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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

DataLux is an innovative platform designed for effective data management and analytics, specifically created to tackle various data-related issues while facilitating real-time decision-making. Equipped with user-friendly plug-and-play adaptors, it enables the aggregation of extensive data collections and offers the capability to collect and visualize insights instantaneously. Utilize the data lake to anticipate and drive new innovations, while ensuring that data is stored in a manner conducive to modeling. The platform allows for the development of portable applications by leveraging containerization, whether in a public cloud, private cloud, or on-premise environment. It seamlessly integrates diverse time-series market data and inferred information, including stock exchange tick data, market policy actions, relevant cross-industry news, and alternative datasets, to derive causal insights regarding stock markets and macroeconomic factors. By providing valuable insights, DataLux empowers businesses to shape their decisions and foster product innovations effectively. Additionally, it supports interdisciplinary A/B testing throughout the product development lifecycle, from initial ideation to final decision-making, ensuring a comprehensive approach to enhancing design and engineering processes.

Description

Analyzing time-series data is crucial for the daily functions of numerous businesses. Common applications involve assessing consumer foot traffic and conversion rates for retailers, identifying anomalies in data, discovering real-time correlations within sensor information, and producing accurate recommendations. With the Cloud Inference API Alpha, businesses can derive real-time insights from their time-series datasets that they input. This tool provides comprehensive details about API query results, including the various groups of events analyzed, the total number of event groups, and the baseline probability associated with each event returned. It enables real-time streaming of data, facilitating the computation of correlations as events occur. Leveraging Google Cloud’s robust infrastructure and a comprehensive security strategy that has been fine-tuned over 15 years through various consumer applications ensures reliability. The Cloud Inference API is seamlessly integrated with Google Cloud Storage services, enhancing its functionality and user experience. This integration allows for more efficient data handling and analysis, positioning businesses to make informed decisions faster.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Google Cloud Platform No 
Google Cloud Storage No 

Integrations

Google Cloud Platform Yes 
Google Cloud Storage Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person Yes 

Vendor Details

Company Name

Vivorbis

Founded

2016

Country

Hungary

Website

www.equinox.is/solutions

Vendor Details

Company Name

Google

Country

United States

Website

cloud.google.com/inference/

Product Features

Big Data

Collaboration No 
Data Blends Yes 
Data Cleansing Yes 
Data Mining No 
Data Visualization Yes 
Data Warehousing Yes 
High Volume Processing Yes 
No-Code Sandbox No 
Predictive Analytics Yes 
Templates No 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Alternatives

Alternatives

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