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What is ZetaAnalytics?

In order to make the most of the ZetaAnalytics product, having a compatible database appliance is vital for setting up the Data Warehouse. Landmark has confirmed that the ZetaAnalytics software works seamlessly with various systems, such as Teradata, EMC Greenplum, and IBM Netezza; for the most current approved versions, consult the ZetaAnalytics Release Notes. Before installing and configuring the ZetaAnalytics software, it is imperative to verify that your Data Warehouse is operational and ready for data exploration. As part of the installation process, you will need to run scripts that establish the necessary database components for Zeta within the Data Warehouse, which requires access from a database administrator (DBA). Furthermore, ZetaAnalytics depends on Apache Hadoop for both model scoring and streaming data in real time, meaning that if you haven't already set up an Apache Hadoop cluster in your environment, you must do so prior to running the ZetaAnalytics installer. During the installation, you will be asked to input the name and port number of your Hadoop Name Server along with the Map Reducer. Following these instructions carefully is essential for a successful implementation of the ZetaAnalytics product and its functionalities. Additionally, ensure that you have all required permissions and resources available to avoid any interruptions during the installation process.

What is Apache Hive?

Apache Hive serves as a data warehousing framework that empowers users to access, manipulate, and oversee large datasets spread across distributed systems using a SQL-like language. It facilitates the structuring of pre-existing data stored in various formats. Users have the option to interact with Hive through a command line interface or a JDBC driver. As a project under the auspices of the Apache Software Foundation, Apache Hive is continually supported by a group of dedicated volunteers. Originally integrated into the Apache® Hadoop® ecosystem, it has matured into a fully-fledged top-level project with its own identity. We encourage individuals to delve deeper into the project and contribute their expertise. To perform SQL operations on distributed datasets, conventional SQL queries must be run through the MapReduce Java API. However, Hive streamlines this task by providing a SQL abstraction, allowing users to execute queries in the form of HiveQL, thus eliminating the need for low-level Java API implementations. This results in a much more user-friendly and efficient experience for those accustomed to SQL, leading to greater productivity when dealing with vast amounts of data. Moreover, the adaptability of Hive makes it a valuable tool for a diverse range of data processing tasks.

Media

Media

Integrations Supported

Adobe Real-Time CDP
Apache Iceberg
Apache Impala
Apache Ranger
CelerData Cloud
Data Virtuality
Datameer
Hue
IBM watsonx.data
MLlib
Mode
Occubee
PHEMI Health DataLab
Privacera
Progress DataDirect
Protegrity
Salesforce Data 360
Secoda
SecuPi
Varada

Integrations Supported

Adobe Real-Time CDP
Apache Iceberg
Apache Impala
Apache Ranger
CelerData Cloud
Data Virtuality
Datameer
Hue
IBM watsonx.data
MLlib
Mode
Occubee
PHEMI Health DataLab
Privacera
Progress DataDirect
Protegrity
Salesforce Data 360
Secoda
SecuPi
Varada

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Halliburton

Company Website

www.halliburton.com

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

hive.apache.org

Categories and 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

Categories and Features

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

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