Strengthen your business growth with Data Science

What is data for, why does your company need to analyze it, and use it as a growth driver?

We're going to talk about the benefits data can bring to a company — and we can tell you, there are many!

Let's set the basics. In a world where the internet takes up so much space, we're seeing two parallel technological accelerations:

an explosion of data being produced

spectacular capabilities to store and process that data

This data explosion stems from the multiplication of sources. Social networks, connected devices, weather data, and many other data generators are real gold mines for companies.

When this rich data is collected and stored, it can bring enormous benefits to companies if it is well interpreted. That's where Data Science enters the stage!

How do you handle such a large flow of data?

Data today is too voluminous to be stored centrally, in particular because of cost and the lack of power of those technologies. We're seeing a real awakening that has pushed many researchers to look into the topic and that has led to the emergence of technologies to handle this enormous data flow.

For example, the HDFS infrastructure (Hadoop Distributed File System) is a storage system truly suited to Big Data, capable of holding terabytes or even petabytes of data. All this data is stored in three places to avoid any risk of data loss.

There's also Spark, a distributed data processing technology widely used by data experts! The idea behind this framework is to make developers' lives easier so that any dev can process this data transparently without much code effort behind the scenes. Spark handles all the optimizations, all the calculations, and dispatches the commands correctly at extremely high speed. There's also a library of algorithms for Machine Learning. It's a bit of a Swiss army knife for the data expert.

Designing these platforms well eliminates many of the problems tied to implementing Data Science. It also helps companies turn collected data into actionable information more efficiently and quickly.

What does it concretely enable?

Once companies have fully gained the ability to process large volumes of data, the next question is: What can I do today that I couldn't do before, or What could I do better than before?

Many companies have made Data Science a priority and invest heavily in this area.

These teams of experts will then leverage this data to improve the company's products and services, helping them gain a competitive edge. How?

By understanding customer habits and expectations and being able to offer more personalized services and tailored offers for each segment based on the results that data reveals. Companies can then make better decisions and improve their performance versus the competition by anticipating their actions to reach their goals.

Sounds great, right?

Is it possible to predict everything with data?

Olivier Yoo, Data Analyst, shares his take in this interview:

"There are still many companies under the illusion that Data and Machine Learning are magic and that you can do anything from nothing. In theory, yes — you can predict anything. You can build a model that will predict something from any data, but there's a risk that it will predict it very badly, and that's the whole point of the data professions: knowing when and at what threshold we consider that the model predicts well."

Another piece of advice: be careful! Even though you can predict many things with data, you shouldn't drift away from the topics that are at the heart of your business. You need to focus and think the data roadmap around the company's structuring processes.

What about hiring?

Companies' need for data scientists is growing fast!

In a brand-new and fast-expanding market, demand far outstrips supply, and the companies that absolutely need these experts are fighting over them. We're moving toward the same hiring model as for developers!

Talent acquisition is an obstacle companies face because these profiles are scarce!

Conclusion

If you're in this situation, get in touch — we're here for that, and our talent is just looking for the best projects! Who knows, it could be yours?

Vincent, our Data career coach, will be happy to help you find the profile that matches your project.