With the constant need for faster insights and analytics, many companies have started to adopt change data capture (CDC) for their data replication needs. Large enterprises spanning transportation and logistics, manufacturing, financial services and more have embraced CDC solutions to efficiently replicate data from their on-premises databases to their cloud destination of choice. CDC ensures the freshest data from a variety of sources are always available in the destination for analytics. Companies like JetBlue and World Fuel Services leverage real-time CDC to keep their operations running smoothly.

Even with advancements in CDC technologies, many companies still struggle with fast, efficient and accurate data replication. Whether you're a retailer who needs to optimize your supply chain or a financial firm looking to detect fraud, CDC ensures that the right information gets to the right place in near-real time. Some of the benefits of CDC solutions compared to traditional batch loading are greater accuracy, faster replication and heightened security protocols all while saving costs and using fewer resources.

If your data team is facing pressure to do more with less in today’s current economic conditions or you’re looking for a more efficient and effective way to scale data projects, CDC is your best option. Here's a closer look at how CDC can increase your data team's efficiency while offering an accurate and reliable way to turn your data into valuable business insights.

[CTA_MODULE]

Achieve fast and accurate log-based CDC for databases

Organizations need an efficient way to process data that will have a low impact on their business operations to ensure maximum uptime and minimal resource constraints. One method of CDC replication, log-based, parses the changes from the transaction log asynchronously which provides a low overhead, high-performance way to capture every single data change — regardless of data volume.

Log-based CDC replicates changes to the destination in the order in which they occur. This allows for capturing changes as they happen without bogging down the source database due to resource constraints. The data can be replicated continuously in real time rather than in batches at set times that could require significant resources.

Improve data replication efficiency

CDC makes extracting, loading and transforming data into a data warehouse or data lake environment more efficient. For example, 1-800-Flowers.com, Inc. is a chain retailer that features a family of more than a dozen brands, including Harry & David®, and The Popcorn Factory®, among others. With such a large brand portfolio, the enterprise leverages Fivetran's high-volume CDC replication solution to import and integrate data across many different sources into Snowflake, its cloud-based data warehouse.

This consolidation of customer and transaction data enables 1-800-Flowers to have consistent reporting across their business and deeper analytical insights that help the organization gain a better understanding of its customers.

Another company that has seen increased efficiency in its data processes is Redwood Logistics, a third-party logistics and transportation management firm. Its homegrown solution could only load data once per day via batch processes without impacting critical source systems. Worse still, the solution regularly had replication failures and became a massive maintenance burden.

When Redwood Logistics deployed Fivetran's log-based CDC solution to replicate data from its on-premises SQL databases to Snowflake, they were able to access and process more data in a timely manner. They can now quickly supply custom, feature-rich data dashboards to internal customers, so business leaders can better track their business metrics. But most importantly, Fivetran helped free up Redwood’s data engineering team to spend more time on value-add projects rather than building and maintaining data pipelines.

Fresh data for accurate and insightful decision-making

CDC captures and replicates only the changes made to data in the source system, rather than replicating the entire dataset. CDC is more efficient and faster than other data replication methods because it only replicates the data that has been updated or inserted. This is especially important in cases where the source system is large and the volume of changes is high, as it reduces the amount of data that needs to be transferred and processed.

With data in the destination always up-to-date, decisions can be made quickly and accurately. CDC is a robust and reliable data replication solution compared to other methods because it can automatically resolve replication issues without manual intervention. This ensures that the data in the destination is always consistent, which is essential for accurate and insightful decision-making.

JetBlue uses Fivetran's log-based change data capture to replicate aircraft maintenance data from its legacy systems and on-prem databases to Snowflake. This data consolidation has allowed JetBlue to progress towards predictive aircraft maintenance, which will improve efficiency and cost savings while also preventing mechanical issues that could shorten the overall lifespan of a part or machine.

Lower your costs while scaling your data initiatives

Another key benefit of CDC is that it is an affordable way to replicate data. CDC allows companies to combine data from disparate sources and empower their data analytics and visualizations.

Autodesk, a construction software company, had analysts building and maintaining pipelines that was consuming a significant portion of their time. Any schema or API changes would cause pipelines to break and require individual attention to fix. By transitioning to Fivetran, Autodesk was able to free up analysts’ time and combine their data movement into a singular platform. Autodesk has seen time and cost savings due to automated schema drift handling, reduced run times and warehouse right-sizing. 

Do more with less

Using a CDC replication method like Fivetran, you have faster access to data to help solve critical business problems. This ultimately allows you to increase the output of your data-driven initiatives and decision-making, save on costs and operate leanly and efficiently to empower your enterprise’s data needs.

[CTA_MODULE]