Business rules and workflow
Ability to define and manage business rules and workflows
Cat avg: 8.3
Top Performing Features
Simple transformations
Simple data transformations are calculations, data type conversions, aggregations and search and replace operations
Cat avg: 8.1
Data model creation
Ability to create and maintain data models using a graphical tool to define relationships between data
Cat avg: 8.4
Connect to traditional data sources
Ability to connect to traditional data sources like relational databases, flat files, XML files and packaged applications
Cat avg: 8.8
Worst Performing Features
Testing and debugging
Tool to debug and tune for optimal performance
Cat avg: 7
Complex transformations
Complex data transformations are data normalization, advanced data parsing, etc.
Cat avg: 7.2
Collaboration
Collaboration is enabled by a shared repository of project information and metadata
Cat avg: 7.3
Astera Data Pipeline Builder (Centerprise) Features from Reviews
Data Source Connection
Ability to connect to multiple data sources
8.2-3%
Connect to traditional data sources
Ability to connect to traditional data sources like relational databases, flat files, XML files and packaged applications
Category average: 8.8
Connecto to Big Data and NoSQL
Ability to connect to non-traditional data sources like Hadoop and other big data technologies, and NoSQL databases
Category average: 7.8
Data Transformations
Data transformations include calculations, search and replace, data normalization and data parsing
6.9-11%
Simple transformations
Simple data transformations are calculations, data type conversions, aggregations and search and replace operations
Category average: 8.1
Complex transformations
Complex data transformations are data normalization, advanced data parsing, etc.
Category average: 7.2
Data Modeling
A data model is a diagram or flowchart that illustrates the relationships between data
7.1-11%
Data model creation
Ability to create and maintain data models using a graphical tool to define relationships between data
Category average: 8.4
Business rules and workflow
Ability to define and manage business rules and workflows
Category average: 8.3
Collaboration
Collaboration is enabled by a shared repository of project information and metadata
Category average: 7.3
Testing and debugging
Tool to debug and tune for optimal performance
Category average: 7
Data Governance
Data governance is the practise of implementing policies defining effective use of an organization's data assets
8.2+5%
Integration with data quality tools
Integration with tools for cleansing, parsing and normalizing data according to business rules
Category average: 7.9
Integration with MDM tools
Integration with master data management tools to ensure data consistency across the organization
Category average: 7.8
Astera Data Pipeline Builder (Centerprise) Features from the Vendor
Data Source Connection
Vendor-contributedConnect to traditional data sources
Ability to connect to traditional data sources like relational databases, flat files, XML files and packaged applications
Connecto to Big Data and NoSQL
Ability to connect to non-traditional data sources like Hadoop and other big data technologies, and NoSQL databases
Data Transformations
Vendor-contributedSimple transformations
Simple data transformations are calculations, data type conversions, aggregations and search and replace operations
Complex transformations
Complex data transformations are data normalization, advanced data parsing, etc.
Data Modeling
Vendor-contributedData model creation
Ability to create and maintain data models using a graphical tool to define relationships between data
Metadata management
Automated discovery of metadata with ability to synchronize and share metadata with other tools like Master Data Management
Business rules and workflow
Ability to define and manage business rules and workflows
Collaboration
Collaboration is enabled by a shared repository of project information and metadata
Testing and debugging
Tool to debug and tune for optimal performance
Data Governance
Vendor-contributedIntegration with data quality tools
Integration with tools for cleansing, parsing and normalizing data according to business rules
Integration with MDM tools
Integration with master data management tools to ensure data consistency across the organization
Additional Features
Vendor-contributedIntegrated development environment
Data quality and profiling
Job flow, scheduling, and execution
Performance and scalability
Code-free user interface
Pushdown mode
Dynamic load balancing
Parallel processing engine
Real-time job monitoring
Management of access and control