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How can Third-Party Data Provide Assistance in Data Analysis
Data science industry is growing by leaps and bounds. Almost all the companies across industries are leveraging this technology for improved performance and to provide an excellent customer experience. The internet and digital evolution have added to the popularity of data science technology by expanding the availability of data sources.
Big data comprises two major components: first-party data, which is the information gathered by the company that intends to use it, and third-party data, which is gathered from other vendors. While the first-party data are valuable for an organization, the importance of third-party data cannot be neglected as it provides an added advantage to the company and its stakeholders. Third-party data can be an effective tool for the data scientists, as it helps them to make an effective predictive model. Here are a few examples of third-party data sources and the ways in which it can help multiple entities:
Mobile data: Mobile data is the most significant source of third party data as all of us are tethered to our mobile phones. Mobile data provides valuable insights into a customer’s behavior. Mobile service providers can track a customer’s shopping behaviors and locations. It can help retailers to have insights into a customer’s interest for a specific product. Mobile devices act as pseudo loyalty cards. The only concern is the issue of data governance and transparency in asking consent from the consumers.
Weather data: weather data can help the retail industry to display products based on a weather report — for example, the sale of umbrella surges in a monsoon season. It can be a great marketing tool, as store traffic can be predicted according to weather conditions.
Internet of Things data: Internet of Things data can be used by many business applications. For example, wearable technology devices collect data about bodily reactions, which can be used by healthcare companies for efficient healthcare services. It can also be used to predict machine defects and maintenance issues.
Telematics: The proliferation of telematics has increased third-party data sources. Telematics devices in cars can observe and record driving behaviors, which is used by insurance companies during claim processing.
Social media platforms: individuals leave their digital footprints while they use multiple social media platforms. It can be an excellent tool for third-party data if the practitioners adhere to governance protocols.