Suppliers Singapore Everlytics Data Science

	Everlytics Data Science
HQ Location	Singapore
HQ City	Singapore
Year Founded	2009
Company Type	Private
Revenue	< $10m
Employees	11 - 50
Website	Open website

Everlytics Data Science

HQ Location

Singapore

HQ City

Singapore

Year Founded

2009

Company Type

Private

Revenue

< $10m

Employees

11 - 50

Website

Open website

Company Description	A team of responsive and collaborative individuals with strong background in Data Science. Clients engage Everlytics to architect and develop solutions that have Big Data and/or Machine Learning as differentiating components. Everlytics has the required competency to manage challenges in collating data from disparate sources and build a scalable analytics platform. Read More
IoT Solutions	Predictive Analytics for Everyone Everlytics simplifies statistical modelling and predictive sciences by handling the intricacies and providing their clients complete directional control over the solution. Through years of collective experience, Everlytics can translate business problems into analytics-enabled solutions by arriving at the optimal design and approach to the problem, choosing the right modelling techniques and keeping the end solution highly relevant and actionable. Machine Learning on Big Data Building a Big Data ecosystem is not only creating a system where terabytes of data can be stored and queried in seconds. It also involves using that processing power to build innovative Machine Learning solutions to predict future outcomes. All big data tools offer libraries to do Machine Learning tasks. Everlytics is an expert in using such tools, as well as improvising them and building new algorithms, Big Data Backends Companies adopt Big Data not because they want to but they have to as traditional systems cannot handle the processing speeds and volumes that Big Data tools can. Our clients rely on us for architecting and implementing their Big Data platforms. A typical engagement starts with consulting on the appropriate tech stack. For example, • Which MPP backend is suitable for storing and querying millisecond level financial ticker data? • The right storage and query engine (OLTP & OLAP) for big data graphs? • Index and search terabytes of textual data in subseconds. Etc. Read More Log in to view content
Contents

Company Description

A team of responsive and collaborative individuals with strong background in Data Science. Clients engage Everlytics to architect and develop solutions that have Big Data and/or Machine Learning as differentiating components. Everlytics has the required competency to manage challenges in collating data from disparate sources and build a scalable analytics platform.

IoT Solutions

Predictive Analytics for Everyone Everlytics simplifies statistical modelling and predictive sciences by handling the intricacies and providing their clients complete directional control over the solution. Through years of collective experience, Everlytics can translate business problems into analytics-enabled solutions by arriving at the optimal design and approach to the problem, choosing the right modelling techniques and keeping the end solution highly relevant and actionable. Machine Learning on Big Data Building a Big Data ecosystem is not only creating a system where terabytes of data can be stored and queried in seconds. It also involves using that processing power to build innovative Machine Learning solutions to predict future outcomes. All big data tools offer libraries to do Machine Learning tasks. Everlytics is an expert in using such tools, as well as improvising them and building new algorithms, Big Data Backends Companies adopt Big Data not because they want to but they have to as traditional systems cannot handle the processing speeds and volumes that Big Data tools can. Our clients rely on us for architecting and implementing their Big Data platforms. A typical engagement starts with consulting on the appropriate tech stack. For example, • Which MPP backend is suitable for storing and querying millisecond level financial ticker data? • The right storage and query engine (OLTP & OLAP) for big data graphs? • Index and search terabytes of textual data in subseconds. Etc.

Everlytics Data Science is a provider of Industrial IoT application infrastructure and middleware, and analytics and modeling technologies.

Technologies

Analytics & Modeling

Big Data Analytics

Predictive Analytics

Application Infrastructure & Middleware

Data Visualization

Everlytics Data Science’s Technology Stack maps Everlytics Data Science’s participation in the application infrastructure and middleware, and analytics and modeling IoT technology stack.

Application Layer
Functional Applications

Cloud Layer
Platform as a Service

Infrastructure as a Service

Edge Layer
Automation & Control

Processors & Edge Intelligence

Actuators

Sensors

Devices Layer
Robots

Drones

Wearables

Supporting Technologies
Analytics & Modeling

Application Infrastructure & Middleware

Cybersecurity & Privacy

Networks & Connectivity

Technological Capability

None

Minor

Moderate

Strong

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	Connectedthinks Industrial data platformThe ConnectedThinks Industrial data platform is capable of connecting to multiple industrial data sources, correlating and transforming the data into useful insights, and helping improve the efficiency of your industrial business.Edge ConnectorsThe edge-connectors suite is a middleware deployable on ARM or X86-based Industrial edge IoT gateways. It enables quick connection and rapid onboarding of various assets such as machinery, sensors, asset trackers, Bluetooth beacons, and IP Video streams as well as OT assets such as PLC, SCADA, CNC, and HMI – to name a few. It offers secure device management and remote connection. Data PlatformThe ConnectedThinks data platform is a modern technology stack, built-to-scale to ingest and process high-speed, high-density, and real-time industrial data. Its functionality could be split into 3 primary parts – the data-ingest, the data-transform-&-store, and the data-query part.The data-ingest part consists of a high-performant MQTT broker and a highly-scalable, multi-cluster Kafka messaging queue which together can ingest and process data at a very high speed.The data-transform-&-storage part is built on top of Kafka KSQLdb and Apache Spark with real-time data transformation and the ability to integrate real-time machine-learning predictions for Anomaly Detection and other Predictive Maintenance tasks. The platform offers out-of-the-box connectors to store data on almost any database, data warehouse, or even into S3-storage compatible Data Lakes with efficient storage formats like PARQUET and AVRO.The data-query part consists of multiple custom-built connectors to various SQL and pseudo-SQL databases and storages along with highly-scalable PRESTO (a.k.a prestodb)Together it forms a complete Industry 4.0 offering for data intelligence and integration. The entire offering is built with Microservices and dockerized to make it suitable for deployment on-prem, private-cloud, or Public Cloud like AWS, Azure, or Google. Data visualization & BIConnectedThinks platform offers a custom-built visualization engine, built from the ground up to serve the specific requirements of industrial operations which demand a combination of real-time diagnostic monitoring for high-speed data, a SCADA-like monitoring system with visual aids and historical data analytics with data ranging from a few weeks to couple years. It is built on top of front-end REACT-js libraries along with Authentication and fine-grain access Authorization to deliver a secure web portal that is accessible from any corner of the world. The platform is also pre-integrated with Apache Superset and offers embedded dashboards as well as quick drag-and-drop data exploration. The prestodb query engine ODBC connectors enable you to import and explore data from your existing BI solutions such as Tableau, Looker, PowerBI, etc,

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Everlytics Data Science

IoT Snapshot

Technology Stack

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