Outsourcing.

In addition, more and more companies are using subcontractors for data analysis. This is called Outsourcing Big Data Analytics.

Outsourcing Big Data: what is it and what is it for?

It’s no secret that data analytics can have many benefits for businesses of all sizes and sectors. However, often, Big Data is considered reserved for large companies.

This perception is related to two main factors. First of all, Data Scientists are highly qualified and coveted experts. As supply is well below demand, only the largest companies are able to afford their services. In addition, many small businesses feel they do not have enough data to rely on Big Data analysis.

It is estimated that 77% of small businesses do not have a Big Data strategy. Yet, data analysis could enable them to make better decisions for marketing, product and service development, and more.

To remedy the lack of qualified profiles, one solution may be outsourcing. Indeed, more and more companies specializing in Big Data are offering data analysis as a service for organizations that do not have Data Scientists available.

OutSourcing Big Data: advantages and disadvantages

The outsourcing of data analytics has advantages, but also disadvantages. In terms of positives, this solution is usually much more affordable than using a Data Scientist.

In addition, service providers generally do not just collect and process data, but also offer interpretations and recommendations. In addition, these Big Data experts are able to analyze data much faster than a company that relies on self-service solutions.

Finally, by opting for Big Data outsourcing, companies can stay focused on their core business while enjoying the benefits of data analytics to make better decisions.

On the other hand, with outsourcing, there is always a risk of exposing the sensitive data of his company. It is therefore essential to ensure that the subcontractor takes the appropriate measures in terms of data protection. Similarly, if the contract is not done well enough, it is possible to face legal problems.

There is also a risk that the subcontractor will accept too many projects simultaneously in order to build a good reputation. This can cause delays or even errors. So be sure to meet regularly with the chosen subcontractor to make sure the project runs smoothly.

As you can see, Big Data outsourcing has both strengths and weaknesses. Nevertheless, in most cases, the benefits outweigh the disadvantages. Just be sure to choose a reputable subcontractor, experienced in Big Data and preferably in your industry, and try to maintain a good relationship from start to finish.