
Ab Initio is a high-performance data platform designed to help organisations effectively manage and process vast amounts of continuously changing data, uncovering valuable insights and knowledge. By embracing automation and self-service capabilities, it enables businesses to adapt swiftly to evolving circumstances, ultimately driving agility and speed in decision-making. The platform seamlessly integrates modern and legacy technologies, addressing the complex data processing and management challenges that large organisations face. With a focus on delivering innovative software built “from first principles,” Ab Initio fosters a collaborative environment, working closely with clients to ensure successful outcomes through comprehensive proof-of-concept engagements that validate performance against high data volumes, complex logic, and critical business requirements.
Architectural Principles
A strong architecture forms the foundation of any system, enabling faster, flexible, and efficient builds that adapt to changing business needs. Ab Initio’s architecture, designed from first principles, achieves scalability, resilience, and low operating costs without compromise, delivering these benefits consistently for mission-critical systems.
Graphical Development
Ab Initio’s graphical design skips coding, using visual flows for easy development, faster debugging, and agile testing.
Metadata-Driven Engine
Ab Initio uses metadata to adapt applications to changes, reducing maintenance and supporting scalable, flexible data handling.
Performance and Flexibility
Built in C++ with just-in-time compilation, Ab Initio is optimised for speed and flexible, metadata-driven adaptability across environments.
Parallel Processing
Ab Initio scales from laptops to massive clusters, using a “shared-nothing” architecture to efficiently distribute data and processing, ensuring high performance and compatibility with both legacy and modern systems.
Distributed Processing
Ab Initio’s shared-nothing setup allows applications to scale across servers and cloud environments, running seamlessly on diverse networks as if on a single platform.
In-Memory Processing
Ab Initio enables high-speed, real-time processing by using in-memory clusters, optimising performance and minimising latency.
Platform Independence
Ab Initio supports smooth application migrations across platforms and integrates easily with both legacy and modern data formats.
Batch, Real-Time Services, and Streaming
Ab Initio’s data-flow architecture supports batch, streaming, and real-time processing with high performance and low latency, enabling business logic reuse without extra integrations.
Robustness
Ab Initio has built-in robustness with checkpointing and backup paths to handle failures seamlessly, preventing errors from affecting outcomes.
Metadata and a Data Catalog
Ab Initio combines data and metadata management for a comprehensive data catalog, lineage tracking, and governance tools, supporting enterprise data management.
Data Processing Platform
Ab Initio’s data processing platform streamlines complex data and business logic integration at any scale, overcoming challenges posed by continual change and diverse data formats. Designed for adaptability and processing speed, it enables high-performance applications that run in parallel across multiple architectures, from batch to microservices. It offers enhanced agility with features like distributed checkpoint restart, monitoring, and runtime adaptability. This platform manages technical details, allowing architects, analysts, and developers to concentrate on data and business logic.
Unlock Productivity, Agility, and Performance in Data Processing
Ab Initio’s graphical tools enable fast, code-free development of complex data applications, making them accessible to both developers and business users. This intuitive design speeds up implementation, reduces maintenance, and requires smaller teams.
Ab Initio’s high-performance platform supports both batch and real-time processing, using scalable, parallel processing to handle data-intensive applications across multiple servers. With one unified engine, applications can achieve high throughput for batch tasks or low latency for real-time tasks, accessing various data sources without reimplementation—only runtime reconfiguration is needed.
Ab Initio enables distributed execution across multiple servers and platforms, treating a network of servers as a unified system. It scales processing power by leveraging multiple processors across containers or servers, with runtime adaptability for data streaming between components. Running natively on various platforms, including cloud, Linux, and mainframes, Ab Initio provides a consistent experience, letting users focus on data and business rules instead of platform differences.
Ab Initio offers platform independence, allowing applications to run seamlessly across physical, virtual, cloud, or hybrid systems on Linux, Hadoop, Unix, Windows, and mainframes. This future-proof design ensures compatibility across legacy and modern platforms, eliminating the need for reimplementation as technology evolves.
Ab Initio supports elastic scaling, adjusting resource use on demand to match data volumes. In clustered setups, it integrates with resource managers like YARN and Kubernetes to maximise utilisation, scaling out for high data loads to meet SLAs and scaling down to save costs in cloud environments.
Ab Initio’s Just-In-Time engine supports agility and resilience by adapting at runtime to changes, such as new fields or business rules, without impacting performance. Driven by metadata, it enables seamless adjustments in data formats, storage, parallelism, and execution environments, allowing applications to evolve with minimal cost and effort. This approach combines high performance with flexibility, ensuring large businesses can handle changes effectively.
Ab Initio supports scalable microservices for real-time applications, using a graphical, data-flow approach. Each microservice is a data flow graph that processes requests and responses, allowing for easy integration with business rules and other services. Compatible with service mesh, containerisation, and DevOps standards, Ab Initio enables rapid building, testing, and deployment, maximising productivity.
Ab Initio supports a wide range of data sources and formats, continually expanding with each release.
Key supported areas include:
Databases: Major options like Snowflake, Google BigQuery, Oracle, SQL Server, and various legacy systems.
Files and Objects: Compatibility with file systems across Linux, Unix, Windows, and cloud storage services like Amazon S3 and Azure Blob Storage.
Data Formats: Support for simple to complex formats such as XML, JSON, and various industry standards.
Queues, Messaging, and APIs: Integration with technologies like Kafka, REST, SOAP, and various messaging systems.
Change Data Capture: Options for major databases like DB2 and Oracle.
Applications: Compatibility with platforms like Salesforce, SAP, and Microsoft Excel.
Ab Initio is committed to adding new data sources and formats, encouraging users to reach out for specific needs not listed.
Ab Initio’s metadata-driven approach allows for the creation of flexible, reusable applications that can adapt to new data formats, rules, and systems at runtime. This enables a small team of technical experts to develop a general-purpose framework, empowering business users to configure their specifications through user-friendly interfaces. As a result, fewer technical resources are needed, maintenance is simplified, and the overall system cost is reduced. This method significantly enhances team productivity, speeds up time to market, and minimises ongoing maintenance efforts in large organisations.
Cloud Native
Ab Initio offers cloud-native applications that leverage the full capabilities of the cloud to enhance operational and technical efficiency. These applications can run in public clouds, virtual machines, or containers, and support both real-time and batch processing with elastic scaling. Ab Initio also assists in migrating legacy applications and data warehouses to modern cloud technologies like Snowflake, Amazon Redshift, and Google BigQuery, ensuring readiness for cloud deployment from day one.
Unlock Cloud Benefits: Cost Savings and Agility with Ab Initio
Large companies often face challenges in realising the benefits of cloud migration due to complexities such as monolithic applications, outdated technologies, and reliance on expensive hardware. Ab Initio helps organisations navigate these hurdles by enabling both hybrid and full cloud migrations. Its tools automate the conversion of existing systems to high-performing Ab Initio applications, allowing for rapid deployment in the cloud with containerised, 12F-compliant workloads. Companies can adopt a phased migration approach, moving virtual machines off premises, transitioning to object or blob storage, and eventually shifting to containerised solutions.
Ab Initio offers an agile data processing platform that supports the development of large-scale, cloud-native applications compliant with the 12 Factor methodology:
- Codebase: A single codebase is tracked in source control with multiple deployments.
- Dependencies: All dependencies are explicitly declared.
- Configuration: Environment-specific configurations are stored separately.
- Backing Services: All services are treated as attached resources, managed by the execution environment.
- Build, Release, Run: A clear separation exists between the build and run stages in the delivery pipeline.
- Processes: Applications run as stateless processes with data stored in backing services.
- Port Binding: Services expose themselves through specified ports.
- Concurrency: Processes scale individually to enhance concurrency.
- Disposability: Fast startup and graceful shutdown promote resilience.
- Dev/Prod Parity: Environments for development, testing, and production remain as similar as possible.
- Logs: Logs are managed as event streams.
- Admin Processes: Administrative tasks run as one-off processes.
This framework ensures applications are sophisticated, maintainable, and scalable.
Ab Initio enhances cloud portability, helping large organisations avoid vendor lock-in while utilising cloud resources. It allows seamless migration between cloud providers without re-coding, supporting consistent application development across various environments, including hybrid models. This flexibility is achieved through five layers of abstraction, enabling quick reconfiguration of target providers and componets, allowing changes to be made in minutes instead of weeks.
Ab Initio facilitates agile provisioning by enabling automated management of containers and virtual machines, helping enterprises reduce IT costs and streamline operations. It integrates with tools like Ansible and Terraform for infrastructure as code, allowing rapid configuration and deployment of environments. Ab Initio also supports Docker for packaging applications and offers complete control over container image layers, enhancing the CI/CD process for deploying updates efficiently.
Ab Initio accelerates time to market for cloud applications by providing a unified data processing and management platform, eliminating the complexities of integrating various technologies. This integrated approach enhances productivity through automation, self-service, and no-code development capabilities, allowing companies to save time and resources on development, testing, administration, and governance tasks.
Ab Initio simplifies cloud connectivity by providing a wide range of efficient and flexible connectors for various cloud filesystems (like AWS S3, GCS, and Azure Blobs), messaging queues, and databases (such as Snowflake and BigQuery). Users can quickly integrate new data sources with a simple drag-and-drop interface, and connectors can adapt at runtime based on metadata. This allows applications to switch between different cloud services, data formats, and configurations without any code changes, ensuring agility and reducing vendor lock-in.
Ab Initio supports scalable microservices for real-time applications, using a graphical, data-flow approach. Each microservice is a data flow graph that processes requests and responses, allowing for easy integration with business rules and other services. Compatible with service mesh, containerisation, and DevOps standards, Ab Initio enables rapid building, testing, and deployment, maximising productivity.
Ab Initio enables developers to quickly build, deploy, and scale microservice-based applications using a graphical data flow processing paradigm. Each microservice functions as a data flow graph that processes service requests via RESTful calls, coordinating with business rules and other services while managing concurrency and timeouts. Ab Initio’s microservices integrate seamlessly with service mesh technologies and support containerisation, DevOps, and OpenAPI standards, resulting in unparalleled productivity in application development and deployment.
Ab Initio is highly efficient and elastically scalable, significantly reducing cloud costs by optimally using CPU and memory resources. Its performance often surpasses that of handcrafted code, being five to ten times faster than integration vendors and database engines. Companies that have transitioned from large-scale Java frameworks to Ab Initio have reported reductions of up to 50% in CPU usage and 80% in memory consumption, resulting in lower overall compute costs compared to other technologies.
Ab Initio enables elastically scalable and cost-effective serverless applications to meet the growing demand for faster response times from digital consumers. By supporting elastic microservice deployments, in-memory databases, and Lambda architectures, Ab Initio helps manage costs effectively. It allows for independent scaling of CPU and storage, giving customers better control over performance and costs in the cloud. Developers can deploy applications with greater granularity, reusing the same business logic for varying data volumes in dedicated containers.
Real-Time Digital Enablement
Ab Initio enables businesses to build, test, and manage modern, digitally enabled applications that meet the demands of real-time decision-making and complex business logic. The software supports high throughput, low latency, and both stateless and stateful service-based architectures, all designed graphically. Its parallel, distributed in-memory cluster combines the advantages of an in-memory data grid and compute grid, providing a robust platform for developing real-time operational systems in a digital environment.
Rapidly Build Advanced Real-Time Systems with Ab Initio
Ab Initio’s platform supports batch, streaming, and service-based architectures, enabling high-performance, scalable applications. Data is processed through graphical data flow graphs, facilitating high-throughput, reliable streaming with exactly-once guarantees. It allows for the integration of various data sources, processing millions of records per second from inputs like IoT devices and web interactions.
Ab Initio simplifies the development of microservice-based applications through its graphical data flow processing paradigm. Each microservice is represented as a data flow graph, processing requests via RESTful calls and enabling coordination across services with concurrency and timeout management. Ab Initio microservices support containerisation, DevOps, and industry standards like OpenAPI, allowing for rapid building, testing, and deployment, resulting in high productivity.
Ab Initio offers robust state management for stateful services through a highly available, parallel in-memory cluster. This architecture allows for scalable microservices, with data replicated across multiple servers to ensure high availability and consistency. In the event of an error, Ab Initio can seamlessly failover to another server, preventing data loss or duplication. The in-memory cluster supports dynamic scaling and real-time updates to service logic and storage schemas without downtime, enabling developers to concentrate on business logic while ensuring low-latency performance and high throughput.
Ab Initio offers advanced in-memory computing capabilities that enable developers to create low-latency applications with high availability and 24/7 operation. Its built-in features include redundant cluster management, elastic scalability, and distributed checkpointing, ensuring data integrity by preventing loss or duplication. In the event of a server crash, services can quickly resume, making Ab Initio’s real-time, stateful computing platform exceptionally powerful for real-time applications.
Ab Initio applications can elastically scale up or down based on demand, optimising resource usage to meet changing business conditions. It automatically manages stateful job execution, ensuring exactly-once processing and seamless job recovery. As the in-memory cluster size adjusts, data records are evenly distributed across servers to facilitate efficient parallel processing.
Ab Initio’s real-time services are highly resilient, ensuring data availability through automatic checkpointing and replication across multiple servers. In case of a crash, data is not lost if any redundant copy is available or saved to disk for disaster recovery. Ab Initio manages job execution consistently, allowing seamless failover to another server, ensuring exactly-once processing. This automatic resilience allows developers to focus on business logic without worrying about data integrity.
Ab Initio’s visual development approach simplifies collaboration between business and technical teams by making software logic easy to understand. Analysts can directly build, test, and adjust rules through an intuitive interface, enabling fast prototyping and automatic deployment once the logic is finalised.
Ab Initio allows users to create business rules for real-time streaming and service-based applications through an intuitive rules-development interface resembling a spreadsheet. This enables non-programmers to quickly specify, test, and deploy rule-based applications at a fraction of the time and cost compared to traditional development methods. Users can create rules for calculations, mappings, decision trees, or machine learning model calls, streamlining the development process.
Ab Initio simplifies building complex API orchestration services by allowing each API to be treated as a microservice and managing data flow between them. It can connect various data sources and systems, making data transformations straightforward. Ab Initio supports standard messaging systems and enables easy mapping of messages to API calls through its intuitive rules-development environment. The API orchestration layers can operate across multiple clouds or in hybrid environments and can be serverless and fully elastic.
Searching, Scoring & Matching
Understanding the relationships between data on customers, partners, suppliers, and counterparties is essential for digital services, impacting both service quality and regulatory compliance. Ab Initio’s search, scoring, and matching technology offers a rapid and flexible solution for accurately matching customers and companies, even with inconsistent or incomplete data. It enables analysis of large datasets, clarifies inferred relationships, and reduces false positives, ensuring reliable identification and compliance.
Overcome Data Matching Challenges with Ab Initio
Ab Initio enables business experts to easily develop and debug their own matching rules through an intuitive interface. Built on advanced search technology, it allows for customisation to address specific matching scenarios, ensuring deterministic rules with full traceability.
Users can adjust matching thresholds to determine when two entities are considered the same, enabling reliable testing of results. This flexibility reduces both false positives and false negatives, minimising costs associated with manual checks and compliance issues.
Ab Initio’s matching technology produces fewer false positives while maintaining the same false negative rate compared to other solutions. This efficiency helps reduce the resources needed for investigations and compliance.
Ab Initio’s software scales effortlessly, maintaining performance even as data volumes increase. Users can search through vast datasets with low latency, processing millions of transactions daily without performance degradation.
Ab Initio provides a fully deterministic matching process with extensive diagnostics, ensuring consistent results for the same inputs. Users can easily understand the rationale behind matches, enhancing audit confidence.
When records match multiple clusters, Ab Initio logs alternatives and flags potential data quality issues, allowing for manual review and ensuring accurate clustering decisions.
Ab Initio employs multiple match strategies to manage missing or conflicting data, utilising advanced search algorithms for comprehensive candidate selection while minimising evaluation time.
Ab Initio helps rapidly verify customer identities and screen them against sanctions lists. Its technology merges and de-duplicates data, providing a complete customer profile while maintaining a low false positive rate for sanctions checks.
Banks utilise Ab Initio to monitor transactions and quickly identify sanctioned entities, ensuring compliance while processing legitimate transactions without delay.
Ab Initio balances thorough matching for compliance with the need for timely processing of legitimate transactions, providing a comprehensive audit trail to demonstrate adherence to regulations.
Ab Initio efficiently preprocesses large volumes of records, allowing for streamlined transaction handling by sending de-duplicated lists, significantly reducing the workload for subsequent processing.
BI, Analytics & Data Engineering
Business intelligence and analytical techniques, including machine learning, can uncover valuable insights within vast amounts of data. Many companies are evolving to become data-driven, as quicker data collection and understanding enhance performance. The primary challenges include locating quality data and preparing it for analysis, along with operationalising the insights gained. Ab Initio accelerates both of these processes, enabling organisations to find, understand, learn from, and utilise their data efficiently.
Accelerate Your Business Intelligence and Analytical Applications with Ab Initio
Data scientists spend most of their time preparing and finding data rather than training machine learning models. Ab Initio streamlines this process by making it easy to catalogue, cleanse, and identify relevant data subsets. The software helps organise data into a comprehensive format that is ready for machine learning, enabling users to add, understand, and combine datasets efficiently.
The quality of features presented to machine learning models is crucial for successful training. Ab Initio facilitates the standardisation of attributes into features and helps data scientists understand field values and cross-field correlations through semantic discovery. It simplifies the application of functions to create features, allowing for effective model learning.
Ab Initio supports the rapid deployment of machine learning models into production. It allows models to run in both batch and real-time environments, enabling easy transitions from development to deployment. Users can leverage existing R and Python libraries within Ab Initio, ensuring comprehensive data processing capabilities.
Ab Initio’s data catalog provides a centralised portal for data access across an organisation, regardless of format or location. It accelerates data discovery, cleansing, and governance, enabling data scientists to quickly find trusted datasets, which significantly reduces the time needed for data analytics and model training.
Ab Initio creates a virtual data hub that logically unites disparate data sources, simplifying access for data scientists. This allows for seamless examination of data, regardless of its storage location, while enforcing access control permissions and enabling data masking for sensitive information.
Ab Initio’s visual development model allows both non-developers and developers to create applications rapidly without writing low-level code. It automates technical tasks by leveraging metadata from the data catalog, enabling users to prepare data for model training easily.
Analyst-developed applications can be directly promoted to production without needing extensive rewrites or tuning. Ab Initio’s efficient framework allows for the rapid deployment of machine learning models, ensuring high performance in real-time environments.
Ab Initio allows analysts to quickly specify and test business logic without developer involvement. This feature enables the creation of rules that help select datasets for various purposes, facilitating efficient data ecosystem design and model training.
Ab Initio enhances data governance and quality by using algorithms and machine learning. It provides visibility into datasets and their lineage, facilitates compliance, and automates data quality controls, allowing data specialists to curate and share trusted datasets effectively.
Ab Initio’s data-processing platform simplifies the integration of data from diverse sources into a corporate data lake. It supports various data formats and ensures secure, efficient data ingestion while maintaining user-specific access controls. The user-friendly interface and robust data catalog enhance data accessibility for business applications.
Decision Automation
In the digital economy, businesses must make fast, smart decisions at scale, requiring seamless data processing and integration. Ab Initio’s decision automation platform enriches and aggregates data in real time, enabling automated, sophisticated decision-making for efficient and responsive operations.
Empower Real-Time Decision-Making with Ab Initio
To enhance decision-making, it’s essential to eliminate silos by integrating data, events, and insights from across the enterprise. Ab Initio’s platform automates the decision-making process in real-time, combining historical insights with current data. This ensures that decision models operate effectively and are continuously refined based on feedback.
Ab Initio provides a comprehensive, real-time view of all relevant entities, including transactions and behaviours. This unified 360-degree profile ensures that decisions are based on up-to-date information, enabling timely and relevant insights that enhance decision-making across various scenarios.
Incorporating real-time contextual data into the decision-making process is vital. Ab Initio allows for the integration of synchronous and asynchronous data, enabling smarter decisions based on current customer behaviour and interactions, which is crucial for improving profitability and efficiency.
Ab Initio supports complex event triggers to facilitate immediate responses to critical customer needs or behaviours. By processing signals in real-time, the platform ensures that appropriate actions are taken as soon as significant changes or thresholds are detected.
Monitoring the changing state of entities is essential for making timely decisions at critical moments. Ab Initio tracks transitions and state changes across various pathways, enabling businesses to react appropriately when customer behaviours shift.
Ab Initio’s platform is designed for unlimited scalability, allowing organisations to process increasing volumes of data efficiently. As businesses face growing data challenges, this scalability ensures they can meet the demands of the evolving digital landscape.
Effective decision-making requires seamless integration across enterprise systems. Ab Initio’s decision automation platform ensures that decisioning data and processes are efficiently integrated into operations, enhancing consistency and efficiency.
The Ab Initio platform is built for operational resilience, delivering reliable, high-performance decision-making. Its architecture supports high availability and fault tolerance, enabling businesses to make confident decisions even under intense operational pressure.
Self-Service Empowerment
Ab Initio promotes self-service capabilities within large organisations, reducing dependency on others and speeding up project completion. By empowering non-developers to create and test rules and configure data-oriented applications, teams can transform data into actionable intelligence. This shift fosters a more dynamic and agile organisational culture, ultimately driving agility and productivity across both business and technical teams.
Empower Your Users with Ab Initio’s Self-Service Capabilities
Ab Initio offers an intuitive interface for business rules, allowing non-developers to create, test, and update critical business logic without needing programming skills. This empowers users to operationalise rules directly, adapting them as conditions change while reducing IT involvement.
Ab Initio includes robust simulation and testing capabilities, enabling users to validate their business rules using real or simulated data. Users can perform detailed analysis and “what-if” simulations without impacting production data, ensuring rule quality before deployment.
The interactive lineage diagram in Ab Initio provides a graphical overview of how data flows into specific rules, making it easier for business experts to diagnose and correct computation errors.
Ab Initio allows non-developers to promote related business rules into production through a tagging process, which facilitates automated validation and testing without IT intervention.
Ab Initio’s no-code environment empowers both developers and business experts to build sophisticated data transformation applications. The platform automates complex tasks, enabling users to focus on business logic and improving productivity.
Ab Initio’s centralised data catalog serves as a single portal for all enterprise data, facilitating data discovery, cleansing, and integration. It standardises access to datasets from various sources, making data more manageable and understandable.
By providing a centralised data catalog, Ab Initio allows self-service access to enterprise data for all employees. This simplifies data access, enabling teams to focus on their work without cumbersome permission processes. By providing a centralised data catalog, Ab Initio allows self-service access to enterprise data for all employees. This simplifies data access, enabling teams to focus on their work without cumbersome permission processes.
Ab Initio tracks data lineage across business applications, providing insight into data sources, transformations, and creations. This feature enhances transparency and compliance while aiding future project planning.
Ab Initio creates a unified metadata environment, integrating data from diverse systems into a coherent interface. This enriches the metadata with business terms and enhances understanding across the organisation.
Ab Initio enables non-developers to configure and manage data processing applications through metadata-driven frameworks. This allows business experts to focus on using data for insights without needing technical expertise.
Ab Initio facilitates self-service data onboarding, allowing authorised users to upload datasets without lengthy delays. This empowers data scientists to access and explore data quickly while ensuring necessary controls and protections are in place.
Automation
Organisations need to respond swiftly to changing business needs, but large companies often find their technical teams act as bottlenecks. Automation is key to achieving agility. While some processes require oversight, many—such as data understanding, optimisation, unit testing, and application deployment—can be automated.
Ab Initio views metadata as active information that drives operational processes, in contrast to traditional approaches that treat it as passive. The core of Ab Initio technology is a processing engine that integrates this active metadata with just-in-time processing, allowing applications to adapt in real-time. This capability facilitates true automation, enabling significant savings for large organisations and reducing time to market while enhancing quality.
Automate Your Data and Governance Systems with Ab Initio
Ab Initio’s advanced data discovery capabilities utilise semantic discovery and machine learning algorithms to automatically inventory data content. This reveals data characteristics and relationships, significantly reducing project timelines—transforming lengthy cataloging efforts into mere weeks. The integrated technology also supports the autogeneration of data quality rules and enhances data protection and self-service ingestion.
Combining semantic discovery with automatic data quality rule generation, Ab Initio simplifies managing data quality across numerous datasets. The software automatically identifies data types and relationships to generate and apply data quality rules. This automation helps quickly address reference data quality issues, centralising reference data management and enhancing validation processes without requiring coding.
Ab Initio automatically generates realistic test data while masking sensitive information. The software creates data sets that adhere to referential integrity, allowing developers to work with high-quality test data without data access challenges. It also enables easy reuse of real application data for testing by capturing data snapshots from live applications.
The Ab Initio rule-authoring environment facilitates easy rule definition and testing. Users can step through data records to analyse rule calculations and perform automated regression tests across large datasets, all without writing any code.
Ab Initio optimises application performance through automation, allowing non-developers to handle large datasets efficiently. The software automatically determines optimal processing strategies, such as parallel execution and pushdown opportunities, enabling applications to run quickly and effectively.
Ab Initio captures input and output data from successful application runs, saving them as test cases. Automated testing identifies discrepancies without requiring coding, with unit tests easily orchestrated through command line and Jenkins integration.
Ab Initio automates data pipelines by reading incoming data and applying semantic analysis to validate data quality. Automated processes enrich data with business terms, mask sensitive information, and integrate it into data lakes or warehouses. While requiring upfront investment, this automation greatly enhances agility and productivity.
Ab Initio fits into modern IT environments by integrating with provisioning tools like Ansible, Chef, and Puppet. It allows for quick deployment of containerised environments across various platforms, streamlining the software deployment process.
Ab Initio’s centralised data catalog simplifies data access across fragmented sources, allowing users to work with unified logical datasets. The technology adapts to underlying data changes, enabling seamless integration and management without users needing to understand specific data storage technologies.
Ab Initio integrates with DevOps tools like Jenkins and Kubernetes to facilitate automated CI/CD pipelines. Trigger events initiate containerised build-and-test sequences, identifying issues early in development and enabling rapid updates with confidence that no regressions occur.
Data Catalog, Quality & Governance
Data is a vital asset, yet many organisations struggle to identify what data they have, its location, content, ownership, quality, and relationships. Ab Initio addresses this by offering an integrated technology platform for data cataloguing, quality management, PII management, and governance. This foundation enables businesses to automate tasks like self-service data provisioning and supports enterprise services such as Business Intelligence applications, empowering users with reliable and trustworthy data.
Explore Ab Initio’s Governance, Quality, and Catalog Capabilities
Ab Initio’s advanced data discovery capabilities utilise semantic discovery and machine learning algorithms to automatically inventory data content. This reveals data characteristics and relationships, significantly reducing project timelines—transforming lengthy cataloging efforts into mere weeks. The integrated technology also supports the autogeneration of data quality rules and enhances data protection and self-service ingestion.
Ab Initio’s virtual data hub provides logical access to siloed data across various repositories, making it appear as a single source to users. It optimises data operations using pushdown and parallel processing, ensuring secure data integration while adhering to permission controls and automatically masking sensitive information.
Ab Initio empowers data users with self-service data onboarding, enabling authorised personnel to quickly integrate new datasets without lengthy approval processes. The software ensures data protection by masking sensitive information and supports agile access to data while maintaining full audit trails of user actions.
Ab Initio’s data quality solution facilitates enterprise-wide management and accountability for data quality. Data stewards can implement and monitor controls, reducing false positives and prioritising fixes based on financial impact. The system allows for consistent data quality across formats and technologies, enabling real-time and batch processing.
Ab Initio provides a robust metadata management platform, including business glossaries, stewardship, and reference data management. It democratises access to metadata, allowing users of all skill levels to engage with data governance, reducing reliance on specialists and fostering trust in organisational data.
Ab Initio automates the discovery and deployment of data quality rules by linking physical data to logical terms. This significantly reduces the effort required to manage data quality, allowing companies to focus on more complex issues while automatically addressing reference data quality concerns.
Ab Initio offers a comprehensive suite for PII data protection, automatically identifying and classifying sensitive data. Users can define protection rules, and the software supports techniques like masking and tokenisation, ensuring compliance and safeguarding data during testing and cloud transfers.
Ab Initio automates the classification of data, saving significant time and enhancing understanding of its meaning and context. Using machine learning algorithms, it proposes relationships and semantic meanings for datasets, facilitating automation in data quality rule generation and self-service data ingestion.
Ab Initio provides detailed enterprise lineage, tracking data from its origin to its destination. It offers both business-friendly and technical lineage views, enabling users to visualise data flows and quality, automate updates, and investigate quality issues efficiently.
Ab Initio supports governance initiatives and regulatory compliance by providing self-documenting metadata for data management activities. It allows organisations to manage authoritative data sources for reports and ensures visibility into data quality and lineage, supporting compliance with regulations like GDPR and CCPA.
Data Catalog, Quality & Governance
Ab Initio supports a wide range of data sources and formats, continually expanding with each release.
Key supported areas include:
Databases:
Major options like Snowflake, Google BigQuery, Oracle, SQL Server, and various legacy systems.
Files and Objects:
Compatibility with file systems across Linux, Unix, Windows, and cloud storage services like Amazon S3 and Azure Blob Storage.
Data Formats:
Support for simple to complex formats such as XML, JSON, and various industry standards.
Queues, Messaging, and APIs:
Integration with technologies like Kafka, REST, SOAP, and various messaging systems.
Change Data Capture:
Options for major databases like DB2 and Oracle.
Applications:
Compatibility with platforms like Salesforce, SAP, and Microsoft Excel.