Xaqt

FEBRUARY 6, 2020

Back then, Artificial Intelligence, APIs, Robotic Process Automation (RPA), and even "Big Data" weren't things yet. The topics de jour were web services, service orientated architectures (SOA), Computer Telephony Integration (CTI), SIP was coming of age, and analytics for the sake of analytics.

Contact Center 52

Contact Center Enterprise Call Center APIs 52

AWS Machine Learning

JANUARY 26, 2024

Define strict data ingress and egress rules to help protect against manipulation and exfiltration using VPCs with AWS Network Firewall policies. He is passionate about building secure and scalable AI/ML and big data solutions to help enterprise customers with their cloud adoption and optimization journey to improve their business outcomes.

Best practices 123

Best practices Government Engineering Accountability 123

Enghouse Interactive

JULY 10, 2018

Contact Babel 2017 DMG says, “It can be stated with some confidence that first-contact resolution is seen as the key to a successful contact center: 76% of the report’s respondents place first-contact resolution as being one of the top 3 metrics that are most influential on customer satisfaction, with 31% stating it as being no.1.”.

Self service 40

Self service CRM Contact Center Analytics 40

AWS Machine Learning

DECEMBER 18, 2023

Among all, the native time series capabilities is a standout feature, making it ideal for a managing high volume of time-series data, such as business critical application data, telemetry, server logs and more. With efficient querying, aggregation, and analytics, businesses can extract valuable insights from time-stamped data.

Finance 105

Finance APIs Analytics Scripts 105

AWS Machine Learning

JANUARY 4, 2024

Today, a large amount of data is available in traditional data analytics, data warehousing, and databases, which may be not easy to query or understand for the majority of organization members. In entered the Big Data space in 2013 and continues to explore that area. Arghya Banerjee is a Sr.

Best practices 120

Best practices Enterprise Engineering APIs 120

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 78

Metrics Scripts Enterprise Telecommunications 78

aircall

APRIL 16, 2021

Establish performance metrics (response time, retention, engagement, etc.). SaaS works well for a variety of general use cases, including: Data backup. Big data analytics. Flexibility – SaaS uses an open API (application programming interface) technology. 8) Failing to track metrics.

SaaS 62

SaaS Sales Coaching APIs 62

AWS Machine Learning

JULY 25, 2022

For production, we wanted to invoke the model as a simple API call. We found that we didn’t need to separate data preparation, model training, and prediction, and it was convenient to package the whole pipeline as a single script and use SageMaker processing. With other standard metrics, the improvement ranged from 50–130%.

Scripts 70

Scripts Engineering Analytics APIs 70

Xaqt

JUNE 22, 2020

The innovation quagmire in the Call Center Reporting and Analytics space is rooted in three key issues: Vendor's who's contact center suites are an amalgamation of various acquisitions, such as: Cisco, Avaya, Genesys, NICE and Verint have done a poor job of providing integrated data and reporting across their own portfolios.

Call Center 52

Call Center Contact Center Analytics Engineering 52

AWS Machine Learning

JUNE 15, 2022

Edge is a term that refers to a location, far from the cloud or a big data center, where you have a computer device (edge device) capable of running (edge) applications. How do I eliminate the need of installing a big framework like TensorFlow or PyTorch on my restricted device? Edge computing.

Transportation 76

Transportation APIs Big data Wireless 76

AWS Machine Learning

SEPTEMBER 9, 2022

Prior to our adoption of Kubeflow on AWS, our data scientists used a standardized set of tools and a process that allowed flexibility in the technology and workflow used to train a given model. As we noted in the previous section, data scientists perform exploratory data analyses, run data analytics, and train ML models.

Engineering 76

Engineering Healthcare APIs Scripts 76

SmartKarrot

JUNE 23, 2020

So much so, that now behavioural data and behavioural analytics are considered the secret ingredients for product led growth. . But what are behavioural data and behavioural analytics? . Behaviour data is essential for behaviour analysis. It helps organise, segment and make sense of your raw behavioural data.

Analytics 10

Analytics SaaS Upselling Entertainment 10

aircall

MARCH 19, 2021

With all the available customer data companies have at their disposal to enhance the performance of customer service, sales, and marketing efforts, a remarkable 73% of companies still do not use it effectively. And out of those who do practise data collection, only 12% analyze it. Best Practices of Customer Data Management.

Sales 62

Sales CRM Marketing Best practices 62

AWS Machine Learning

JUNE 24, 2022

The model training step could be either one training job, if the data scientist is aware of the best model configuration, or a hyperparameter optimization (HPO) job, in which AWS defines the best hyperparameters for the model (Bayesian method) and produces the corresponding model artifact. Data lake and MLOps integration.

Enterprise 90

Enterprise Engineering Accountability APIs 90