Most data scientists spend years learning about calculus, probability, statistics, and everything data science. However, it is seen too often that such data scientists have a hard time when they get into the industry. This is just because they aren’t familiar with some of the common business terms. Therefore, this article is aimed at providing a guide to business jargons for data scientists.
If you are a data scientist moving into the industry, this article is certainly for you. But first, let’s identify if you will ever need to learn these terms or not.
Tell-tale signs that you will need to learn business jargons as a data scientist
You should know that knowledge of business jargons will come handy if your future or current work entails you to do the following:
- Research on product development that contains any kind of unit economics.
- Automate business processes through data.
- Optimize business processes through data.
- Create business analytics dashboard for stakeholders or operations.
- Work with people who are business-heads.
- Start your own business.
Business jargons aren’t a must if…
Business jargons aren’t a must if your future or current work entails you to do the following:
- Work on academic research.
- Work on a non-profit oriented project.
Nonetheless, it wouldn’t hurt to pick up on the terms discussed below if you are really looking to expand your knowledge.
Ten business jargons a data scientist should know
The following list contains many business jargons along with their meaning and frequently used acronyms. Spend the next 5 minutes going over the list and you are good to go.
1. Key Performance Indicator (KPI)
A Key Performance Indicator (KPI) is a quantifiable measure used to evaluate the success of an organization, employee, etc. in meeting objectives for performance. It is a metric used for measurement.
Example usage: “The number of sales is a key performance indicator for measuring the growth of our business.”
Revenue is the income that a business has from its normal business activities, usually from the sale of goods and services to customers. Revenue is also referred to as sales or turnover.
Revenue is generally of two types:
- Gross Revenue – Gross Revenue is the total amount of sales recognized for a reporting period, prior to any deductions such as tax, refunds, etc.
- Net Revenue – Net Revenue is the total amount of sales recognized for a reporting period after all deductions such as tax, refunds, etc.
Example usage: “We made a gross revenue of $400,000 this year and we had a net (revenue) of $100,000.”
3. Business-to-Business (B2B) / Business-to-Consumer (B2C)
B2B and B2C are some of the most common acronyms in the world of business.
- Business-to-Business (B2B) – B2B is a business model where the supply of good is services is done by one business to another.
- Business-to-Consumer (B2C) – B2C is a business model where the supply of goods or services is done by business to end-users or consumers and not other businesses.
Example usage: “Our food delivery company is both B2B and B2C since we provide food to businesses as well as general customers at their home.”
4. Return on Investment (ROI)
Return on Investment or ROI shows you how much you profited or lost on a business investment relative to how much you spent on it.
If you gained any kind of profit from an investment, it is commonly referred to as a positive ROI and if you didn’t reach any profitability with your investment, it is commonly referred to as a negative ROI. However, if your investment was able to bring exactly the invested money (no more or less), it is known as breakeven.
Example usage: “I had a positive ROI in the last company that I had invested in since it made me $30,000 in profit.”
5. Cash Flow
Cash Flow is the amount of money coming in and going out of business.
If the amount of income is greater than the amount of expenditure then the cash flow is positive. In contrast, if the amount of expenditure is greater than the amount of income then the cash flow is negative.
Example usage: “Our company has been in negative cash flow for the past 6 months and thus, we do not have any money left to pay our staffs.”
‘An asset is a resource with economic value that an individual, corporation or country owns or controls with the expectation that it will provide a future benefit.’ – Investopedia
Furniture, Land Property, Inventory, etc. are examples of assets.
Example usage: “The four chairs that we bought are a tangible asset to the company.”
Liabilities are the exact opposite of assets and are responsible for decreasing the company’s total amount (capital).
Bank loans, Taxes, Bills, etc. are examples of liabilities.
Example usage: “The 4 million bank loan that we are about to take is going to be a very huge liability for the business.”
Equity is the amount of shares an individual has of a business. It can also be referred to as the owner’s part of business assets.
Example usage: “I own 20% equity in our data science startup.”
9. Balance Sheet
‘A balance sheet is a financial statement that reports a company’s assets, liabilities and shareholders’ equity at a specific point in time, and provides a basis for computing rates of return and evaluating its capital structure.’ – Investopedia
Example usage: “Our balance sheet shows that we have $400,000 in assets and $20,000 in liabilities.”
10. Profit margin
Profit margin is the amount of profit a business earns in each sale.
It is normally expressed in percentage relative to the manufacturing cost of an item or the amount needed to perform a service. Profit margin is also mentioned in gross and net terms as:
- Gross Profit margin – Gross Profit margin is the total margin on a sale prior to any deductions such as tax, refunds, etc.
- Net Profit margin – Net Profit margin is the total margin on a sale after deductions such as tax, refunds, etc.
Example usage: ‘We have a profit margin of 10% on our new product.”
This article on ‘Business Jargons For Data Scientists’ is our effort to help our click readers get up to speed in their new business roles or current ones. We hope that we could help you expand your knowledge with the most frequently used terms in business.
Also, if you are trying to become a data scientist or are looking for your first job, this article on ‘How To Get Your First Data Science Job in Nepal?‘