AWS Machine Learning

SEPTEMBER 3, 2024

Harnessing the power of big data has become increasingly critical for businesses looking to gain a competitive edge. However, managing the complex infrastructure required for big data workloads has traditionally been a significant challenge, often requiring specialized expertise.

Big data 119

Big data Engineering Accountability Real estate 119

AWS Machine Learning

SEPTEMBER 21, 2022

Until recently, organizations hosting private AWS DeepRacer events had to create and assign AWS accounts to every event participant. This often meant securing and monitoring usage across hundreds or even thousands of AWS accounts. Build a solution around AWS DeepRacer multi-user account management. Conclusion.

Accountability 93

Accountability APIs Enterprise Big data 93

AWS Machine Learning

APRIL 30, 2025

However, the journey from production-ready solutions to full-scale implementation can present distinct operational and technical considerations. For more information, you can watch the AWS Summit Milan 2024 presentation. Subhro Bose is a Data Architect in Emergent Technologies and Intelligence Platform in Amazon.

Government 71

Government Engineering Enterprise APIs 71

C3Centricity

MARCH 15, 2018

A 2015 Capgemini and EMC study called “Big & Fast Data: The rise of Insight-Driven Business” showed that: 56% of the 1,000 senior decision makers surveyed claim that their investment in big data over the next three years will exceed past investment in information management.

Big data 124

Big data Analytics Personalization Entertainment 124

C3Centricity

MAY 25, 2020

A 2015 Capgemini and EMC study called “Big & Fast Data: The rise of Insight-Driven Business” showed that: 56% of the 1,000 senior decision makers surveyed claim that their investment in big data over the next three years will exceed past investment in information management.

Technology 121

Technology Big data Analytics Personalization 121

AWS Machine Learning

MARCH 15, 2024

Healthcare organizations must navigate strict compliance regulations, such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States, while implementing FL solutions. FedML Octopus is the industrial-grade platform of cross-silo FL for cross-organization and cross-account training.

Healthcare 141

Healthcare Big data Engineering Accountability 141

Talkdesk

MAY 19, 2015

Oxford defines “big data” as “extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.” Big data is of special interest to businesses that wish to gauge their consumers’ preferences and ideas regarding customer service.

Big data 40

Big data Call Center call center software Customer Service 40

TechSee

AUGUST 7, 2024

Today, CXA encompasses various technologies such as AI, machine learning, and big data analytics to provide personalized and efficient customer experiences. Over time, additional interactive solutions like IVR systems added the ability to automate basic queries like account balances or simple troubleshooting.

Customer Experience 124

Customer Experience Customer Service Interactive Voice Response Chatbots 124

AWS Machine Learning

JULY 29, 2022

Reviewing the Account Balance chatbot. As an example, this demo deploys a bot to perform three automated tasks, or intents : Check Balance , Transfer Funds , and Open Account. For example, the Open Account intent includes four slots: First Name. Account Type. Complete the following steps: Log in to your AWS account.

Contact Center 135

Contact Center Interactive Voice Response Self service Accountability 135

AWS Machine Learning

FEBRUARY 1, 2024

Ingesting from these sources is different from the typical data sources like log data in an Amazon Simple Storage Service (Amazon S3) bucket or structured data from a relational database. In the low-latency case, you need to account for the time it takes to generate the embedding vectors.

Best practices 138

Best practices Engineering SaaS Accountability 138

AWS Machine Learning

MARCH 8, 2023

It also provides common ML algorithms that are optimized to run efficiently against extremely large data in a distributed environment. Store your Snowflake account credentials in AWS Secrets Manager. Ingest the data in a table in your Snowflake account. Launch a SageMaker Training job for training the ML model.

Scripts 134

Scripts Accountability Enterprise Management 134

AWS Machine Learning

OCTOBER 20, 2023

This framework addresses challenges by providing prescriptive guidance through a modular framework approach extending an AWS Control Tower multi-account AWS environment and the approach discussed in the post Setting up secure, well-governed machine learning environments on AWS.

Government 135

Government Engineering Accountability Enterprise 135

TechSee

OCTOBER 9, 2018

According to Accenture , Millennials have overtaken Baby Boomers as the largest consumer demographic, expected to account for 30% of retail sales — that’s $1.4 With big data and advanced analytics readily available, companies can provide Millennials with the acknowledgement they demand. Pay attention.

Customer Service 359

Customer Service Self service Virtual Agent Chatbots 359

AWS Machine Learning

OCTOBER 29, 2024

A multi-account strategy is essential not only for improving governance but also for enhancing security and control over the resources that support your organization’s business. In this post, we dive into setting up observability in a multi-account environment with Amazon SageMaker.

Government 112

Government Metrics Accountability APIs 112

AWS Machine Learning

FEBRUARY 29, 2024

In this post, we present a framework for automating the creation of a directed acyclic graph (DAG) for Amazon SageMaker Pipelines based on simple configuration files. The framework code and examples presented here only cover model training pipelines, but can be readily extended to batch inference pipelines as well.

Scripts 128

Scripts Engineering Metrics Best practices 128

AWS Machine Learning

FEBRUARY 28, 2024

Athena also allows us to use a multitude of supported endpoints and connectors to cover a large set of data sources. After we walk through the steps to build the solution, we present the results of some test scenarios with varying SQL complexity levels. Here, the output is presented to the user.

Engineering 143

Engineering Best practices Analytics Enterprise 143

AWS Machine Learning

FEBRUARY 2, 2023

Next, we present the data preprocessing and other transformation methods applied to the dataset. Finally, we present the model performance results. The data preprocessing and feature engineering was adapted from the winner of the NFL Big Data Bowl competition on Kaggle. We first describe the dataset used.

Calibration 98

Calibration Engineering Big data Automotive 98

AWS Machine Learning

AUGUST 21, 2023

In this post, we show how to use Lake Formation as a central data governance capability and Amazon EMR as a big data query engine to enable access for SageMaker Data Wrangler. Solution overview We demonstrate this solution with an end-to-end use case using a sample dataset, the TPC data model.

Engineering 98

Engineering Accountability Big data Sales 98

AWS Machine Learning

JUNE 3, 2024

We begin by understanding the feature columns, presented in the following table. To learn more about importing data to SageMaker Canvas, see Import data into Canvas. Choose Import data , then choose Tabular. After a successful import, you will be presented with a preview of the data, which you can browse.

Surveys 128

Surveys Metrics Engineering Analytics 128

AWS Machine Learning

JUNE 30, 2022

This presents an undesired threat vector for exfiltration and gaining access to customer data when proper access controls are not enforced. Studio supports a few methods for enforcing access controls against presigned URL data exfiltration: Client IP validation using the IAM policy condition aws:sourceIp.

APIs 98

APIs Enterprise Big data Accountability 98

AWS Machine Learning

FEBRUARY 13, 2024

SageMaker provides end-to-end ML development, deployment, and monitoring capabilities such as a SageMaker Studio notebook environment for writing code, data acquisition, data tagging, model training, model tuning, deployment, monitoring, and much more.

Engineering 133

Engineering Gamification Big data Scripts 133

AWS Machine Learning

AUGUST 29, 2023

The presented MLOps workflow provides a reusable template for managing the ML lifecycle through automation, monitoring, auditability, and scalability, thereby reducing the complexities and costs of maintaining batch inference workloads in production. The central model registry could optionally be placed in a shared services account as well.

Scripts 98

Scripts APIs Enterprise Accountability 98

Squelch

AUGUST 6, 2019

She currently serves as SVP of Global Customer Success at Guavus , which she describes as “a big data real-time analytics company supporting the largest and most complex data infrastructures in the world.”. I actually just presented at an AI conference recently, and I love to do things like that.

Engineering 74

Engineering Big data Analytics Technology 74

TechSee

MARCH 7, 2019

With this high turnover presenting a significant challenge to contact centers in terms of cost, productivity and morale, it is not surprising that there’s an ongoing global trend towards fostering agent development and enhancing their day-to-day activities.

Gamification 104

Gamification Contact Center Agent Empowerment Self service 104

AWS Machine Learning

JULY 29, 2022

It’s aligned with the AWS recommended practice of using temporary credentials to access AWS accounts. At the time of this writing, you can create only one domain per AWS account per Region. To implement the strong separation, you can use multiple AWS accounts with one domain per account as a workaround.

Management 101

Management APIs Accountability Construction 101

AWS Machine Learning

AUGUST 2, 2024

To overcome this limitation and provide dynamism and adaptability to knowledge base changes, we decided to follow a Retrieval Augmented Generation (RAG) approach, in which the LLMs are presented with relevant information extracted from external data sources to provide up-to-date data without the need to retrain the models.

APIs 129

APIs Analytics Chatbots Engineering 129

Answer Dash

SEPTEMBER 19, 2017

The ability for companies to collect, store, and manage vast amounts of digital information has paved the way for big data to shape corporate strategy for a variety of departments. Which leads to another challenge surrounding cognitive AI—knowing what data to collect. Then figure out what to do later.”

Customer Experience 59

Customer Experience Big data Chief Customer Officer Technology 59

AWS Machine Learning

SEPTEMBER 6, 2023

Prerequisites To try out the Amazon Kendra connector for AEM using this post as a reference, you need the following: An AWS account with privileges to create AWS Identity and Access Management (IAM) roles and policies. She is passionate about designing big data workloads cloud-natively. Choose Save or Add Secret.

Management 128

Management Enterprise Analytics Finance 128

TeamSupport

DECEMBER 6, 2019

It also launched "big data" into the mainstream, and support teams had more information about their customers than ever before. Assuming you have historical customer and data in your support software solution, machine learning can be powerful in driving interactions that matter.

B2B 80

B2B Customer Support Self service Big data 80

AWS Machine Learning

AUGUST 2, 2023

We demonstrate CDE using simple examples and provide a step-by-step guide for you to experience CDE in an Amazon Kendra index in your own AWS account. A centralized data lake with informative data catalogs would reduce duplication efforts and enable wider sharing of creative content and consistency between teams.

Enterprise 98

Enterprise Healthcare APIs Big data 98

AWS Machine Learning

FEBRUARY 21, 2023

MLOps includes practices that integrate ML workloads into release management, CI/CD, and operations, accounting for the unique aspects of ML projects, including considerations for deploying and monitoring models. In a broader model development picture, models are typically trained in a data science development account.

Best practices 98

Best practices Accountability Metrics Engineering 98

Branch Mesenger

MAY 2, 2018

Using Big Data to Make Leadership Advances in the Workplace. Back to Best Buy’s learnings they presented at the Future Miami convention earlier this year, they showed that in addition to dropping employee turnover, they also wanted to focus on retaining their best employees with newer styles of training.

Engineering 74

Engineering Morale Employee engagement Big data 74

Totango

JANUARY 26, 2021

A customer churn analysis is an investigation that uses big data analytics methods to go beyond churn rate and identify underlying factors promoting customer churn. For a comprehensive analysis, use a systematic customer churn analysis checklist that takes into account potential problems from each stage of your customer journey.

Customer retention 94

Customer retention Sales Marketing Big data 94

AWS Machine Learning

SEPTEMBER 11, 2024

SIMD describes computers with multiple processing elements that perform the same operation on multiple data points simultaneously. SIMT describes processors that are able to operate on data vectors and arrays (as opposed to just scalars), and therefore handle big data workloads efficiently. Tick 2 trade.

Benchmark 116

Benchmark Banking Analytics Big data 116

NobelBiz

APRIL 30, 2024

This evolution has been driven by advancements in machine learning, natural language processing, and big data analytics. These recommendations are highly personalized, increasing the likelihood of conversion by presenting customers with options that resonate with their specific preferences and needs.

Call Center 105

Call Center Chatbots Virtual Agent Contact Center 105

NobelBiz

APRIL 30, 2024

This evolution has been driven by advancements in machine learning, natural language processing, and big data analytics. These recommendations are highly personalized, increasing the likelihood of conversion by presenting customers with options that resonate with their specific preferences and needs.

Call Center 104

Call Center Chatbots Virtual Agent Contact Center 104

AWS Machine Learning

DECEMBER 1, 2022

The Model dashboard is a centralized repository of all models that have been created in the account. The Model dashboard offers a rich set of information regarding the overall model ecosystem in an account, in addition to the ability to drill into the specific details of a model. SageMaker Model Dashboard. Conclusion.

Government 101

Government Metrics APIs Engineering 101