A data source is a location that data originates from. For business purposes, this is any data you use within your organization. Where does that data come from? That is the data source. When you’re dealing with data management or data integration, it helps to understand the definition of data sources to maximize the effectiveness of your business data.
Data Sources: What You Need to Know
What is a data source in simple terms? As noted, a data source is any location that provides data relevant to your needs. As a business, your data sources could be on-premises, off-site, or in the Cloud.
Sometimes, the data source is the creation point of the data. This could be an online source at which you digitalize and upload physical data. Examples of physical data include photos, forms, videos, and audio digitized for streaming or transfer purposes.
A source of more refined or manipulated data that’s transitioned through multiple sources could still classify as a data source if that’s the only location you retrieve the data from.
Examples of data sources include various databases, such as business devices with flat files or IoT devices like smart bulbs or wearable tech.
To understand why data sources are important, think about this: A music fan is buying concert tickets online. The website has to tell the customer which tickets are available and which are sold out. This information comes from a database of tickets. Here, the database is the data source. The accuracy of that data and the reliability of the connection to that data source are paramount to a successful transaction.
Types of Data Sources
Data source, for our purposes, means any source of data relevant to your purposes. However, in certain other contexts, it may have a slightly different or more specific meaning. In various applications, the term "DataSource" may be a collection of data providing access to something via standardized means. In Java, the term DataSource only ever means something that represents the connection to a database. This is useful to know if you come across DataSources spelled this way.
Within data management, there are several types of data sources, and the number of sources available increases as technologies change and update.
Flat files are data sources that have no hierarchy. They are just single tables of information, usually with one record per line. Flat files aren’t as versatile as relational databases, but they take up less space, so they are still useful for some purposes. Some programmers use flat files for app creation or to transfer data into a relational database that can structure it more efficiently.
Apps and SaaS such as Salesforce, Bill.com, Stripe, QuickBooks, or Shopify all classify as data sources if you use them for your business. Many of these applications have their own APIs to allow ease of connection, while other data sources have a dedicated or user-defined data source name or DSN. Connecting to each data source individually is very time-consuming and may require a whole data management team. It's easier to manage data sources with data integration tools that allow simple, low-code manipulation of multiple sources across a range of locations and connections.
Data Sources and Data Integration
What else is a data source? It is the first step towards effective data integration for your organization. Understanding your data sources, where they are, and how to access them allows you to use a tool like Xplenty to bring all that data together in one location. You can then access and analyze that data using your chosen analytics platform—for example, Teradata or Tableau.
Why is it important to integrate all your data sources? Because you can, for example, review multiple sales channels to analyze the effectiveness of a marketing campaign. You can find out which blog posts are most read by tracking engagement and click-throughs to your website across social media channels or through your email newsletters. This empowers you to gather accurate reports based on the most up-to-date data, compare those results against previous weeks, months or years, and make business-critical decisions using insights not possible by manually monitoring individual data sources.
Xplenty is an ETL tool (ETL stands for Extract, Transform, Load). ETL tools create data pipelines between your data sources and your data destination, typically a data warehouse such as Amazon Redshift. If you’d like to learn more about how Xplenty can make the most of your business’s data sources, schedule a conversation with us and arrange a demo.