Any Source, Any Analytics, Any Big Data Platform
Automates the complete data workflow from source to consumption
Automates delivery of data to BI and advanced analytics
Automates migration of data and workloads from legacy Data Warehouse systems to big data platforms
Automates orchestration and management of production analytics pipelines and critical infrastructure
PRODUCT CAPABILITIES
AUTOMATED DATA INGESTION
The Autonomous Data Engine automatically crawls data sources, ranging from flat files to relational databases such as Teradata, Oracle, and SQL Server.

In analogy to Google crawling the web to get web data, the Autonomous Data Engine crawls data sources and ingests source data in a high-performance, parallel process, while automatically preserving data precision.
AUTOMATED DATA SYNCHRONIZATION
The Autonomous Data Engine automatically crawls data sources, ranging from flat files to relational databases such as Teradata, Oracle, and SQL Server.

The Autonomous Data Engine continuously synchronizes source data from enterprise databases, data warehouses, and file sources. Changing data is captured from the source systems using log-based and query-based methods. The changed data is merged with the base data in a high-performance continuous merge process.

  • Automatically handles slow-changing-data and schema changes and creates current and historical tables.
  • Supports export to other enterprise operational and data warehouse systems.
  • Supports streaming, batch and incremental mode of data synchronization and export.
AUTOMATED DATA REFLECTION AND METADATA SYNCHRONIZATION
The Autonomous Data Engine learns the metadata and infers data relationships for the data ingested from external data sources as well as data sets created using Infoworks. It also tracks end-to-end data lineage so that users can trace data elements back to the original source systems and perform downstream impact analysis.
DATA TRANSFORMATION AND PREPARATION
The Autonomous Data Engine enables self-service data preparation by providing an interactive, drag-and-drop data transformation capability with support for SQL-based and other transformations.

It enables users to accelerate data preparation by working interactively with data in a collaborative, intelligent, suggestion-based user interface that reduces or eliminates dependence on IT skills. It also provides a framework to change the back-end execution engine such as Spark, Hive, Map-reduce and others, where the transformations are executed.
AUTOMATED CUBE GENERATION
The Autonomous Data Engine contains a powerful cube engine that enables users to visually design star/snowflake schemas, and build high-performance OLAP cubes. Data analysts can drag and drop facts, dimensions, and measures. It builds a fully pre-aggregated cube natively on the big data platform. The data is efficiently organized in the cube to provide sub-second response times to most user queries. An ODBC/JDBC interface is made available to the cubes enabling access from industry standard tools such as Tableau, Microsoft Power BI, Microstrategy, and other analytics tools.
MULTIPLE INTERFACES FOR HIGH-PERFORMANCE ACCESS
The Autonomous Data Engine provides business applications access to the data via multiple interfaces, thereby providing enterprises a single platform to handle multiple use cases. The data access interfaces include access through SQL, R, ODBC, and a programmatic API.
AUTOMATED WORKLOAD MIGRATION
The Autonomous Data Engine automatically migrates the workload (ETL logic, BTEQ in Teradata, SQL workloads, and other such programs) from legacy data warehouses to a big data environment. With automated data, schema and workload migration, the Autonomous Data Engine provides a comprehensive solution for data warehouse offload and migration.
ORCHESTRATION AND PRODUCTION OPERATIONS MANAGEMENT
Managing production workloads in a big data environment is complex and manually intensive. The Autonomous Data Engine automates this process with a distributed orchestrator that monitors production workloads and makes them fault tolerant, which reduces the load on system and production administrators.

Users can build end-to-end workflows and orchestrate jobs from data ingestion, synchronization, and building of data models and run the jobs in production. The Autonomous Data Engine also makes the process of migrating from a development environment to production a simple single-click operation.
ENTERPRISE-GRADE SECURITY INTEGRATION
The Infoworks platform provides security integration for user authentication and data security policies. It supports Single-sign-on/LDAP integration, Kerberos based authorization. It supports encryption for data in motion and at rest.