Data science, in the simplest of words, is a field of study where trained professionals take complex data, sift through it, organize it, make sense of it, and present it. In reality, data scientists have a lot more going for them. Among their many tasks, you will see those using programming skills, mathematics, machine learning algorithms, and a plethora of other tools. These tools are used to perform tasks leveraged by artificial intelligence and at the core of it all, to make sense of information.
The Importance of Data Science
We are generating more data today than we have ever done so in the entire history of humanity. There are billions and billions of sensors across the globe recording, storing, and relaying different information. To the trained eye, this information makes sense. However, for a business, not everyone has a trained eye. For example, you might be a geologist working for a construction company. You might understand what different soils are, how terrains differ from each other, and what the best possible surface to build on is. However, the organizational stakeholders might not. They might need this same information to be presented in a way that makes it easier for them
Data scientists have now become one of the most in-demand people in the world. Almost every major corporation needs a team of people with the ability to collect, store, organize, and make sense of the data they have. Data-driven decision-making is imperative for organizations to understand what their customers want, how they can get it, and how they are responding to their options now.
Data Science & the World We live in
Data science is considered a job for the future. In recent times, data science is predicted to show more growth than any other field in the world. Job search platform Indeed has recorded a 256% rise in data scientist job searches. As per the Harvard Business Review, a data scientist with experience in the field residing in the state of California can make around $200,000 a month. This information is a testament to the validity of this field. It goes to show just how much opportunity there is in the field of data science.
In a world of e-commerce and social media, all forms of data are generated on a regular basis. For example, users who only visit the website, users who make a purchase, users who make one purchase, users who make several purchases, users who only visit once, and users who regularly visit. The list goes on and on which translates into a lot of data. In order to learn from all this data, it is important to make sense of it. The data needs to be presented properly so that stakeholders can understand what is going on. This is partly why data scientists are in such high demand.
The Future of Data Science
As big data becomes the norm on a larger scale, legislation is being drafted to ensure that it is under the legal umbrella. When data protection and privacy will become legal tender, more organizations will need more data scientists. Data will need to be processed and stored properly, something a data scientist can make possible. Moreover, with time, data science has grown as a field. In the beginning, it was considered a subset of AI and there was no proper way to learn how to become a data scientist. However, in 2022, you have university degrees that teach you everything you need to know. Meta and Alphabet have created full-fledged online courses which allow you to learn all that there is to know. Using these degrees and certifications, becoming a data scientist has never been more accessible. However, in order for you to become a data scientist, you must gain experience. While the demand for a data scientist is at an all-time high, a requirement is for you to have experience. Most degrees and certifications give you clarity on the matter. However, if you are unable to secure a means to gain experience, there are scores of free data sets to use on the internet.
Getting Started with Data Science
To get a job in data science, you need to know how to tackle real-world problems. To do so, you need access to the right data. To get started with data science, you need access to a data set that you can work on. You can use Kaggle, AWS open data, and dataworld to get started. These platforms have thousands of data sets for you to go through. Take what you have learned and begin applying them to these data sets to begin your journey with data science. Using Suddenlink internet, you can get started with your data science journey. If you want to learn more, get in touch with the Spectrum offer.
By no means is data science a walk in the park. As is the case with any field, you need to learn and then apply your lessons to the real world. Once you have gotten a taste of how things work in the real world, you can pick one of the following jobs:
- Statistician
- Data Analyst
- Data Scientist
- Data Engineer
- Data Architect
- Enterprise Architect
- Applications Architect
- Infrastructure Architect
- Machine Learning Scientist
- Machine Learning Engineer
- Business Intelligence Developer
Under the umbrella of ‘data science’, you have all of these opportunities to choose from!
