Name: Smart Manufacturing with AWS - Turn Data into Insights
Start: 2021-09-30T17:00:00Z
End: 2021-09-30T17:00:59.000Z
Location: BrightTALK
Rating: 0

We are advisors, engineers, and designers who deliver innovation, quality, and speed—elevating and accelerating our clients’ digital journeys. Our approach is built on a foundation of empathetic, human-focused experience design that ensures value and continuity from concept to release.

n this digital event, originally aired August 26th, we demonstrate how business leaders can modernize their data warehouse (DWH) and transform it into a scalable ecosystem of collaborating products.

Watch Yulia Sholohon, SoftServe’s Big Data Engineer, and Dilip Kikla, AWS Principal Analytics Specialist, demystify the Lake House concept and uncover a cost-saving opportunity that Amazon Redshift presents for next-gen DWHs.

Modernize with Amazon Redshift Lake House Architecture

This digital event, originally aired on July 15th, provides insights for manufacturing leaders to overcome barriers to Industry 4.0 technology adoption. Watch Douglas Bellin, AWS Business Development Lead for Industry 4.0, and SoftServe’s Principal Architecht for Data Analytics Rodion Myronov—alongside Oleksandr Yavlinsky, Retail & Supply Chain Practice Lead, discuss how manufacturing leaders can scale their efforts without prohibitive up-front investments.

We’ll also showcase a minimum viable product (MVP) for Industry 4.0 technology — powered by tried-and-trusted, modular solutions, specifically tailored for the manufacturing and CPG industry.

Join us to learn how you can drive cost optimization and increased business efficiency with a roadmap in hand.

The Road to Industry 4.0: an MVP Approach with SoftServe & AWS

In this Digital Event, originally aired on June 18, 2020, Softserve explains how Amazon SageMaker eliminates most machine learning challenges by providing a fully managed ML infrastructure, tooling, and AutoML capabilities that empower state-of-the-art ML solution delivery in a time-efficient manner—and with minimal effort. Amazon SageMaker is an end-to-end solution that assists during all stages of the ML model lifecycle.

Why join?

If you are a Geophysicist/Geologist you will learn how using ML for data interpretation can speed up your first pass seismic interpretation leading to increased productivity.

If you are a Data Scientist or IT Manager, you will learn how to set up an Amazon SageMaker environment for subsurface team members, and best practices for creating scalable systems that integrate with existing IT resources.

ML for Exploration with Amazon Sagemaker

This digital event, originally aired on May 13, 2021, explains how Amazon Forecast uses machine learning (ML) to automate and deliver highly accurate forecasts. Utilizing the same technology as Amazon itself does for its business predictions, Amazon Forecast combines ML, time series data, and variables specific to your company to build better forecasts. It unlocks insights­ that power innovation.

We showcase how one of SoftServe’s retail clients used this system to unlock working capital by decreasing inventory spend by 12%. It had zero negative impact on sales and optimized demand prediction.

Watch and learn how Amazon Forecast and ML optimize demand prediction, drive cost savings, and increase competitive strength by improving your forecast accuracy.

AWS Machine Learning Revolutionizes your Demand Prediction

In this digital event recorded on July 15, 2020—SoftServe’s Infrastructure Solution Architect, Ruslan Kusov, and AWS Solution Architect, Jay Vellore Sampathkumar, presented the positive enterprise impact that occurs when the hybrid, disaster recovery, containerization, and mobility capabilities of VMware Cloud are fully leveraged and backed by the power of AWS.

VMC & AWS: Better Together

This Webinar is a recording from June 9, 2021-
Unplanned downtime in the oil and gas industry leads to costly problems like production delays. With artificial lift downtime being a primary source of such deferred production, identifying potential problems before they occur is crucial.

By applying advanced analytics and machine learning (ML) at scale in the cloud, oil and gas companies can improve their field performance. Using asset diagnostics and acting on real-time monitoring insights, you’ll create data-driven maintenance flows, leading to an increase in production and reduced lease operating expenses.

This video explains how AWS production monitoring solutions and services like Amazon SageMaker reduce unscheduled maintenance and deferred production. These tools help you to predict suboptimal equipment performance and potential failures so you can make data-driven operational decisions.

How Machine Learning Drives Artificial Lift Performance

In this digital event recorded on September 17, 2020, data & analytics experts from SoftServe and AWS discussed how an Actionable Insights Ecosystem—anchored by AWS Redshift for EDP—enables manufacturing enterprises to unlock data value for Industry 4.0.

AGENDA AGENDA:

    WHY data humanization and democratization?
    WHAT is an Actionable Insights Ecosystem (AIE)?
    HOW an AIE, anchored by Redshift, enables SMART Manufacturing.
    Contextual storytelling based on actual case studies.
    Frequently Asked Questions.

Smart Manufacturing with AWS - Turn Data into Insights

Digital Transformation

Manufacturing

Automation

Modernization

Data Analytics

Artificial Intelligence

Big Data Analytics

Data Best Practices

Cloud Adoption

Cloud Architecture

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Cloud Computing

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Business Intelligence and Analytics

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Big Data and Data Management

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Emerging Technologies

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Smart Manufacturing with AWS - Turn Data into Insights

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