Brightics AI, A to Z of Data Analytics
Anyone can build analytics models and work with others seamlessly using intuitive, easy-to-use modeling tools and functions without specialized DS knowledge or scripting.
Share your models and reports with ease. Operationalize insights right away to enable actions on site and facilitate teamwork on Brightics AI platform.
Collect, analyze, operationalize and assess data non-stop. View and manage the entire life cycle of data manipulation process from data preparation, model building, analysis, to results exporting.
Flexible, easy-to-use image and video search functionality drives efficiency in a variety of sectors from financial services, manufacturing to government.
Brightics AI was designed with our customer’s needs in mind. Its analytic, voice recognition, and visual AI services are applicable to a diverse range of industry sectors.
* Click each Brightics AI module to view detailed information.
Data Hub
Data Preparation
Standardizes and integrates data by utilizing features for collecting, storing, converting, and searching for data, and provides an intuitive, efficient, and automated operation management solution for utilizing the data for the intended purposes.
Machine Learning
Supports high-performance analytics functions based on various languages, such as Scala, Python, R, and SQL, provides recommendations for optimal algorithms matching the data characteristics and supports automatic analysis simulation environments to provide data high-performance, architecture-based machine learning services that are scalable.
Deep Learning
Provides features for analyzing unstructured data utilizing the deep learning technology, which allows you to extract the required information from unstructured data, filter the information, and understand the characteristics of the information.
Aanlytics Services
Expert data analysts from Samsung SDS will cultivate the potentials of your data and provide specialized analytics services for you.
Data Hub
Provides a distributed file system incorporating Apache Hadoop and Hadoop Ecosystem as the platform for storing and processing big data.
5,361
No. of the
registered users
21,108
No. of Brightics
Studio downloads
61
No. of the
registered
use case
1,377,410
No. of tutorial views
299,662
No. of downloads
of tutorials
of analytics models
Manufacturing site intelligence based on an integrated AI platform
Throughout all stages of the manufacturing process, various data collection, processing, and optimal analysis models are developed, and field engineers are trained as AI experts through systematic training, and the AI development process at the manufacturing site is standardized and systemized. Through this, customers have improved quality by improving the sorting power of outgoing products and reduced cost by reducing the disposal rate.
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
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
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
Analyze error cause of conveyance equipment
Conveyance logistics and equipment operation loss will be minimized by reducing the response time to operation errors through the equipment event and the automatic cause analysis of errors based on log and reducing the reoccurrence rate of errors through the management for frequent errors.
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
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
Brightics AI enables deep-learning analysis of ECG(Electrocardiogram) data that is collected by wearable device in order to classify highly sensitive and diverse arrhythmia with high accuracy. Hospitals and research institutes can use these result in heart disease diagnosis and clinical studies.
Brightics AI Video Tutorial for easy learning and excellent utilization
