In a data-driven economy, enterprises can hardly afford to base their decisions on outdated data. Competitive advantage is a function of real-time, accurate data. As companies start through a data evolution, they’re moving quickly from batch processing to real-time streaming architectures.
One major driver of this change is Oracle CDC (Change Data Capture), which empowers Oracle database users to capture and replicate data changes perpetually on a constant basis. This power changes the way enterprises control data, produce analytics, and make business decisions.
Learn more about how Oracle CDC is driving the data flows and synchronizing the advanced data architectures of its implementation, and how to choose the right tool.
Historically, most companies used batch Extract, Transform, Load (ETL) pipelines to transfer data between systems. These pipelines ran periodically — every hour, daily, or weekly — inducing some latency between the time data was changed in operational systems and the time that the insights from it would be available.
Today, this practice is inadequate for creating new business value quickly enough.
To mitigate this problem, Oracle CDC detects and captures changes (inserts, updates, and deletes) the moment they occur in the Oracle databases. The changes are then delivered in real-time or near real-time to downstream systems, which results in timely insights and operational agility.
Companies no longer have to wait for the next ETL cycle. Instead, they can query new data within their analytics platforms and data-driven apps in real time.
Some of the benefits that companies would be able to access after the implementation include:
- Real-time BI and analytics: Give people dashboards and reports that are up-to-date and actionable.
- Improved customer experience: Provide better contexts for the interaction by knowing who and what the conversation is about.
- Fast fraud detection: Spot anomalies and fraud as it occurs.
- Modernize data pipelines: Reduce architectural complexity by changing heavy ETLs into lightweight CDC-based streaming pipelines.
- Lower operational costs: Reduce infrastructure and maintenance costs by eliminating heavy ETL workloads.
Learn more about what Oracle CDC does and how it can supercharge the data infrastructure in real time.
Cloud-native data platforms gain popularity for advanced analytics, machine learning, and AI. Many organizations are now building or migrating their data and analytics workloads to the cloud. This will need a perpetual supply of new data to maintain accuracy.
There arecritical features that make this transition possible by synchronizing changes from an Oracle database with:
- Cloud data warehouses like Snowflake, Amazon Redshift, and Google BigQuery
- Amazon S3 and Azure Data Lake-based cloud data lakes
- Real-time stream processing frameworks and platforms
It opens up operational data that is held hostage in transactional systems so companies can tear down data silos and get a single view into enterprise data.
It guarantees that the data pipelines are lightweight, efficient, and scalable — essential features for powering today’s data-hungry applications.
Contemporary business intelligence platforms demand real-time data access. It ensures that updates in Oracle transactional systems are accurately reflected in the BI dashboards and reports in real time, so companies can make informed decisions more quickly.
Organizations that are creating centralized data lakes can use Oracle CDC to accomplish low-latency Oracle-to-cloud data lake increments. This is the foundation for advanced analytics, data science, and AI/ML.
As companies migrate from legacy data warehouses to cloud-native, it provides a smooth transition that new cloud targets need by synchronizing Oracle databases with them. It is possible to avoid the processing delay in batch processing, and the time to data availability becomes very short.
Learn more about Oracle CDC & how it can enable the data modernization and cloud migration projects.
Operational reports are frequently based on transactional data that must be up-to-date and correct. It enables enterprises to replicate changes to their reporting databases synchronously, enabling near real-time operational visibility, which can be used to support an agile, more responsive business.
Reasons why ETL is now an outdated approach:
- Two-stage ETL pipelines add latency, are overly complex, and are hard to manage.
- There are many better alternatives.
- Streaming data replication: Data is constantly being streamed to target systems.
- Reduced architecture: There is no need for complex ETL pipes to construct heavy.
- Reduced operating complexity: No big batch jobs to manage or redundant processing.
- Better performance: Log-based capture adds no noticeable overhead to production databases.
- Seamless integration: Natively integrates with contemporary data platforms and cloud services.
All CDC tools are not equal. Companies should take into account the following factors when searching for a solution:
- Performance-optimized log-based CDC
- Infallible data consistency and integrity
- Powerful interoperability with today’s cloud data platforms
- Strong monitoring and alerting options
- Supported for schema change and metadata changes
BryteFlow is one of the most cutting-edge answers out there now. It is a fully automated and end-to-end replication with built-in data comparison for change data validation. It lets businesses create data pipelines easily and at speed, without the need to code or spend hours manually building them.
With fast incremental loading and continuous synchronization, it assists in modernizing the data architecture without disruption to operations.
In conclusion, for business, real-time is now a must-have in today’s competitive environment. Oracle CDC lays the groundwork for organizations that want to build real-time data architectures to support modern analytics, AI/ML, operational intelligence, and cloud migration efforts.
Bringing scalable, low-latency data replication worldwide, it allows enterprise customers to exploit their data sets across cloud, hybrid, and on-premises deployments, opening the door to new possibilities for innovation and flexibility. With the increasing need for up-to-the-minute data, it isn’t simply a technological choice.