A Big Data training program enables you to acquire the skills needed for careers in Big Data such as Data Analyst, Data Scientist, or Data Engineer. Discover why and how to become a professional in the field of Data Science.
Thanks to smartphones, social networks, connected devices, and e-commerce stores, companies have access to immense volumes of data. This is Big Data.
By analyzing this data, it’s possible to uncover insights: actionable information for making better decisions, understanding consumer demand, or identifying the strengths and weaknesses of the company. This is Data Science.
Data Science and Big Data analysis offer numerous advantages to businesses. However, it requires the technical expertise of professionals like Data Scientists, Data Analysts, or Data Engineers. To pursue these careers, Big Data training is necessary.
Why train in Big Data?
There are many compelling reasons to pursue a Big Data training. Firstly, the demand is extremely high. Companies from all sectors are looking for qualified professionals to harness the data stored in their systems. The number of job openings continues to rise, and this trend will persist in the years to come.
Data analysis currently represents one-tenth of the overall IT market, but it will soon account for one-third. For many organizations, it is now an absolute priority. And this applies to all industries since Big Data is used in every sector: finance, manufacturing, communication, logistics, healthcare, retail, and more.
Today, the demand for specialists already far exceeds the supply of qualified profiles in the market. This trend will only intensify in the future with the widespread adoption of Data Science and the explosion of unstructured data volumes such as images, sounds, or videos.
Naturally, in response to this high demand, the salaries offered are very attractive. Tech giants like Google, Amazon, or Facebook generously compensate their Data Scientists, but smaller companies are also looking to hire Big Data experts by all means. In France, the average annual salary for a Data Scientist is around 50,000 euros.”
Why learn Big Data?
A Big Data training program should enable you to acquire several essential skills to work in the field of Data Science. You must, in particular, learn to work with programming languages like Python, Java, and C++.
It’s imperative to master key Big Data tools such as Apache Hadoop, Apache Spark, or Hive. Techniques in Data Mining, Data Visualization, and Machine Learning are also part of the arsenal of a Data Science expert. SQL and NoSQL databases, as well as various data structures, should have no secrets for you.
Big Data professions
What are the career prospects after completing a Big Data training program? Such a path provides access to various careers in Data Science.
1. Data Analyst: Data analysts analyze data and create automated systems to retrieve information from databases and compile reports or visualizations.
2. Data Scientist: Data scientists go even further by using Machine Learning for more in-depth and automated data analysis.
3. Data Engineer: Data engineers are responsible for providing data to analysts and scientists. They create pipelines to transport data from various sources to Data Warehouses and other platforms, as well as prepare and transform data into a format suitable for analysis.
Among other Big Data careers, there are roles like architect, Big Data engineer, business analyst, and Machine Learning Engineer. Pursuing a Big Data training program, therefore, offers numerous career opportunities.”
How do I take a Big Data training course?
To pursue a Big Data training program, you can choose DataScientest. Our various pathways enable you to acquire the skills required for careers in Data Science: Data Analyst, Data Scientist, Data Engineer, and more.
These professionalizing training programs are designed by experts to meet the practical needs of businesses, and 93% of our alumni found employment within a maximum of 6 months after their training. Learners also receive a diploma recognized by La Sorbonne.
All our pathways adopt a Blended Learning approach, combining distance learning and in-person instruction, and can be completed as BootCamps or Continuous Training. Discover our Big Data training programs!
Now you know how and why you should take a Big Data training course. Discover our complete dossier on the Big Data professions, and our introduction to Data Science.
What are the trends in favor of Big Data professionals?
Many wonder if Big Data will ever come to an end or if it has reached its peak. What is clear at the moment is that the volume of data continues to grow each year, and it’s important not to ignore the trends in order to better prepare for them.
The growing number of individuals primarily using the Internet demonstrates that there are more opportunities than ever to create and collect data. By enabling organizations to make data-driven decisions at high speed, information technology will soon become the ‘hero’ of data, contributing to shaping the future of businesses.
Enhanced data analysis
Interconnected devices are expected to reach 31 billion by 2023. More and more companies are beginning to explore and harness their advantages to achieve various business objectives.
Big data is valuable for marketers, and IoT adds an extra layer of value. In addition to better targeting and personalization of marketing messages, companies will be able to create more useful products for their customers with the help of Big Data experts. This will help unlock the true potential of some of these emerging technologies like IoT, Machine Learning, and Artificial Intelligence.
Increased focus on cloud-based data analysis
Today, companies are mass migrating their Big Data projects to the Cloud. The shift of data to the Cloud intensifies the adoption of the latest features to turn data into action. It also helps reduce ongoing maintenance and operating costs. Therefore, we can expect to see more data on the Cloud in the future.
More demand for Big Data and analytical skills
An increasing number of companies are adopting Hadoop and other platforms used to store and process large amounts of data, which will quickly introduce new innovative solutions. To do this, they will hire more experts in big data analytics to provide better service to their customers and maintain their competitive advantage.