IBM Netezza “appliances” are now part of IBM PureSystems and the IBM PureSystems for Analytics has recently seen the announcement of a new offering in this category: the IBM Integrated Analytics System. These offerings maintain the same key design tenents from Netezza for ease of use, performance, scalability and embedded analytics. IBM Integrated Analytics System drives the insights needed to maintain your competitiveness. It matches accelerated development and deployment times for your data scientists with a high performance, optimized and cloud-ready data platform.
During the webinar, we will highlight 6 reasons clients prefer IBM Integrated Analytics Systems:
- High-speed architecture – Uses a massively parallel processing (MPP) architecture to provide operational efficiency and low latency.
- Common SQL engine – The technology decouples the analytics application and data storage, enabling applications to work transparently with on-premise, cloud, RDBMS, NoSQL and Hadoop data sources.
- Embedded Spark processing with machine learning – Embeds Apache Spark processing to provide higher performance. Models can be deployed directly where the data resides, reducing data processing that would impact performance and increase complexity.
- Built-in tools for data scientists – Use Jupyter Notebooks or the built-in Data Science Experience feature to quickly connect to system data and begin modeling immediately. Data scientists can access data regardless of location or data type. This allows them to maximize the value of their models by using the right data.
- Easy to manage and maintain – Simplifies the management of your analytics system by reducing the maintenance required for tuning, indexing or aggregated tables.
- Cloud-ready with scalable deployment – Scale up to petabyte levels. Flexible configurations allow you to expand computing and storage capacity independently, and scale your workload as needed. Workloads required to be in the cloud can also be moved without application rewrites.
REGISTER NOW & invite your colleagues. We look forward to virtually meeting you.