Why you need a data integration platform

Data doesn’t sit in one database, file system, data lake, or repository. Data created in a system of record must serve multiple business needs, integrate with other data sources, and then be used for analytics, customer-facing applications, or internal workflows. Examples include:

• Data from an e-commerce application is integrated with user analytics, customer data in a customer relationship management (CRM) system, or other master data sources to establish customer segments and tailor marketing messages.
• Internet of Things (IoT) sensor data is linked to operational and financial data stores and used to control throughput and report on the quality of a manufacturing process.
• An employee workflow application connects data and tools across multiple software-as-a-service (SaaS) platforms and internal data sources into one easy-to-use mobile interface.

Many organizations also have data scientists, data analysts, and innovation teams who increasingly need to integrate internal and external data sources. Data scientists developing predictive models often load multiple external data sources such as econometrics, weather, census, and other public data and then blend them with internal sources. Innovation teams experimenting with artificial intelligence need to aggregate large and often complex data sources to train and test their algorithms. And business and data analysts who once performed their analyses in spreadsheets may now require more sophisticated tools to load, join, and process multiple data feeds.

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