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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Fully compatible with Netezza, this solution offers a streamlined command-line upgrade option. It can be deployed on-premises, in the cloud, or through a hybrid model. The IBM® Netezza® Performance Server for IBM Cloud Pak® for Data serves as a sophisticated platform for data warehousing and analytics, catering to both on-premises and cloud environments. With significant improvements in in-database analytics functions, this next-generation Netezza empowers users to engage in data science and machine learning with datasets that can reach petabyte levels. It includes features for detecting failures and ensuring rapid recovery, making it robust for enterprise use. Users can upgrade existing systems using a single command-line interface. The platform allows for querying multiple systems as a cohesive unit. You can select the nearest data center or availability zone, specify the desired compute units and storage capacity, and initiate the setup seamlessly. Furthermore, the IBM® Netezza® Performance Server is accessible on IBM Cloud®, Amazon Web Services (AWS), and Microsoft Azure, and it can also be implemented on a private cloud, all powered by the capabilities of IBM Cloud Pak for Data System. This flexibility enables organizations to tailor the deployment to their specific needs and infrastructure.

Description

To effectively utilize the ZetaAnalytics product, a compatible database appliance is essential for the Data Warehouse setup. Landmark has successfully validated the ZetaAnalytics software with several systems including Teradata, EMC Greenplum, and IBM Netezza; for the latest approved versions, refer to the ZetaAnalytics Release Notes. Prior to the installation and configuration of the ZetaAnalytics software, it is crucial to ensure that your Data Warehouse is fully operational and prepared for data drilling. As part of the installation, you will need to execute scripts designed to create the specific database components necessary for Zeta within the Data Warehouse, and this process will require database administrator (DBA) access. Additionally, the ZetaAnalytics product relies on Apache Hadoop for model scoring and real-time data streaming, so if an Apache Hadoop cluster isn't already set up in your environment, it must be installed before you proceed with the ZetaAnalytics installer. During the installation, you will be prompted to provide the name and port number for your Hadoop Name Server as well as the Map Reducer. It is crucial to follow these steps meticulously to ensure a successful deployment of the ZetaAnalytics product and its features.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon S3
Amazon Web Services (AWS)
Arcion
Cloudera Data Platform
Coginiti
DBHawk
DbVisualizer
Digna
IBM Cloud
IBM watsonx.data
Lyftrondata
Microsoft 365
Nucleon Database Master
RazorSQL
Red Hat Cloud Suite
SAS Federation Server
Semarchy xDI
StreamFlux
Style Intelligence

Integrations

Amazon S3
Amazon Web Services (AWS)
Arcion
Cloudera Data Platform
Coginiti
DBHawk
DbVisualizer
Digna
IBM Cloud
IBM watsonx.data
Lyftrondata
Microsoft 365
Nucleon Database Master
RazorSQL
Red Hat Cloud Suite
SAS Federation Server
Semarchy xDI
StreamFlux
Style Intelligence

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/products/netezza

Vendor Details

Company Name

Halliburton

Website

www.halliburton.com

Product Features

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

Product Features

Oil and Gas

Compliance Management
Equipment Management
Inventory Management
Job Costing
Logistics Management
Maintenance Management
Material Management
Project Management
Resource Management
Scheduling
Work Order Management

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Alternatives

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