Bismart Data Integration Framework is a data ingestion and integration platform designed to facilitate and streamline data integration processes in the corporate environment, especially in the context od data integration with Azure Data Factory (ADF).
The solution has been developed to perform optimally both with SQL and Databricks.
The platform, developed by Bismart, is based on Azure resources, orchestrated by Azure Data Factory and configurable via metadata.
Are your data integration projects disorganized and individually managed, increasing complexity and risks?
Is the lack of standardization and automation in your integration processes affecting the scalability of your solutions in Azure Data Factory?
Are you looking for a centralized solution that allows you to easily control, document and scale all your data integration processes?
Standardize and automate data integration:
save costs and improve process efficiency
You can see all the technical specifications of Bismart Data Integration Framework in the solution's datasheet.
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Data Integration Framework: How Does It Work?
Data Integration Framework allows moving and transforming data from multiple sources to multiple destinations, with the advantage of allowing you to define which objects to integrate and how the readings at source, the loads at destination and the activation criteria of each ingest must behave.
- Reduction of costs and implementation times: Especially valuable in projects with a large number of tables, where automation and standardization of processes reduces the operational burden.
- Greater control and data governance: The framework provides a complete and centralized view of processes, facilitating the identification and resolution of loading problems.
- Operational efficiency: Optimized processes reduce component redundancy and duplicate loading logic, reducing the risk of errors.
- Ensured scalability: Modular design and customization capabilities allow data integration processes to scale as business needs grow.
Data Integration Framework with Databricks
Data Integration Framework with SQL
Data Integration Framework: ¿Por qué lo necesitas?
Bismart's team of experts in data integration has developed this platform to solve the most recurring and complex issues of data integration processes in Azure Data Factory.
Contextualization: Problems of Using Data Factory for Data Integration without a Framework
Projects developed with Data Factory require control and a methodology, otherwise:
- Each project or solution is designed independently, which is a major risk
- Easily leads to disorder
- Difficulty of adoption of the solution by new users
- There are as many processes as tables to be loaded, with the consequent duplication of loading logics.
- Redundancy of components: linked services, datasets, copying activities...
- Overcosts
- Slow processes, generally executed in sequence or with too much parallelism
- Poor data governance: difficulty in identifying, locating and resolving problems in the loads
- Decentralization and poor process control
- No alignment between the “technical” load criteria and the “functional or business” load criteria.
Main advantages of Bismart Data Integration Framework
- Architecture 100% based on Azure
- Standardization of data ingestion processes in Data Factory
- Reduction of implementation costs (especially when the number of tables is high)
- Faster implementation, ingestion and data transformation times
- Facilitates the adoption of the tool for team members
- Streamlines and optimizes data loading processes from any data source (cloud or on-premise)
- Provides a high flexibility and scalability to the platform
- Centralized monitoring of all processes
- Allows configuring read-at-source and load-at-destination behaviors for each individual ingestion
- Includes mechanisms for automatic historification of source data
- Detects changes in the source data structure, manages these changes through preconfigured rules and notifies those responsible for changes
You can see all the technical features of Bismart Data Integration Framework in the solution's datasheet.
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