Coresignal logo
Back to blog

Data Sourcing: Benefits, Source Types, Providers, Challenges, and More



June 07, 2021

Contemporary business is inseparable from data and data technology. Multiple types of data are being utilized for various business purposes. In order to get the information they need, companies must turn to many different data sources. Broadly defined, a data source is any location where the data which the company accesses originates or is located. Data sourcing is a crucial part of modern business that enables firms to get the informational assets they need.

What is data sourcing?

Data sourcing is the process by which companies extract and integrate data from multiple internal and external sources. This procedure creates the firm’s data infrastructure that is used for handling daily workflows and achieving various business objectives. As such, this process is an integral part of doing business in the heavily data-based markets of today.

Sourcing data in the age of information

The world now is more connected than ever before due to the growing reach of the internet and numerous devices capable of sharing and storing information. This connectivity has formed the current business landscape in which data occupies the central spot.

Companies were keen on adopting big data analytics because it allows them to measure every aspect of business, major or minor. The knowledge that comes with it turns to competitive advantage and opportunities for new daring decisions in business management.

Naturally, data sourcing is a pivotal procedure that allows companies to get the information they need in the correct conditions. Different companies and financial firms have varying data sourcing purposes. These include such objectives as portfolio management, lead generation, designing marketing and management strategies.

Data sourcing is especially important for B2B marketing and sales. In fact, a recent survey has shown that in 2021 B2B marketers are making database acquisition and data quality their top priority, as the percentage of marketers lacking database strategies went down from 50% to 28% in a year. The main explaining factor behind such increased attention to data sources has to be the value that skillful sourcing of information brings to B2B marketing.

As data is crucial both in finding leads and in preparing the sales approach, it comes as no surprise that B2B sales require thorough research. And since there is more to know about firms than most companies are able to gather on their own, multiple sources are often employed for data collection.

To execute data sourcing skillfully, and unleash its maximum potential, it is suggested to follow data sourcing best practices routinely. As sourcing data has become such an important part of modern business, a lot of useful knowledge about it has been accumulated. Below are 5 things worth noting when carrying out this procedure.

Types of data sources

As “data sources” can assume broader or more specific meanings in different contexts, there are multiple ways to classify them. For example, from the company’s perspective, they could categorize them into internal and external sources. Specifically, going from the largest to the smallest types of sources, such as a database, a computer file, a specific device that records data, etc. However, the most common way to classify most data source types is into two major categories – machine data sources and file data sources.

Machine data sources

These are the kind of sources that, as the name will tell, are in one sense or the other machines. In other words, machine data refers to the data that originates or is stored in the device that is being used or connected to. This type of data is harder to share than file data, but to access the data stored on a machine, users would refer to the Data Source Name (DSN), which serves as a shorthand for the file location information.

File data sources

As opposed to machine sources, file data sources are easy to share, copy and move between different devices. These are the sources for data that is stored in a single computer file. Each computer file stores connecting information for a particular source. Sources of this type are not assigned to particular systems or users and can be accessed simultaneously by many users.

Benefits of data sourcing

As there are many purposes for which data sourcing is used in business, there are also multiple benefits. It allows companies to improve their lead generation and enhance the quality of leads, as leads are nothing but data gathered from particular sources. Additionally, sourcing data improves the efficiency of the workflow that requires data and data analysis. 

Furthermore, it enhances decision-making both in strategizing and company management as well as in investing. Finally, sourcing information improves sales conversion rates and allows sales personnel to concentrate on actually selling instead of devoting time to the additional gathering of information.

Data providers for outsourcing alternative data

Where there is demand, supply is soon to follow. In contemporary business, there is a large demand for data. These are perfect conditions for the proliferation of data suppliers. From the sourcing perspective, choosing a data provider is a lot about accessibility options that are offered. Many providers will allow accessing their data through APIs in which case it is advisable to look at the filtering solutions offered. The best providers will also offer convenient data formats suitable for the data being shared.

Additionally, it is always good to look for providers that offer many different data types collected from multiple sources. This will ensure diversity and multiple utilities of the sourced data. For these reasons, Coresignal is a great B2B data provider that can conveniently access and share various data types. 

Prioritizing data quality

Data quality has to be included among the factors by which to choose the right provider. Generally, when talking about acquiring and utilizing data to its full potential, quality is the key. On the one hand, various statistics show the multimillion-dollar cost of poor data quality and, on the other, that companies still struggle to ensure that the data they use is of optimal quality.

Thus, when sourcing data, quality must be prioritized. Companies should look closely at metrics such as the age, consistency, and validity of data should be scrutinized as much as possible. Although it is not always easy to make sure that the data used conform to high-quality standards. But there are still some things one can do. For example, data suppliers can be asked about data gathering methods and the age of data. And, of course, after trying multiple providers, those whose data show signs of the highest quality should be preferred.

Data sourcing challenges and concerns

Uneven quality in itself is one of the challenges of data sourcing that could be mitigated in the ways mentioned above and constant quality control efforts. Another major group of challenges is the legal rules of data management. Business is an increasingly global phenomenon, with international markets opening up more and more. And digital data admit no state borders. Yet, data governing still lacks the global character that would suit the contemporary business reality, with guidelines varying in different states or regions.

Security of sensitive information is another challenge related to the aforementioned. Hopefully, with international communities employing their greatest legal minds to solve the former issue and the greatest computer scientist for the latter, these challenges will be mitigated as much as possible in the near future.

Summing up

If once it was the professional interest of only programmers and data scientists, now data sourcing is at least part of most entrepreneurs’ professional interest. As always, when data is in question, the key things about sourcing are related to the quality, accessibility, and diversity of the data. All these aspects come down to choosing the right provider and getting the most value of the data that is used.

Frequently asked questions

What are different types of data sources?

Depending on the context, there are multiple ways to classify data sources. However, two major relevant types of sources are machine data sources and file data sources.

What is an example of a data source?

For example, suppose a company is selling B2B. In that case, it may have acquired from a provider a CSV file with tabular firmographic data such as age, size, and revenue of companies in a particular geographical area. In this case, the CSV file is our data source.

What is the purpose of data sourcing?

The general purpose of data sourcing is to get valuable and useful information. Businesses utilize it for lead generation, competitive intelligence, market analysis, and many more.

What is the difference between data source and database?

A database is a type of a data source, whereas a data source is the more general term that encompasses many different types of data sources.

Related articles


October 13, 2021

A Quick Guide to Data Redundancy

Data redundancy, which involves the storage of the same data in multiple separated places, isn’t always a bad thing. But it is...

Read more


October 11, 2021

Understanding Market Segmentation: Benefits, Importance, and Use Cases

Many business professionals tend to overlook market segmentation. This concept refers to dividing the target market into clusters...

Read more


October 08, 2021

A Guide to Alternative Assets: Benefits, Sources, Methods, and More

Alternative investments or assets are all tradeable goods that are not stocks, bonds, or cash. This means that aside from these...

Read more

Coresignal's fresh web data helps companies achieve their goals. Let's get in touch.

Contact us

Use cases


Coresignal © 2021 All Rights Reserved