Data management projects are complex, challenging, and time-consuming. Project leads need tools to quickly and efficiently apply data quality standards, migrate data, and create governance frameworks.
Aperture Data Studio is a powerful and user-friendly data quality management suite. It helps manage consumer data projects and enables users to quickly develop sophisticated workflows. These workflows incorporate machine learning for automatic data tagging and enrich data using globally curated sets from Experian. This ensures data quality and helps govern adherence to data standards.
Aperture Data Studio v2.15 includes three powerful new features for your data management and governance initiatives.
1. Pushdown Processing
Within Aperture Data Studio, Pushdown Processing (PDP) enables data managers to convert a Workflow into a SQL query that is executable on database tables without the need to transfer the table data into Aperture Data Studio.
Pushdown processing is a technique used in data management to optimise query performance by offloading processing tasks to the data source itself. Examples of the data processing tasks PDP empowers include:
- Filtering – applying conditions to data
- Aggregation – creation of summary statistics
- Joins – combining data in different sets
- Sorting – arranging data in order
- Profiling – real-time insights from your source system
Instead of transferring large amounts of data to a central processing unit, pushdown processing allows the data source (such as a database or data warehouse) to perform the processing directly.
Results are displayed for exploration and manipulation within Aperture Data Studio, helping users to quickly and securely process data quality workflows in one place, without the need for any coding.
PDP overcomes the dual problem of security concerns and long processing times when processing large data volumes, whilst keeping costs down due to lower resource requirements such as servers required for data transfer.
Pushdown Processing in Aperture Data Studio further benefits from Experian’s data capabilities including direct access to source data for improved customer service.
2. Real-time Workflows
Another impressive new feature is Real-time Workflows (RTW), a module that empowers users to validate, transform, enrich and govern a single data record in real-time from the point of collection.
Real-time workflows are automated processes that react to and process data as it is generated, without significant delays. These workflows are crucial for organisations that must make timely decisions based on the latest information and prevent poor data entry into their source system.
RTWs are capable of:
- Ingesting data – in real-time from the source, including as it is generated
- Processing data – for transformation, enrichment & cleansing
- Analysis – identification of trends and patterns
- Automatic triggers – responses or notifications based on pre-set parameters.
- Data validation workflows – ensure data accuracy across all source systems
The outcome driven by this powerful new addition to Aperture Data Studio is that a data manager can find and fix issues with any type of data anywhere in their database. This creates an upstream benefit as the data can inform decision-making faster than before – in real-time.
Immediate validation at the point of processing creates a uniform consistency of data quality rules across disparate data systems, reducing processing times and improving operational efficiency.
This capability is useful across all major industries but relies upon a high standard of data quality across an organisation; this makes RTWs an especially relevant offering as part of the Aperture Data Studio data management solution.
3. GenAI
Examples of work in roadmap/progress:
Aperture Data Studio is soon to be enhanced with Generative Artificial Intelligence (GenAI), a type of AI that is capable of creating suggestions, having learned from patterns within large volumes of data that existed previously.
In data management, GenAI can support a whole host of use cases, including but not limited to:
- The automatic creation of data quality rules
- Glossary-style explanations of data quality rules
- Observations, insights, warnings and responses to data profiling through intelligent detection capabilities
- Automatic completion of names, descriptions & data types
GenAI builds upon our six key areas of automation in data quality:
- Smart harmonisation
- Suggested transformations
- Automated rule creation and smart profiling
- Distributed architecture
- Real-time use
- Powerful dashboarding
Alongside other powerful benefits from our Machine Learning (ML) integration such as auto-classification, smart suggestions and outlier analysis, the addition of GenAI to Aperture Data Studio will transform the productivity, efficiency and speed with which users drive value for their organisations.
For more information on the current product roadmap, please visit our website.