The Different Ways Businesses Can Use Raw Data

By Guest Author | data raw data | February 3, 2021

According to leading business experts, data is the newest hot commodity in the business world, with some estimating that data has eclipsed oil as the most valuable asset in the world. While this may be true, there is still a lot of confusion regarding data, how it is collected, the types of data that are available for use, as well as how data can help businesses do everything from marketing to streamlining their internal processes. Raw data in particular is a hot topic in the business world and for good reason; by processing raw data, businesses can get key insights into their clients’ wants and needs, help them improve their marketing campaigns, personalize their content, and ultimately improve their bottom lines.

Before delving into some of the uses of raw data, however, business owners first need a deeper understanding about what data is, how it is collected, and how it can be transformed into the valuable asset that it is.

Data: Breaking Down the Basics

Starting with the basics, data can be described simply as facts or statistics that have been collected for analysis. Data can be broken down into two different types: quantitative and qualitative data. Quantitative data is data that deals only with things that can be measured objectively. This can include the price of items at a store, a business’s daily sales figures, the number of employees on a business’s payroll, and other such measurable things. Qualitative data, on the other hand, deals with information that cannot be measured objectively, such as customer opinion, employee morale, and other subjective aspects of a business. Both types of data play an important role in improving a business; however, most businesses find quantitative data easier to understand and use in the everyday running of a business.

But data on its own can only get a business so far. By processing raw data, businesses have access to the insights it has to offer. Data science professionals make it their goal in life to take both kinds of data and process them into usable information. Click here for more information about the importance of data science professionals as well as what a career in the field could offer.

Why is Raw Data Important?

Raw data – which is also called atomic data, primary data, source data, or unprocessed data – can be seen as the first step in the whole process of processing and using data. Raw data comprises data that has been collected but not yet analyzed or processed. Examples of raw data include information such as a business’s list of customers and how much they spend with the business; the weekly wages paid by a business to employees; taxes paid versus income earned by a business; or the weekly production figures of a manufacturing plant; and other such information. While each data set on its own provides insight into one or two aspects of a business, when processed by the business through data analysis software, such data can be collated to provide deeper insight into a business’s processes. 

How is Raw Data Collected?

Raw data can be collected or generated by a human user, or by computer programs designed for the purpose. Consumer data, raw and processed, can be broken down into four main categories; personal data, which deals with personally-identifiable information such as the full names and addresses of customers; engagement data, which is data that relates to how a customer interacts with a business’s social media pages, website, and other customer service routes; behavioral data, which includes information such as purchase history and product usage information; and attitudinal data, which includes data about how satisfied a customer is with a product or service, the desirability of products, and more. Identifying what kind of data they want to collect is an important first step for businesses looking to collect data that could help them improve their product or service offering. 

What Are Some of the Uses of Raw Data?

While unprocessed data may not be as useful to businesses as processed data, there are still several ways in which it can be used by businesses for a range of purposes:

Using Raw Data for Fraud-Detection

One of the most common uses of raw data is as source data for anti-fraud algorithms. Fraud-detection algorithms typically use raw data such as timestamps and the number of cookie occurrences to detect fraudulent activity on websites, or to detect whether or not a visitor to a website is a physical person who is a bot (also called non-human traffic). Raw data can also be used to detect duplicate transactions and even amounts, as well as calculate the ratio for key numeric fields.

Profiling and Customizing Customer Profiles

Data can give businesses key insight into their customers that they would otherwise not have access to, and raw data is especially useful when it comes to profiling customers so that businesses can better understand how to market to those clients to improve their engagement. Raw data is often used to help businesses create customized customer profiles based on data such as their physical location or gender.

Raw Data Can Offer Broad Insight into Client Behavior

Having access to raw data rather than processed data can be a boon to companies who are looking to explore previously unseen links or patterns in aspects of their business such as their customers’ buying habits. For example, a data analyzer looking for data on their customers’ buying habits may look at the link between the number of times a person visits a website, versus how often they purchase on that site in order to offer insight into how those two sets of data are related. However, by exploring the raw data attributed to that customer, a data analyst could find that there is also a correlation with another set of data, such as the time of day that a person visits the site or even where the customer is accessing the website from, that could also be used to generate more engagement.

How Can Companies Refine Raw Data into More Targeted Data?

While raw data is an essential tool for businesses, being able to take raw data and refine it into targeted data is an important step that businesses need to undertake to get the most value from the data as a whole. Data processing offers businesses a way to translate raw data into usable information or insights that can be used to improve the business overall. While having access to a person with a degree in data science can help with data processing and analysis, thanks to advances in technology, the tools to transform data into valuable insights are now available to all business owners regardless of their qualifications.

Free Online Data Processing Tools

When it comes to data analysis and visualization, there is a huge variety of free tools that are available to businesses who are looking to capitalize on the insights that their raw data can provide. A good example of a popular tool that can be used to visualize data is Data-Driven Documents, a free tool that can be used to manipulate documents based on data provided by the user.

Another popular free visualization tool is WebDataRocks, a JavaScript-based tool that helps users accurately and efficiently display data from CSV and JSON files (file formats typically used for the storage of raw data). WebDataRocks also gives users access to an enhanced web reporting experience that allows for the creation of reports based on the raw data supplied to the tool as well as data analysis features that can help make web reporting easier for businesses.

Paid Data Processing Tools

While free tools can offer businesses access to various tools to help them transform their data into usable formats, there is also a bevy of paid software options that can be used for everything from storing raw data, to analyzing it, to creating predictive models that can help give businesses valuable insight into their data, and much more. For example, software such as Alteryx can help businesses combine data from multiple sources to perform predictive, spatial, and statistical analysis on raw data to improve easily allow users to find, manage, and understand the analytical information related to their organization.

For businesses looking for software that can help them better understand their data to use it to design and implement better workflows, the KNIME Analytics Platform offers users access to several intuitive tools that can help blend and shape data as well as create machine learning models that can be used for many different purposes within the organization. KNIME also includes visualization tools and summary statistic tools that can help businesses share the valuable information they have gathered from their raw data with stakeholders in a variety of file formats.

Data is an essential tool for businesses and being able to leverage data can help business owners take their offering to the next level. Raw data is a vital component in this entire ecosystem and knowing how raw data can be transformed into usable information will help businesses get ahead of their competition and succeed in a competitive world.