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ease
features
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support

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Description

BigBI empowers data professionals to create robust big data pipelines in an interactive and efficient manner, all without requiring any programming skills. By harnessing the capabilities of Apache Spark, BigBI offers remarkable benefits such as scalable processing of extensive datasets, achieving speeds that can be up to 100 times faster. Moreover, it facilitates the seamless integration of conventional data sources like SQL and batch files with contemporary data types, which encompass semi-structured formats like JSON, NoSQL databases, Elastic, and Hadoop, as well as unstructured data including text, audio, and video. Additionally, BigBI supports the amalgamation of streaming data, cloud-based information, artificial intelligence/machine learning, and graphical data, making it a comprehensive tool for data management. This versatility allows organizations to leverage diverse data types and sources, enhancing their analytical capabilities significantly.

Description

MLlib, the machine learning library of Apache Spark, is designed to be highly scalable and integrates effortlessly with Spark's various APIs, accommodating programming languages such as Java, Scala, Python, and R. It provides an extensive range of algorithms and utilities, which encompass classification, regression, clustering, collaborative filtering, and the capabilities to build machine learning pipelines. By harnessing Spark's iterative computation features, MLlib achieves performance improvements that can be as much as 100 times faster than conventional MapReduce methods. Furthermore, it is built to function in a variety of environments, whether on Hadoop, Apache Mesos, Kubernetes, standalone clusters, or within cloud infrastructures, while also being able to access multiple data sources, including HDFS, HBase, and local files. This versatility not only enhances its usability but also establishes MLlib as a powerful tool for executing scalable and efficient machine learning operations in the Apache Spark framework. The combination of speed, flexibility, and a rich set of features renders MLlib an essential resource for data scientists and engineers alike.

API Access

Has API

API Access

Has API

Screenshots View All

No images available

Screenshots View All

Integrations

Apache Cassandra
Apache Hive
Hadoop
Amazon EC2
Amazon Redshift
Amazon S3
Apache HBase
Apache Kafka
Apache Kudu
ArangoDB
Elasticsearch
Google Cloud BigQuery
Java
Kubernetes
MapReduce
MongoDB
Python
R
Salesforce
Scala

Integrations

Apache Cassandra
Apache Hive
Hadoop
Amazon EC2
Amazon Redshift
Amazon S3
Apache HBase
Apache Kafka
Apache Kudu
ArangoDB
Elasticsearch
Google Cloud BigQuery
Java
Kubernetes
MapReduce
MongoDB
Python
R
Salesforce
Scala

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

BigBI

Founded

2019

Country

Israel

Website

bigbi.io

Vendor Details

Company Name

Apache Software Foundation

Founded

1995

Country

United States

Website

spark.apache.org/mllib/

Product Features

Business Intelligence

Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Natural Language Generation (NLG)
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics

ETL

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

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Alternatives

Alternatives

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