As the volume of data grows exponentially, organizations need a high-performance analytics database. It must not only sift through vast amounts of information in seconds to uncover real-time insights but also ensure robust security and flexibility.
Discover why enterprises choose OpenText Analytics Database for fast, scalable analytics. With built-in machine learning, robust security, flexible deployment, and low TCO, it powers data-driven decisions across industries.
Our OpenText-powered predictive maintenance system, built on vast amounts of data and advanced AI models, allows us to detect and address potential issues before they impact clinical operations. This improves the reliability of our equipment and enhances patient outcomes and satisfaction.
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With OpenText Analytics Database, Agoda can detect and remove frustrations and inefficiencies in the customer journey, crunching through billions of records in complex join patterns in a matter of seconds.
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Our OpenText platform is instrumental in many areas of our business—creating predictive algorithms, serving up product recommendations, powering insight to our mobile apps, and generating daily reports and ad hoc queries. It’s crucial for enabling us to be more agile with data.
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OpenText has drastically changed working practices for the analysts as they can now verify more hypotheses, knowing an answer will be delivered straight away. Thanks to OpenText’s incredible analytics speed, we can experiment and draw conclusions on a massive scale.
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When we experienced a data explosion following our Virgin Mobile acquisition, [OpenText Analytics Database] Eon Mode gave us the flexibility and scalability required to continue growing our business with abundance.
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Enable advanced analytics for massive datasets with OpenText Analytics Database. Solve complex challenges, uncover insights, and drive business outcomes with unmatched performance, security, and scalability.
Analyze IoT-sensor and machine data to predict equipment failure, reduce downtime, and optimize asset performance for predictive maintenance.
Run anomaly-detection models on large volumes of data to detect and prevent fraud in real time, enabling a faster response and minimizing risk.
Leverage unified customer data from multiple sources to gain a 360-degree view, enabling personalized marketing, improved service, and data-driven decision-making. Achieve better customer relationships, reduce churn, and maximize monetization.
Investigate vast amounts of market, credit, and operational data to assess risk exposure, ensure compliance with regulations (e.g., GDPR, HIPAA), and streamline reporting for audits and regulatory authorities.
Analyze massive volumes of network-performance and usage data in real time to optimize service delivery, detect anomalies, and reduce downtime.
Explore the powerful features of OpenText Analytics Database, designed to handle complex data workloads at petabyte scale across data-warehouse and data-lakehouse environments, transforming how enterprises manage and analyze data.
Efficiently stores and retrieves petabyte-scale data, delivering ultra-fast query performance, enabling real-time insights on massive datasets, and reducing the overall disk I/O requirements.
Distributes data across multiple nodes, enabling parallel processing for faster query execution, scalability, and high-performance analytics.
Unlocks immediate insights across vast datasets. OpenText Analytics Database outperforms other database providers with ultra-fast query execution to enable critical business decisions.
Runs ML models directly in-database using SQL or Python. No need to export data—train, test, and deploy models at scale. Unlock deep data insights with 650+ built-in advanced analytics functions.
Seamlessly analyzes structured and semi-structured data wherever it’s stored—in a data lakehouse, warehouse, or cloud object storage—using popular formats like Parquet, ORC, AVRO, or our native ROS.
Deploys anywhere—on-premises, in any major cloud (AWS, Azure, GCP), or hybrid environments—giving you full control over performance, cost, and data sovereignty.
Enables high-performance, multi-dimensional queries on large datasets—ideal for online analytical processing (OLAP) workloads. Support complex aggregations, drilldowns, and slice across dimensions.
Includes end-to-end encryption, role-based access control, and makes compliance with GDPR, HIPAA, and other regulatory frameworks easier.
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A data warehouse handles structured data for fast analytics. A data lakehouse combines that with the flexibility of a data lake, supporting both structured and semi-structured data—ideal for advanced analytics, AI, and simplified data architecture.
Both. It’s a unified analytics engine that supports modern data warehouse and lakehouse architectures—enabling you to store, query, and analyze data across cloud, on-premises, or hybrid environments, wherever the data resides.
Structured, semi-structured, and complex data, with advanced capabilities for handling large volumes of time-series, IoT, and machine-generated data.
OpenText Analytics Database supports flexible deployment—on-premises, in any major cloud (AWS, Azure, GCP), in hybrid environments, or via Kubernetes containers.
Yes, OpenText Analytics Database delivers real-time and near-real-time insights, ideal for time-sensitive applications like fraud detection, network monitoring, and predictive maintenance.
Our analytics database integrates with BI tools (e.g., Tableau, Power BI), data science libraries (e.g., scikit-learn), ETL tools, Kafka, Spark, and more.
Yes. OpenText Analytics Database includes built-in ML algorithms and supports Python (via VerticaPy), enabling in-database training, testing, and deployment at scale.
How AdTech leaders optimize bidding, boost performance, and wow clients with real-time analytics.
Read the blogSee how OpenText Analytics Database revolutionizes data management by enhancing the ELT process.
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