Businesses are faced with an unprecedented number of data sources that drive their day-to-day operations. From structured data sources like ERPs, CRM, and relational data stores to unstructured data such as PDFs, images, and videos, enterprises are confronted with the daunting challenge of keeping up with their ever-expanding data ecosystem.Â
To muddy the waters further, how businesses access their data is inconsistent across sources, from APIs to databases, data streams, and more. Data teams are now tasked with designing and maintaining scaleable, flexible data architecture to support a wide variety of business-critical data-driven reports and analytics.Â
In this blog, we’ll explore how Fivetran delivers business value by automating many of the headaches data teams deal with daily, giving them more time to focus on innovation, strategic initiatives, and driving business growth.
What Business Challenges Does Fivetran Solve?
At phData, we’re lucky to work with a wide range of customers spanning multiple verticals to solve their toughest data and AI challenges. During our work, we’ve helped many customers leverage Fivetran to solve several important business problems. Below are a few of the most notable examples we’ve come across and how Fivetran helps bring value back to our customers.Â
Designing New Data Pipelines Takes a Considerable Amount of Time and Knowledge
Designing new ingestion pipelines is a complex undertaking that demands significant time and expertise. Each data source comes with a variety of different criteria, including Change Data Capture (CDC) logic, authentication and authorization mechanisms, and error handling.Â
To further complicate matters, each data source will also have its own challenges around data volume and velocity. Some sources might have strict restrictions around API limits; others may be extremely inefficient if parallelism is not designed or implemented poorly, costing organizations time and money.Â
On top of all these problems, engineers will need to design custom logging and monitoring to ensure their pipelines are running correctly and errors are being handled as expected.
How Fivetran Solves This Challenge to Drive Value
Fivetran offers connectors for various common and uncommon data sources and can ingest structured, unstructured, and even streaming data. Rather than building custom architecture from scratch, data teams can leverage the Fivetran connector network with over 500 managed connectors (and that number continues to grow)! This can significantly expand the scope and capabilities of an engineering team as new sources can be added with just a few clicks.Â
This streamlines the data ingestion process as engineers are no longer required to learn the intricacies and nuances of their data sources but rather leverage Fivetran to manage and maintain this custom logic.Â
With this level of flexibility, organizations can focus on their data-driven goals rather than worry about growing technical debt by adding new sources.
Custom Data Integration Solutions Demand Time from Engineering Teams to Maintain
As the number of data sources expands, engineers must grapple with the growing nightmare of change management. Engineering teams must maintain a complex web of ingestion pipelines capable of supporting many different sources, each with its own intricacies.Â
Supporting these data pipelines and ensuring they remain stable can take up a large chunk of time that could be spent progressing the organization’s goals.Â
With all of this development, code will need to be maintained with good DevOps practices in order to ensure changes to the architecture do not result in downstream failures.
How Fivetran Solves This Challenge to Drive Value
Fivetran automates many headaches associated with maintaining ingestion architecture by providing a flexible solution for data teams to schedule their ingestion pipelines, monitor performance, and view outstanding errors and issues.Â
Fivetran also simplifies ingestion pipeline upkeep by automating the process of maintaining connectors. Should a data source have updates, from schema drift to API changes, Fivetran manages this infrastructure and automatically updates any connector an organization uses, thus reducing reliance on Continuous Integration/Continuous Deployment (CI/CD) practices.
Additionally, should a connector not be available for a data source, engineers can build their own connector. While custom code, this connector is completely managed from an orchestrational perspective by Fivetran, allowing data teams to view and govern all of their connectors from one centralized platform.Â
With their automated approach to data ingestion, Fivetran allows data teams to spend less time managing their data pipelines and more time on analysis and deriving insights for the business.
Simplify Data Governance Through Centralization
Further adding to the headache, data teams are also tasked with maintaining an architecture that meets their organization’s data governance and security standards. Some organizations may have data sources that contain Personally Identifiable Information (PII) and other sensitive information that cannot be moved without being hashed, anonymized, or outright blocked.Â
Other organizations might have strict data governance policies that delegate who can work on and maintain these data connections. While necessary, these challenges ultimately burden data teams when they must support custom data architecture that considers all of these varying requirements.
How Fivetran Solves This Challenge to Drive Value
Fivetran can provide required governance regarding data ingestion by delegating access to connectors and automatically handling PII, either by hashing this information or outright blocking it from entering the data platform. This provides data teams with a consistent solution to pipeline governance and data masking.
Organizations can also leverage Fivetran to centralize their data into one unified data platform. With all their data in one place, organizations can now build cross-functional reports with ease, enabling data-driven decision-making. Furthermore, now that data is centralized in one place, customers can leverage their cloud data store’s data governance features, many of which offer various options to secure and delegate access.Â
For example, the Snowflake Data Cloud provides Role Based Access Controls (RBAC) that allow administrators to explicitly deny or allow data consumers access to specific tables, columns, schemas, and more. This comprehensive approach to data governance empowers organizations to maintain regulatory compliance, protect sensitive information, and foster a culture of data stewardship.
Top ROI-Driving Fivetran Features
Platform Scalability
Fivetran’s scalability is also a pivotal driver of business value. As an organization’s data footprint grows, Fivetran can effortlessly scale to handle the increasing load, be it additional connectors, more frequent loads (as little as 1 minute!), or the ever-expanding volume of rows loaded.Â
Furthermore, data teams have full transparency into the costs of adding a new connection. Upon creating a new connector, Fivetran will load this data for free and provide an estimated monthly cost based on the next 14 days of usage. Should the team decide the price is not worth it, they can delete this connector without repercussions.Â
These features allow data teams to readily embark on new data projects with confidence, knowing they can efficiently integrate complex data sources and scale as needed without financial uncertainty or resource constraints.
Integration with dbt Cloud
Because Fivetran centralizes all of your data into one data platform, organizations are put into a position where they can leverage dbt Cloud. dbt pairs excellently with Fivetran as Fivetran can automate the ingestion of data sources, while dbt handles all of the transformations that model your data into insightful and actionable analytics.Â
This integration allows customers to schedule and run their dbt Cloud jobs directly from the Fivetran platform. Fivetran allows you to execute dbt jobs as soon as their Fivetran counterparts have finished ingesting new data, providing a solution for low-latency data loads. This means you save time between your source data loading to your data transforming inside your data warehouse.Â
Additionally, customers can view dbt job logs directly from the Fivetran platform, allowing engineers to view and debug ingestion jobs and transformations all in one place.
Conclusion
Fivetran can provide data teams with a significant ROI due to the business value it generates. Since the platform automates everything involved with data ingestion, teams can spend less time worrying about maintaining and debugging their data sources.Â
Additionally, new data sources can be easily ingested with just a few clicks, allowing data teams to start building out actionable insights from day one.Â
Should it be deemed too expensive to load a data source, it’s easy to cancel and delete this job without any cost, as Fivetran provides a free fourteen-day trial for all new connectors, even custom ones!Â
This gives teams the confidence to add to their data ecosystem without worrying about the cost incurred. Fivetran also seamlessly integrates with dbt Cloud, allowing data teams to build out low-latency solutions that can provide their actionable insights at the lowest latency possible.
Interest in leveraging Fivetran?
As Fivetran’s 2024 Partner of the Year, the experts at phData can help optimize your Fivetran experience with real-time data and batch replication, automation, migration needs, and much more!
