Businesses striving to compete in today’s highly digitalized economies need stream data integration capabilities to accelerate growth and revenues while servicing customers more responsively and without compromising governance requirements. Next-generation infrastructures such as Cloud, IoT analytics, advanced analytics/ML, and real-time applications help to improve decision-making by harnessing the value of event streams. Businesses need to adopt technologies that allow stream data integration to identify and leverage valuable opportunities. Traditional batch processing technologies such as ETL cannot match the high volume and low latency requirements provided by real-time data streams.
Gartner defines SDI (stream data integration) as a data pipeline that allows ingesting, filtering, transforming, enriching, and storing the data in a target database or a file for running analytics later. In SDI systems, event records are not a static snapshot of data at rest but, rather, a continuous, unbounded sequence of data in motion.
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During data integration, event data is ingested from across the enterprise and made accessible to business users to improve decision-making in real-time for enhancing:
● Customer experience
● Minimizing fraud
● Optimizing operations and resource utilization
4 Use Cases of Data Integration Platform
Forward-looking enterprises will find streaming data integration useful for:
● Data modernization
● Real-time insights
● Operational analytics
● Digital customer touchpoints
Use Case #1: Data Modernization with Cloud Adoption
One of the first steps to modernizing operations and data & analytics solutions is cloud adoption. It begins with the migration of the on-prem database to the cloud and must be performed without disruption to the business. Streaming data integration in Striim enables this through the Change Data Capture (CDC) feature. All new transactions are captured as they happen, without pausing operations, and loaded to the cloud database once the on-prem database is loaded and ready.
Not only at the time of migration, but this feature facilitates even the bi-directional movement of data or cloud to cloud integration without interruption.
Use Case #2: Real-Time Insights
A wizard-based UI and SQL-based language in Striim allow users to develop real-time applications quickly and easily using stream data integration pipelines. Visualization and analytics on the data can be performed while it is in motion, even before the data is delivered to the target, using Striim’s SQL-based streaming analytics.
Use Case #3: Operational Analytics
Striim’s stream data integration capabilities allow users to derive operational intelligence by leveraging data from a variety of sources in real-time. The pre-processed in-flight data is delivered in a consumable format, accelerating downstream applications and providing insights into operations. Smart data architecture is made possible by stream data integration, with only necessary data that serve the end-user purpose being stored in a consumable form.
An elaborate use case of striim services: Striim-Powered Real-Time Data Integration of Core Banking System with Azure Synapse Analytics
For businesses with hybrid cloud architecture, streaming data integration connects the cloud database to enterprise-wide systems and makes it a natural part of the data center. It facilitates continuous real-time data movement from databases, log files, machine data, and other cloud sources, sensors, and messaging systems to transform cloud workloads into operational workloads.
Striim also helps to create machine learning models that continuously deliver training files to the analytics environment by extracting and pre-processing suitable features. This can be brought to Striim using the open processor component, which facilitates operational decision-making by implementing ML logic to streaming events for gaining real-time insights. Monitoring the fitness of the model and fully automating it through retraining are also possible.
Striim Platform’s Core Capabilities and Benefits
Some of the core features of the Striim platform that enable the above use cases for streaming data integration include:
● Collection of Continuous, Structured, and Unstructured Data: Real-time data of all types is gathered from multiple sources on the Striim platform. These include databases (using low-impact change data capture), log files, cloud applications, IoT devices, and message queues.
● Stream Processing Using SQL: Striim uses static or streaming reference data for applying filtering, transformations, masking, aggregations, and enrichment.
● Monitoring and Alerting Pipelines: Striim enables the real-time visualization of data flow and content while offering delivery validation.
● Real-Time Delivery: Streaming data is distributed in a consumable form to all major targets such as Cloud environments, messaging systems including Kafka, Hadoop, flat files, and relational and NoSQL databases.
You might be interested in: Multi-Cloud Data Pipelines with Striim for Real-Time Data Streaming
Some of the key advantages of the Striim streaming platform for unified data integration include:
● Streaming data integration with intelligence using an in-memory platform
● Movement of real-time data across on-prem and cloud environments
● Low-impact CDC for Oracle, HPE NonStop, SQL Server, and MYSQL
● SQL-based in-flight filtering, transformation, aggregation, and enrichment
● drag-and-drop UI for quick deployment and easy integration
● Continuous monitoring of data pipeline and built-in delivery validation
● Can integrate with existing technologies and open source solutions
Indium – Striim Partner to Enable Data Integration
Streaming data integration in Striim acts as the backbone for an enterprise’s data fabric that breaks down data silos and enables the building of an agile and global data environment for tracking, analyzing, and governing data across environments, applications, and users.
Indium is a Striim partner that facilitates connecting legacy and modern solutions to deliver real-time data through intelligent pipelines. It builds a flexible and scalable data integration backbone that connects data from hybrid and multi-cloud environments.
With real-time data integration, organizations can improve the digital experiences for customers through increased responsiveness and customization. Indium facilitates a bespoke development of Striim streaming platform for unified data integration to help businesses leverage their data for enhancing their customers’ digital experience.