Introducing OpenText Core Analytics Database: Optimize server costs for cloud data warehousing 

OpenText Core Analytics Database introduces innovative cloud database architecture for scalable, cost-effective data management.

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Steve Sarsfield

April 15, 20242 minute read

Cloud data warehouses and data lakes offer a powerful way to perform analytics that includes scalability, cost-efficiency, performance, and accessibility. Customers look for platforms that easily scale resources up or down based on demand and allow them to manage their data workloads more flexibly and cost-effectively compared to traditional on-premises solutions. Cloud data warehouses simplify data management by providing maintenance, security, and compliance features, reducing the burden on IT teams.  

In CE 24.2, we’re announcing a new analytics cloud database. OpenText Core Analytics Database was developed as a response to conventional data warehousing and management models that are costly and environmentally unfriendly. By building a system that will efficiently deal with massive amounts of real-time data while using minimal CPU resources, we will deliver better data analytics. 

Data storage and computation are separated in OpenText Core Analytics Database, a revolutionary architecture. This separation allows the system to fully utilize the cloud’s elasticity, scalability, and flexibility, providing a solution that accommodates varied workload demands without compromising speed or efficiency. Users, data, and workloads can be scaled independently while maintaining optimal performance. In this way, OpenText underscores its commitment to offering its clients comprehensive and cost-effective data management solutions. 

Data management is becoming more inclusive and sustainable as traditional barriers like prohibitive cloud infrastructure costs and rigid server requirements are dismantled. This development represents a philosophical shift towards recognizing and addressing the impact of digital technologies on the environment. The future of analytics seems bright. 

OpenText provides built-in support for SQL, Python, time-series, and geospatial features, as well as machine-learning capabilities within the database. Accessing and querying structured and semi-structured data in a unified system without compromise opens up new possibilities for data analytics, enabling insights and efficiencies previously unattainable. 

Cloud data warehousing and data lakes have evolved significantly since the early launch of cloud solutions for analytics. OpenText has redefined what is possible in data management not only through optimizing server costs and embracing the cloud’s inherent flexibility but also by setting a new standard for sustainability and efficiency.

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Steve Sarsfield

Steve Sarsfield, a thought leader and author within the data management world, currently works in product marketing for OpenText Analytics and AI. With a rich background that spans executive roles at notable companies such as Cambridge Semantics, Hewlett Packard Enterprise, and Talend, Steve brings a wealth of industry experience to his position. Steve’s book “The Data Governance Imperative” is a seminal work which explores the crucial collaboration between business and IT to tackle complex business challenges.

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