Data Synchronization and Replication: What’s Batch Got to Do With It?
This article is the first of a two-article series that discusses an API-Led data synchronization and replication approach using MuleSoft.
Today’s enterprises are highly segmented, as different parts of the organization use data and tools from various vendors to achieve their goals. This segmentation has led to a proliferation of data sources and data repositories, as multiple systems become necessary to support a growing company. However, as we've discussed previously, maintaining data integrity across the enterprise has lost none of its importance even as the challenge has multiplied. Timely access to accurate data is more crucial than ever to every aspect of a business, companies must accurately and efficiently disseminate the data they are collecting.
Achieving this requires a cohesive solution, combining both data synchronization and replication. Various data sources may feed into multiple applications and tools, and these repositories of data must be kept synchronized. If this synchronization falters, system users will be unable to make use of the data collected in different segments of the enterprise, or, even worse, they will be making business decisions based on incorrect data. An effective data synchronization solution is usually implemented with an event-driven architecture that is best suited to handle incoming data immediately.
Unfortunately, data synchronization is only half of the story, and event-driven architecture struggles with replicating entire data sets. When a new instance is created, a new application comes online, or a significant update is made, it is often necessary to replicate existing data over to the new system. A solution based on synchronizing new data often lacks the tools to handle this task. Without an answer to both problems, companies pay the price in the form of errors, data quality, and, eventually, a lack of trusted data. The USGS estimates the cost of poor data quality as between 15 and 25 percent of a company’s operating budget.
Fortunately, MuleSoft provides powerful tools for both event-driven data synchronization and large-scale data replication. MuleSoft’s API-led connectivity philosophy lends itself exceptionally well to data synchronization through an event-driven architecture. At the same time, MuleSoft’s Batch Scope provides the parallelization necessary to handle data replication through ETL operations on entire data sets.
API-Led Connectivity and Data Synchronization
A solution for data synchronization across an entire enterprise requires significant flexibility. The solution must be able to cope with new sources of data and new consumers of data regularly. This means that point-to-point designs will quickly become unmanageable, as adding new direct connections between each source and sink will create an ever-growing burden on IT. Instead, the focus should be on creating a way for data sources to expose the data they provide efficiently and on building replicable tools to synchronize data exposed in that manner quickly.
It's easy to see how API-led connectivity can be of use here. For example, building an API in front of a central data repository significantly simplifies loading data from multiple origins. Whenever a new data source comes online, developers can leverage previous work in calling this API to streamline the process.
Furthermore, the developers don’t need to understand or adapt to the central data repository changes, as those changes will only require updates to the API implementation. The API will present a consistent interface to its consumers while internally handling the central repository's modifications. This straightforward implementation helps decouple the applications, preventing scenarios where the central repository cannot be modified without extensive changes to every process serving data to it.
As another benefit, abstracting your data repository behind an API helps create and adopt canonical data models. Canonical data models reduce complexity and boost productivity, as developers stop needing to account for varying data types throughout the enterprise.
Why MuleSoft for Data Synchronization and Replication?
Several factors make the MuleSoft Anypoint Platform the tool of choice to build this kind of structure. The API-led model is built into the fabric of Mule 4. Indeed, Mule 4 contains a wealth of features to enable users to build potent APIs. The three biggest differentiators are Anypoint Connectors, DataWeave, and the Anypoint Platform.
Anypoint Connectors jumpstart the process of building APIs that connect to various applications, whether on-premise or in the Cloud. These Connectors reduce the upfront development effort while also serving as the basis for reuse in your organization.
DataWeave shines in transforming data and taking advantage of canonical data models. The flexibility of DataWeave is unmatched in handling varied data formats and input and target schemas, which is essential for easy synchronization.
Anypoint Platform provides reliability and security, with easy deployments through CloudHub. More importantly, in Exchange and API Manager, Anypoint Platform gives organizations the tools to monitor and manage their APIs. The most significant benefits of an API-led approach are realized when assets are easily discoverable and reusable. MuleSoft gives you the tools to make this happen out of the gate.
ADOPTION & EXPANSION
+ Number of APIs
+ Business coverage
+ Number of contracted apps
+ API usage
+ API reuse
EFFICIENCY & COST SAVINGS
+ Number of APIs in each SDLC stage
+ Time spent in each SDLC stage
+ Cost and time to build an API
+ App development velocity
+ Number of launches per year
+ Number of defects
SECURITY & VULNERABILITIES
+ Security violation
+ Policy enforcement
+ Time since the last version was published
+ Number of throttling issues
+ Time to onboard
+ Number of deployments
+ Number of incidents
+ Percentage of customers impacted. per incident
+ Time to resolve incidents