AWS Machine Learning

FEBRUARY 13, 2024

Before moving to full-scale production, BigBasket tried a pilot on SageMaker to evaluate performance, cost, and convenience metrics. Use SageMaker Distributed Data Parallelism (SMDDP) for accelerated distributed training. Log model training metrics. Use a custom PyTorch Docker container including other open source libraries.

Engineering 103

Engineering Gamification Scripts Big data 103

Totango

JULY 13, 2021

Strategy for customer success growth has changed as commerce has gone digital and big data has made marketing and sales customer-centric. In order for your enterprise to survive this shift to a customer-centered market, it must become customer-centered, too. In the old days, growing your business was easy.

Customer centricity 104

Customer centricity B2C Enterprise Upselling 104

Totango

SEPTEMBER 17, 2019

With the bulk of customer value derived over years of renewal, recurring revenue enterprises have to provide new value to customers as their business grows and evolves over time. A customer data platform is fundamental to that task. Your customer data platform can collect, organize, and present information in real-time.

Metrics 64

Metrics Enterprise Big data Customer Experience 64

Totango

DECEMBER 1, 2021

An agile approach brings the full power of big data analytics to bear on customer success. This should reference your KPI metrics and lay out a path to achieve each. The post How to Bring Agile Innovation to Customer Success appeared first on Best Customer Success Blog: Articles for Enterprise Growth.

Government 99

Government Journey mapping Accountability Benchmark 99

AWS Machine Learning

OCTOBER 27, 2022

After the predictors have been created, we evaluated their quality metrics in the predictors dashboard. For customized evaluation and analysis, you can also export the forecasted values to evaluate predictor quality metrics. We use the AutoPredictor API, which is also accessible through the Forecast console.

APIs 97

APIs Best practices Metrics Government 97

ClearAction

MAY 2, 2016

Other marketing maturity models are holistic, it seems, yet the approach taken is stymied because of moving targets in emerging marketing practices, such as the advent of big data or digital marketing, which weren’t on the horizon of yesteryear. Agility = mobilize the enterprise. Marketing Maturity Model Litmus Test.

Marketing 62

Marketing Accountability Enterprise Metrics 62

ChurnZero

JULY 22, 2022

They’re an open source big data platform and the director of onboarding said, “Management wants me to build out a whole risk mitigation plan.” Maybe your company started in enterprise customers as well and is going down market. When we talk about metrics and data, that’s what you need to look at.

Gamification 98

Gamification Accountability B2B Enterprise 98

AWS Machine Learning

JULY 19, 2022

This allows us to compare the evaluation metrics of different versions of the model that are trained based on different input datasets. When the model training process is complete, we can access the evaluation metrics on the Evaluate tab on the model page. He works closely with enterprise customers to accelerate their Cloud journey.

APIs 70

APIs Metrics Enterprise Government 70

ClearAction

MAY 16, 2016

Other marketing maturity models cover the whole enchilada, so to speak, yet the approach taken is stymied because of moving targets in emerging marketing practices, such as the advent of big data or digital marketing, which weren’t on the horizon of yesteryear. Agility = mobilize the enterprise.

Marketing 54

Marketing Customer Experience Enterprise Metrics 54

Totango

SEPTEMBER 1, 2022

In addition to relying on outdated data, the traditional QBR model fails to take advantage of the latest tools for agile innovation in digital technology, AI, and big data analytics. Today’s competitive SaaS company needs a digital, data-driven, AI-powered approach to QBRs for SaaS. Reimagining the SaaS QBR .

SaaS 100

SaaS Journey mapping Upselling Best practices 100

Xaqt

FEBRUARY 6, 2020

Back then, Artificial Intelligence, APIs, Robotic Process Automation (RPA), and even "Big Data" weren't things yet. each holding a key piece of data making up the information you need to run your business efficiently. This will enable you to take the disparate applications across your enterprise and create an ecosystem.

Contact Center 52

Contact Center Enterprise Call Center APIs 52

AWS Machine Learning

JANUARY 26, 2024

Reviews can be performed using tools like the AWS Well-Architected Tool , or with the help of your AWS team through AWS Enterprise Support. Repeat this process for each of the OWASP Top 10 for LLM vulnerabilities to ensure you’re maximizing the value of AWS services to implement defense in depth to protect your data and workloads.

Best practices 126

Best practices Government Engineering Accountability 126

AWS Machine Learning

JANUARY 4, 2024

Monitoring – Logs and metrics around query parsing, prompt recognition, SQL generation, and SQL results should be collected to monitor the text-to-SQL LLM system. This is where providing vector embeddings of a centralized or unified data catalog to the LLMs results in more accurate and comprehensive information returned by the LLMs.

Best practices 122

Best practices Enterprise Engineering APIs 122

Fonolo

NOVEMBER 17, 2020

As the focus of contact center turns to creating value rather than reducing expenses, KPIs like customer satisfaction and service level will become increasingly favored over metrics like Average Handling Time. FCR is the Most Important Metric. 2016: 50% of Global 1000 companies will have stored customer-sensitive data in the cloud.

Contact Center 176

Contact Center Gamification Call Center Average Handle Time 176

Cincom

OCTOBER 14, 2020

Data has been the essential raw material used to identify market segments, market size, audience, buyer preferences, message content, contact qualification and all the other metrics and values required to market a product. Marketing is now well positioned to initiate digital transformation within the enterprise.

Marketing 52

Marketing Analytics Call Logging Enterprise 52

AWS Machine Learning

DECEMBER 21, 2022

SageMaker Feature Store automatically builds an AWS Glue Data Catalog during feature group creation. Customers can also access offline store data using a Spark runtime and perform big data processing for ML feature analysis and feature engineering use cases. Table formats provide a way to abstract data files as a table.

Scripts 73

Scripts Engineering APIs Big data 73

Voxjar

JUNE 8, 2021

My impression of Playvox is that they are targeting larger enterprises. The next two vendors will hopefully introduce you to a new approach to quality assurance in your call center, powered by artificial intelligence and big data. Playvox does offer a free trial but you have to talk to sales to get started. Playvox pricing.

Call Center 51

Call Center Analytics Enterprise Sales 51

ClearAction

MAY 3, 2019

“The goal of digital experience management is seamless, transparent and frictionless integration and optimization of customer touch-points,” explained Dennis DeGregor, author of The Customer-Transparent Enterprise. The new frontier is strategic data monetization.”. 1) Visionary Leadership. 6) Digital Empathy.

Journey mapping 48

Journey mapping Customer centricity CRM Marketing 48

AWS Machine Learning

APRIL 24, 2023

We invoke a Lambda function to validate that the training data path exists, and then trigger an Amazon Comprehend training job. If the training job is complete, we get the model metric and store it in DynamoDB for further evaluation. After the training job starts, we use another Lambda function to check the training job status.

APIs 62

APIs Customer Experience Feedback Chatbots 62

AWS Machine Learning

FEBRUARY 2, 2024

You can run the notebook pattern1-rag/notebooks/distance-analysis.ipynb to see the trends in the distance metrics over time. He is currently focused on Generative AI and plays a key role in assisting enterprises to architect and build cutting-edge solutions powered by Generative AI. He also holds an MBA from Colorado State University.

Big data 94

Big data Technology Management Engineering 94

Beyond Philosophy

DECEMBER 23, 2015

Reflective of the escalating focus on customer data, experiences, and relationships across all methods of communication and access, the role is rapidly evolving and morphing; however, there is general agreement regarding its significance in building and sustaining true value, planning capability, and enterprise customer-centricity.

Chief Customer Officer 250

Chief Customer Officer Enterprise Customer centricity Consulting 250

Natalie Petouhof

FEBRUARY 28, 2016

Managing performance and productivity in a typical enterprise is no easy task, given disparate systems, complex processes and the differences in performance metrics between roles and functions. Why Is It Important to Balance Cost, Quality and Customer Service? What Does the Scorecard Include?

Gamification 45

Gamification Management Analytics Metrics 45

ProProfs Blog

DECEMBER 11, 2020

Poor service quality can cost your business, whether you are a month old startup or a decade old enterprise. “ However, at the same time, it is also one of the CX metrics that cannot be measured straightforwardly. This metric is called CES or Customer Effort Score, and it should be as low as possible. Let’s check them out.

Metrics 78

Metrics Customer Service Surveys Customer effort 78

AWS Machine Learning

NOVEMBER 9, 2023

Conclusion Organizations often need to align with enterprise-wide toolsets to enable collaboration across different functional areas and teams. She holds a master’s degree in Computer Science specialized in Data Science from the University of Colorado, Boulder. Data Lake Architect with AWS Professional Services.

Scripts 102

Scripts Accountability Engineering Best practices 102

AWS Machine Learning

MARCH 15, 2024

He entered the big data space in 2013 and continues to explore that area. Her specialization is machine learning, and she is actively working on designing solutions using various AWS ML, big data, and analytics offerings. He also holds an MBA from Colorado State University.

Healthcare 108

Healthcare Big data Engineering Accountability 108

Natalie Petouhof

DECEMBER 8, 2015

This enables the broader sharing of resources across the bank enterprise, whether they are in a contact center or another location. For example, for mortgage appointments, customers can schedule an appointment in their preferred branch but be connected with a mortgage representative in another location via video conference.

Banking 45

Banking Enterprise Wait times Contact Center 45

AWS Machine Learning

JUNE 24, 2022

As enterprise businesses embrace machine learning (ML) across their organizations, manual workflows for building, training, and deploying ML models tend to become bottlenecks to innovation. Building an MLOps foundation that can cover the operations, people, and technology needs of enterprise customers is challenging. About the Author.

Enterprise 93

Enterprise Engineering Accountability APIs 93

Tenfold - Contact Center Blog

NOVEMBER 30, 2017

Wikibon predicted that enterprise cloud spending is growing at a 16% compound annual growth (CAGR) run rate between 2016 and 2026. This requires tracking and measuring call center metrics and key performance indicators to evaluate both agent and call center performance. This is where big data and predictive analytics come into play.

Call Center 56

Call Center Customer Support Customer centricity Contact Center 56

AWS Machine Learning

JULY 14, 2022

Without enterprise-class model monitoring , your models may be decaying in silence. Fiddler , an enterprise-class Model Performance Management solution available on the AWS Marketplace , offers model monitoring and explainable AI to help ML teams inspect and address a comprehensive range of model issues. Don’t fret. Conclusion.

Enterprise 76

Enterprise Engineering Analytics Big data 76

AWS Machine Learning

NOVEMBER 14, 2023

In the era of big data and AI, companies are continually seeking ways to use these technologies to gain a competitive edge. At the core of these cutting-edge solutions lies a foundation model (FM), a highly advanced machine learning model that is pre-trained on vast amounts of data.

Management 92

Management APIs Best practices Calibration 92

AWS Machine Learning

JULY 21, 2022

As a result, this experimentation phase can produce multiple models, each created from their own inputs (datasets, training scripts, and hyperparameters) and producing their own outputs (model artifacts and evaluation metrics). We also illustrate how you can track your pipeline workflow and generate metrics and comparison charts.

Metrics 77

Metrics Scripts Enterprise Telecommunications 77

SmartKarrot

AUGUST 12, 2021

The power of AI, ML, and big data has facilitated a decision-making metric. In contrast, decisions should depend on data. AI opens the doors for enterprises to augment their understanding of customer goals and their journeys to achieve those goals. ?Conclusion. Conclusion.

Customer Experience 11

Customer Experience Automotive Chatbots Big data 11

AWS Machine Learning

JULY 19, 2023

Best practices for managing model cards Operating in machine learning with governance is a critical requirement for many enterprise organizations today, notably in highly regulated industries. As part of those requirements, AWS provides several services that enable reliable operation of the ML environment.

Government 80

Government Best practices Metrics Enterprise 80

AWS Machine Learning

DECEMBER 1, 2022

As companies are increasingly adopting machine learning (ML) for their mainstream enterprise applications, more of their business decisions are influenced by ML models. With the SageMaker Python SDK, you can seamlessly update the Model card with evaluation metrics. He has helped set up AI/ML platforms for enterprise customers.

Government 78

Government Metrics APIs Engineering 78

AWS Machine Learning

FEBRUARY 29, 2024

framework/modelmetrics/ – This directory contains a Python script that creates an Amazon SageMaker Processing job for generating a model metrics JSON report for a trained model based on results of a SageMaker batch transform job performed on test data. The model_unit.py script is used by pipeline_service.py The pipeline_service.py

Scripts 95

Scripts Engineering Metrics Best practices 95

AWS Machine Learning

NOVEMBER 24, 2023

Both the workspace and portal are monitored using Amazon CloudWatch logs, metrics, and alarms to check key performance indicators (KPIs) and proactively notify the platform team of any issues. He has a record of working with distributed teams across the globe within large enterprises.

Engineering 74

Engineering Analytics Government Self service 74

AWS Machine Learning

AUGUST 29, 2023

Solution overview The following figure illustrates the proposed target MLOps architecture for enterprise batch inference for organizations who use GitLab CI/CD and Terraform infrastructure as code (IaC) in conjunction with AWS tools and services. The data scientist can review and approve the new version of the model independently.

Scripts 72

Scripts APIs Enterprise Accountability 72