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In briefShow moreShow lessThe need for data platforms has increased over the past 10–20 years due to technological advances in data storage and processing.
- The need for data platforms has increased over the past 10–20 years due to technological advances in data storage and processing.
- A data platform enables flexible data architectures that can be adapted to a company’s specific needs and further developed over time.
- Retail chains can use a data platform to collect and analyze sales, customer service, and inventory data to identify trends and optimize operations.
- Operational databases handle fast transaction processing and show the latest available information, while data platforms store and analyze historical data over time.
- Data platforms make it possible to answer complex business questions about customer segments, campaigns, and in-demand products that simple operational databases cannot address.
The need to collect data in this way has grown over the past 10–20 years due to technological advances in data storage and processing. These advances have made it possible to build flexible data architectures that extend beyond the traditional data warehouse. Today, companies can tailor the technology to their specific needs and further develop the platform as new requirements arise.
For example, a retail chain can use a data platform to collect sales data from physical stores, e-commerce, customer service, and inventory. By analyzing this data, the chain can uncover sales trends, identify bottlenecks in inventory logistics, or optimize customer service across channels.
Key components of a data platform:
Although a data platform is similar to a traditional data warehouse, it often has more use cases and components. Here are the key components of a data platform:
The difference between a data platform and an operational database
An operational database and a data platform serve different purposes. Operational databases are designed to support rapid data entry and transaction processing. Examples of use include updating customer details or checking order history. The data stored here is often organized for quick retrieval and reflects the latest information.
A data platform, on the other hand, is used to store and consolidate data for large-scale analyses. For example, you can compare sales data from a geographical area over several years or combine sales information with social media data. The data platform stores historical versions of the data and builds a timeline, giving you both the latest version of the data and an overview of how it has evolved over time.
Why is this important?
A data platform enables businesses to leverage their data in ways that are not possible with simple operational databases. The platform can answer complex questions, such as how different customer segments respond to different campaigns or which products are most in demand during a given period.
If you are considering building a data platform or want to optimize your existing solution, we are ready to help you with professional advice and implementation.
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