February 22, 2022
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.
Simply put, a data source is exactly what it sounds like—a source of data, may it be a computer file, a database, or a web service.
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.
Data source examples: computer file, database, web service, etc.
Data sources can assume broader or more specific meanings in different contexts (i.e., primary and secondary vs. file data sources and machine data sources). In this article, we will focus on the primary and secondary data sources.
Primary data is generated by the company itself through questionnaires, surveys, interviews, and so on. Gathering primary data is useful for tackling a specific problem at hand and receiving elaborate answers.
Secondary data is generated by someone else and then can be extracted and used for specific purposes. Sources of secondary data can vary widely from government institutions to websites, books, and articles.
It can be further classified into internal and external data.
Internal secondary data comes from historical records that have already been collected by the company. It usually lies in the CRM platform and consists of your customer data, transactions, and other customer records.
Also known as public web data, external data is mostly publicly available information that cannot be found in your company's CRM platform. It's usually collected either manually or via data providers.
Collecting data on your own might seem cheaper but in the long run, it takes too much time, rendering it cost-ineffective. Furthermore, manually prepared data might result in a breach of data quality which will bring additional distress.
As a result, confiding in a trustworthy data provider, such as Coresignal, allows you to gather fresh and relevant data quickly without worrying about data quality issues. Everything is taken care of and all you need to do is use it to improve efficiency and reach business objectives.
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 before basing decisions on it. Although it is not always easy to make sure that the data used conforms 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 consulting multiple providers, you should select one that offers fresh, relevant, and high-quality data.
Relying on data providers
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.
For example, Coresignal offers three different API solutions: Company API, Employee API, and Jobs API. Also, if you need to get the freshest data possible, you can utilize our Company scraping API, Employee scraping API, and Jobs scraping API. The options are abundant, all you need to do is choose what you need.
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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.
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. To put things in perspective, a total of 90% of the world's data was generated during the period of 2016-2018 alone.
Sourcing data offers multiple benefits for your operations.
- Big data analytics allows measuring every aspect of internal and external environment. The knowledge that comes with data analysis turns to competitive advantage and opportunities for new daring decisions in business management.
- 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 survey has shown that in 2021 B2B marketers were 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 source data skillfully and unleash its maximum potential, it is suggested to follow the best data sourcing practices routinely. As sourcing data has become such an important part of modern business, a lot of useful knowledge about it has been accumulated.
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.
Data collected manually is liable to breaches, inconsistencies, and duplication. Even worse, one mistake is all it takes for your data to contradict actual data. Data quality issues should not be taken lightly.
If you have the ability, you should always buy data from professional sources. After all, low-quality, inaccurate data can potentially cost you more than investing in a data vendor.
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 admits 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. Implementing sophisticated data security measures is required to prevent unauthorized access and ensure that sensitive information remains protected and unbreached.
Hopefully, with international communities employing their greatest legal minds to solve the legal issue and the greatest computer scientists for security, these challenges will be mitigated as much as possible in the near future.
Data sourcing, if once it was the professional interest of only programmers and data scientists, now is at least part of most entrepreneurs’ professional interest. It can greatly improve business intelligence, decision-making, and even allow you to create a useful data warehousing project for later use that could help you with both everyday decisions and long-term business strategies.
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.
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