Data Pipelines
Organizations are aspiring to become data driven. Intuitive decision-making is getting replaced by fact-based decision-making that is backed by data. Often, enterprises find it difficult to implement this data-driven decision-making as most of the workforce performing this task could be non-technical. Integrating data to make it accessible for analytics is a highly technical process. This is what data pipelines enable organizations to do; make data analysis easier for business analysts.
Pipelines in Hevo
A data pipeline, or Pipeline in Hevo is a no-code data processing framework that loads data from any Source such as a database, SaaS application, or file into a Destination database or data warehouse. For example, you may load data from your Facebook Ads account to a Google BigQuery data warehouse for analysis.
With just a few clicks you can have analysis-ready data at your finger tip, without any data loss. You can even view samples of incoming data in real-time as it loads from your Source into your Destination.
Pipeline Components
The following form the key components of a Pipeline:
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Source: You can configure a new Source by providing the required connection parameters or use an existing one. Read Sources for the various Sources that Hevo integrates with.
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Destination: You can use an existing Destination or specify the necessary connection parameters to configure a new one. At this time, you can replicate data from a Source database only to a Snowflake Destination. Read Destinations.
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Pipeline: In the Pipeline configuration, you can define the way in which you want Hevo to load data to your Destination. Here, you can specify how your Destination schema should evolve and also how often the data from the Source should be synchronized with the Destination.
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Objects: Hevo allows you to select the objects from which you want to replicate data. You can also define a primary key for your object here if you have opted to load data to the Destination with the Merge data loading policy.
In a Pipeline, one Source maps to one Destination only. However, the same database or data warehouse may be configured as a Destination for multiple Sources.
Benefits of Creating Pipelines Using Hevo
Following are some of the benefits of creating Pipelines using Hevo:
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Near Real-Time Data Transfer: Hevo provides real-time data migration, so you can perform data analysis anytime as per your business need.
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100% Complete and Accurate Data Transfer: Your Hevo Pipeline ensures reliable data transfer with zero data loss.
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Scalable Infrastructure: Seamless integrations with Sources can help you scale your data infrastructure as per your business need.
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Live Monitoring: Options to view the data and its movement along different stages of the Pipeline allows you to monitor the progress of your data replication. You can also control the number of Events your Pipelines load per day and be alerted whenever this limit is exceeded. Read Data Spike Alerts.
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Connectors: Hevo supports integration with various warehouses including Google BigQuery, Amazon Redshift, and Snowflake, Amazon S3 data lakes, and MySQL, MongoDB, TokuDB, DynamoDB, PostgreSQL databases to name a few. Read Sources.
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Schema Management: Pipelines created in Hevo take away the tedious task of mapping and managing the Destination schema. The Auto Mapping feature automatically detects the schema of your incoming data and maps it to the Destination schema. You also have the option to do this manually.