Transforming the User Experience

Integration within the Logical Data Warehouse
When your Logical Data Warehouse includes PureData System for Analytics and other data stores such as Hadoop, Spark, DB2, dashDB or Oracle, IBM Fluid Query 1.6 allows access to data across these platforms, and provides data movement capabilities. Fluid Query connects PureData System for Analytics appliances to these systems and makes queries possible against data across a Logical Data Warehouse containing any or all of these systems. IBM Fluid Query is part of the Netezza Platform Software (NPS), so existing clients can take advantage of this new capability at no cost.

The IBM PureData System for Analytics’ performance advantage over traditional custom options comes from its unique asymmetric massively parallel processing (AMPP™) architecture that combines open, IBM blade servers and disk storage with IBM's patented data filtering using Field Programmable Gate Arrays (FPGAs). This combination delivers fast query performance on analytic workloads supporting thousands of business intelligence application users, sophisticated analytics at the speed of thought, and petabyte scalability. With the new PureData for Analytics you will be able to tackle Big Data faster than ever before, with a 128-gigabyte per second effective scan rate.¹

Simplicity & Ease of Administration
The entire lifecycle of the PureData for Analytics has been simplified; from how the system is procured and deployed, to how it's managed and maintained. This results in a low cost of ownership and minimal maintenance effort. The system is up and running in hours, requires minimal up front design and tuning, and minimal ongoing administration. It provides standard interfaces to best of breed analytics, business intelligence and data integration tools; as well as easy connectivity to other big data platform components. The Netezza technology also eliminates the need for complex database management tasks such as defining and optimizing indexes and manually administering storage.

Fast Time to Value
IBM PureData System for Analytics, powered by Netezza technology, delivers high performance automatically, with no indexing or tuning required. As an appliance, all of the integration of hardware, software and storage is done for you, leading to shorter deployment cycles and industry leading time to value for BI and analytic initiatives. The appliance is delivered ready-to-go for immediate data loading and query execution and integrates with leading ETL, BI and analytic applications through standard ODBC, JDBC and OLE DB interfaces. IBM PureData System for Analytics is architected for high availability from the ground up. All components are internally redundant for a robust, production-ready environment from the moment the appliance is plugged into your data center.

IBM PureData System for Analytics dramatically simplifies analytics by consolidating all analytic activity in one place, right where the data resides. Moving analytics to the IBM PureData System is straightforward with an embedded analytic platform delivered with every appliance. With support for PMML models in the appliance itself, data modelers and quantitative teams can operate on the data directly inside the appliance instead of having to offload it to a separate infrastructure and deal with the associated data preprocessing, transformation and movement. Data scientists can build their models using all the enterprise data, and then iterate through different models much faster to find the best fit. Once the model is developed, it can be seamlessly executed against the relevant data in the appliance. Prediction and scoring can be done right where the data resides, inline with other processing, on an as-needed basis. Users can get their prediction scores in near real-time, helping operationalize advanced analytics and making it available throughout the enterprise.

The IBM Netezza Analytics built-in library of statistical and mathematical functions supports a breadth of analytic tools and programming languages. These scalable in-database analytic functions execute analytics in parallel, while abstracting away the complexity for developers, users, and DBAs. Also included are in-database geospatial analytics that are compatible with the industry-standard Esri GIS formats which enable easy integration into existing geospatial analytic environments.

Strategic analytics on enormous data volumes

Contact IBM

Considering a purchase?