The world is online, and hardly any business decision is made without troves of data informing it. There are thousands of petabytes of data online, and every single bit helps business leaders make better decisions. Without the internet’s capability to collect massive amounts of data, it would be hard for businesses to compete in any market.

Yet, with so much data to go through, business leaders must also know how to interpret data. The internet is an invaluable tool for collecting a seemingly endless amount of data about anything that could affect a company. Yet, it can also be useless for interpreting that data and putting it to use.

It’s up to data scientists to take the information that the internet collects and distill it into a usable format. Business leaders depend on data science to communicate data and display it in an understandable way. Yet, few understand the first thing about data science.

For many, the processes behind it can seem like a total mystery. Understanding data science is easy though — all it does is interpret data so that the average person can understand it. And to learn more about how data science interprets data, and how it’s used in business, keep reading below!

Successful Businesses Depend on Data

The first thing to understand about data science is that it’s instrumental for any successful business. In fact, the applications of data science are so wide that almost every company depends on it in some way. Whether it’s as a part of the company’s marketing or as a part of its product research, data science plays a role.

The best businesses are ones that work to ensure that they interpret data correctly. They understand how important having the right data is, how crucial it is that they comprehend it correctly, and how vital it is that data is communicated well. Good data science is at the core of any successful business’s strength.

To Interpret Data, You Must First Collect It

To interpret data well, you must first make sure that your data is trustworthy. You must make sure that there aren’t any flaws in it, and that it’s relevant to your company. And this comes down to checking the methodologies with which your data was collected.

To learn more about how data collection affects your ability to interpret data, keep reading below!

Data Collection Methods Matter Most

There are several different kinds of data collection that data scientists use, depending on their fields. Academic researchers may use formal data collection methods, for example. They may work to maintain that data is collected in the same environment every time, and that each experiment is performed exactly the same every time.

Yet, corporate researchers may not emphasize as much academic rigor when it comes to collecting data. They may reach out to audiences over the internet and collect surveys at random, from people across the world. A market survey may be done on the curbside or in a coffee shop.

Before you start collecting data, you should understand how important it is that the data is trustworthy. If the decisions that your data will inform can affect your company for years, then it should be held up to high standards. Yet, if you need to conduct basic market research for your company, you may not need to work as hard at collecting it.

Qualitative Data Differs Dramatically From Quantitative

There are also different kinds of data that may be included in any kind of report. For most businesses, quantitative data informs most company decisions. It tells business leaders about the number of people consuming a product, visiting a website, or interacting with the company’s social media.

Yet, qualitative data matters just as much as quantitative data, and it should be interpreted just as thoroughly. While quantitative data can tell you if people are engaging with social media, it won’t say if that engagement is positive or negative, for example. Qualitative data tells you if you are in control of your market, while quantitative data tells you if you’re still a part of it.

Know What May Affect the Quality of Your Data

The final part of data collection is awareness; you must stay aware of anything that can affect the quality of your data. There are always excruciating circumstances for any kind of data collection that must be accounted for. Something as insignificant as the weather can actually change what kind of data you get.

Knowing what affects your data is also a part of interpreting it. It’s the first step towards identifying trends and patterns, and towards making more informed business decisions.

Correlation is Not Causation

There’s one fundamental part of interpreting data that everyone should be aware of: correlation is not causation. It’s easy to mistake two data trends as causing one another. For example, at first glance, the chart comparing the number of people drowning in a pool to movies Nicholas Cage stars can indicate that they cause each other.

Yet, it makes more sense for there to be another, larger factor at play affecting them both. And for the Nicholas Cage example, the factor is simply is probably related to the fact more people are likely to go swimming in Summer, and Nicholas Cage is a summer-movie star.

Analysts should try to stay aware of all factors that can affect data points before trying to identify trends. Otherwise, it’s easy to misinterpret data and misinform business leaders. They can lead companies astray just by being too confident in a trend and failing to maintain a reasonable level of doubt towards research.

Data Informs Decisions and Helps Businesses Succeed

It takes experts to interpret data — not everyone can do it. You must consider the way it was collected, anything that may have affected that data while collecting it and stay aware of extenuating factors. Several things can affect research, and the way to interpret data well is by staying aware of as many as possible.

Few businesses can do it by themselves, and almost every company needs help interpreting data and making decisions at some point. And to learn more about how data affects your company, just keep reading here. Technology depends on data, and it’s a vital part of any business.