Brightics Machine Learning

An integrated data analytics platform - Accelerate digital transformation with data analytics

A wide range of automated analytics features empower anyone to develop and use AI analytics service easily and with speed

Brightics Machine Learning recommends the most optimized algorighm depending on the characteristics of data, which enables anyone to start data analytics. By providing Alaytics App functions with more strengthened utilization of the analytics results, it is possible to provide the high-performance AI platform services for the entire analytics stages.

Major Services

  • Fast, efficient analytics platform service with user convenient automation features and various pre-built models

  • Instant insights based on prebuilt analytics models from field-proven best practices

    Prebuilt analytics models from best practices proven in the fields allow you to secure data-based insights faster than anyone else, because they can be instantly applied to your business.

  • High-speed processing and visualization of large data

    Brightics Machine Learning can quickly process large amounts of data and present the results in a chart. It supports rendering of data with up to 100 million rows.

  • Recommend the most optimized analytics model

    Even expert analysts can benefit from the recommendations. Optimal algorithms for the analysis environment and data guarantee easy modeling for the best analysis results.

  • Provide automated analytics guideline

    The detailed instructions explaining the analysis process in each stage allows anyone to analyze data with excellent results.

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Videos

AI-based big data analytics platform, Samsung SDS Brightics AI

You don't have to be a data expert: Based on Brightics Machine Learning, anyone can easily do data analytics through analytics models that can be utilized in various industries.

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Analyst Reports

  • IDC MarketScape: Asia/Pacific (Excluding Japan) AI Life-Cycle Software Tools and Platforms 2022 Vendor Assessment (Doc # AP48940522, October 2022)

    IDC MarketScape: Asia/Pacific (Excluding Japan) AI Life-Cycle Software Tools and Platforms 2022 Vendor Assessment (Doc # AP48940522, October 2022), IDC

  • MarketScape Asia/Pacific (Excluding Japan) Vision AI Software Platform 2021 Vendor Assessment

    MarketScape Asia/Pacific (Excluding Japan) Vision AI Software Platform 2021 Vendor Assessment, IDC

  • Magic Quadrant for Data Science and Machine Learning Platforms, 2021, Gartner

    Magic Quadrant for Data Science and Machine Learning Platforms, 2021, Gartner

    in Magic Quadrant for Data Science and Machine Learning Platforms, March 2021

    in Magic Quadrant for Data Science and Machine Learning Platforms, March 2021, Gartner


    Learn more

  • in The Forrester Wave™ : Multimodal Predictive Analytics and Machine Learning, Q3 2020

    in The Forrester Wave™ : Multimodal Predictive Analytics and Machine Learning, Q3 2020, Forrester

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Use Cases

    • Predict product sales
      By predicting demands and sales of products, sales can be optimized. Through more accurate prediction of sales, the promotiion effects can also be analyzed.

      [Values for business]
      - Optimize sales and preemptive market response through demands/sales prediction
      - Anlyze promotion effects through accurate sales prediction
      - Calculate product life cycle and adjust launching period for new products based on the sales trend in the past & plan promotion
      Learn more

    • Analyze market response
      It is possible to quickly find out about the market response by analyzing positive/negative feedback from customers based on buzz words arisen from SNS.

      [Values for business]
      - Find out about causes of customers' negative opinions regarding brands, product categories based on buzz words arisen from SNS / Manage product quality with prompt response
      - Analyze buzz words and influencers from SNS, news and tech forums

      ※ Buzz words: customers' opinions about products, which can be found online including SNS, news and tech forums
      Learn more

    • Predict visitors by store
      The customer satisfaction can be improved by establishing efficient workforce plans through prediction of the number of visitors to the store, optimizing the workforce allocation based on the customer visit patterns and analyzing customer behavior data.

      [Values for business]
      - Predict the total sales amount by studying the prediction results of the number of visitors, labor cost and the conversion rate (CVR) / Reduce 11% of topportunity/loss cost of sales
      - Improve operation effiviency by optimizing workforce allocation based on the customer visit patterns / Improve customer satisfaction through data analytics on customer behavior
      Learn more

    • Analyze marketing effects
      It is possible to not only measure the degree of the sales influence depending on marketing activities but establish marketing plans depending on the investment size by promotion by establishing data-analytics-based marketing decision making schemes.

      [Values for business]
      - Measure modeling-based investment performance
      - Predict the degree of sales increment influence and ROI depending on marketing activities
      - Measure performance of promotions by product/transaction channel
      - Establish data-analytics-based marketing decision making schemes
      - Investment size/mix depending on marketing activities and promotion purposes

    • Customized recommendation
      It is possible to provide customized services by predicting the preference of products/ad by customer. The customer satisfaction will be improved and the marketing targeted based on customers will be available.

      [Values for business]
      - Developing engines that recommend customization by predicting consumers' preference and suggesting highly preferred items
      - By realizing algorithms that provides recommendations based on customization, utilizing the analytics results for customized recommendation businesses (e.g. products, ad) by combining with IoT in the future
      - Expect the improved satisfaction by recommending based on customization through Prescriptive Analytics
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    Features

    • Provide visualized analytics environment

      Without complicated coding, the drag & drop function visualizes the workflow. This also enables to have a glimpse of input/output data and applied algorithms, which helps on-site/industry experts easily analyze data.

    • Recommend the most optimized algorithm

      By providing the most optimized algorithm for data and functions that suggest algorithms to suggest proper parameters, on-site experts can easily do modelling. This can minimize trial and error in the course of finding the most optimized model and learning factors.

    • Provide automated analytics guideline

      By providing the service of Guided Analytics that explains the analytics courses in each stage in detail, users can easily analyze difficult data while following the guideline stage by stage.

    • Prompt serving of analytics results

      It is possible to immediately edit and serve analytics results as a report. By registering the scheduler, automatic updates are supported. Users can quickly check out the data and report that they want whenever.

    Specifications

    Recommended specifications
    • Machine learning analytics platform

      x86 server with 3 or more nodes
      -CPU: 8 cores/Node
      -Memory: 16GB/Node
      -Disk: 100GB/Node
      -Operating system: Linux 64bits

    • PC for platform users

      - Browser : Chrome (Version 50.0 or higher)
      - Screen resolution: 1280 x 900 (recommended)

    • Supported data source

      RDB, File, HDFS

    • Supported analytics script

      Scala, SQL, R, Python

    • API

      REST API

    • Appropriate cloud environments

      SDS Cloud, Amazon Web Service, MS Azure, Google Cloud, etc.

    Documentations

    자료 더보기
    Let’s talk

    Whether you’re looking for a specific business solution or just need some questions answered, we’re here to help

    Brightics AI is an AI-powered analytics platform designed to provide an integrated environment for fast and accurate business analytics. It covers the entire lifecycle of data from data collection and analysis to utilization by using different modules including data preparation, machine learning, and deep learning. It allows everyone to easily perform structured and unstructured data analysis, build analytics models and work with others seamlessly using intuitive, easy-to-use modeling tools and functions without specialized data science knowledge or scripting. Brightics AI has more than 100 references across various industries, including manufacturing, marketing, logistics, security, and healthcare. Brightics AI represents one of Samsung SDS’s five key technology areas — AI, blockchain, cloud, data analytics and security (ABCDS) and can be complemented with other proprietary offerings, such as Samsung Cloud and Brightics IoT.

    Disclaimer : Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. 

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