What is data science?
Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. For most organizations, it is employed to transform data into value in the form of improved revenue, reduced costs, business agility, improved customer experience, the development of new products, and the like. Data science gives the data collected by an organization a purpose.
Data science vs. data analytics
While closely related, data analytics is a component of data science, used to understand what an organization’s data looks like. Data science takes the output of analytics to solve problems. Data scientists say that investigating something with data is simply analysis. Data science takes analysis another step to explain and solve problems. The difference between data analytics and data science is also one of timescale. Data analytics describes the current state of reality, whereas data science uses that data to predict and/or understand the future.
The benefits of data science
The business value of data science depends on organizational needs. Data science could help an organization build tools to predict hardware failures, enabling the organization to perform maintenance and prevent unplanned downtime. It could help predict what to put on supermarket shelves, or how popular a product will be based on its attributes.
For further insight into the business value of data science, see “The unexpected benefits of data analytics” and “Demystifying the dark science of data analytics.”
Data science jobs
While the number of data science degree programs are increasing at a rapid clip, they aren’t necessarily what organizations look for when seeking data scientists. Candidates with a statistics background are popular, especially if they can demonstrate they know whether they are looking at real results; have domain knowledge to put results in context; and communication skills that allow them to convey results to business users.
Many organizations look for candidates with PhDs, especially in physics, math, computer science, economics, or even social science. A PhD proves a candidate is capable of doing deep research on a topic and disseminating information to others.
Some of the best data scientists or leaders in data science groups have non-traditional backgrounds, even ones with very little formal computer training. In many cases, the key ability is being able to look at something from a non-traditional perspective and understand it.
For further information about data scientist skills, see “What is a data scientist? A key data analytics role and a lucrative career,” and “Essential skills and traits of elite data scientists.”
Data science salaries
Here are some of the most popular job titles related to data science and the average salary for each position, according to data from PayScale:
- Analytics manager: $71K-$131K
- Associate data scientist: $61K-$101K
- Business intelligence analyst: $52K-$97K
- Data analyst: $45K-$87K
- Data architect: $79K-$159K
- Data engineer: $66K-$132K
- Data scientist: $60K-$159K
- Data scientist, IT: $$60K-$159K
- Lead data scientist: $98K-$178K
- Research analyst: $43K-$82K
- Research scientist: $52K-$123K
- Senior data scientist: $96K-$162K
- Statistician: $55K-$117K
Data science degrees
According to Fortune, these are the top graduate degree programs in data science:</…….
Source: https://www.cio.com/article/221871/what-is-data-science-a-method-for-turning-data-into-value.html