This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Das Format Business Talk am Kudamm in Berlin führte ein Interview mit Benjamin Aunkofer zum Thema “BusinessIntelligence und Process Mining nachhaltig umsetzen”. 3 – Bei der Nutzung von Daten fallen oft die Begriffe „Process Mining“ und „BusinessIntelligence“. Für Data Science ja sowieso. Umsatz-Forecasts.
The excitement is building for the fourteenth edition of AWS re:Invent, and as always, Las Vegas is set to host this spectacular event. The sessions showcase how Amazon Q can help you streamline coding, testing, and troubleshooting, as well as enable you to make the most of your data to optimize business operations.
The company developed an automated solution called Call Quality (CQ) using AI services from Amazon Web Services (AWS). In this post, we demonstrate how the CQ solution used Amazon Transcribe and other AWS services to improve critical KPIs with AI-powered contact center call auditing and analytics.
IoT solutions as well as BusinessIntelligence tools are widely used by companies all over the world to improve their processes. Usually, companies choose a platform provided by one of the most well-known vendors like Amazon (AWS), Google Cloud, or Microsoft Azure. Businessintelligence tools can help you with this task.
Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL, businessintelligence (BI), and reporting tools. Choose the us-east-1 AWS Region in which to create the stack. Choose Submit.
The analyst will also be able to quickly create a businessintelligence (BI) dashboard using the results from the ML model within minutes of receiving the predictions. In the review page, scroll down to the Capabilities section, and select I acknowledge that AWS CloudFormation might create IAM resources. Choose Create stack.
Amazon Web Services (AWS) has created yet another wave in artificial intelligence (AI) with its new generative AI-powered assistant, Amazon Q. This new AI tool is launched in three variations – Q Developer, Q Business, and Q Apps – catering to the varied needs of businesses, developers, and app builders.
We can also gain an understanding of data presented in charts and graphs by asking questions related to businessintelligence (BI) tasks, such as “What is the sales trend for 2023 for company A in the enterprise market?” AWS Fargate is the compute engine for web application.
Because Amazon Bedrock is serverless, you don’t have to manage infrastructure, and you can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with. AWS Prototyping developed an AWS Cloud Development Kit (AWS CDK) stack for deployment following AWS best practices.
With the right strategy, these intelligent solutions can transform how knowledge is captured, organized, and used across an organization. To help tackle this challenge, Accenture collaborated with AWS to build an innovative generative AI solution called Knowledge Assist.
In this post, we demonstrate how data aggregated within the AWS CCI Post Call Analytics solution allowed Principal to gain visibility into their contact center interactions, better understand the customer journey, and improve the overall experience between contact channels while also maintaining data integrity and security.
Rocket Mortgage, America’s largest retail mortgage lender, revolutionizes homeownership with Rocket Logic – Synopsis, an AI tool built on AWS. This post offers insights for businesses aiming to use artificial intelligence (AI) and cloud technologies to enhance customer service and streamline operations.
Such infrastructure should not only address these issues but also scale according to the demands of AI workloads, thereby enhancing business outcomes. Native integrations with IBM’s data fabric architecture on AWS establish a trusted data foundation, facilitating the acceleration and scaling of AI across the hybrid cloud.
Amazon Redshift: Amazon Redshift is a cloud-based data warehousing service provided by Amazon Web Services (AWS). It integrates seamlessly with other AWS services and supports various data integration and transformation workflows. Looker: Looker is a businessintelligence and data visualization platform.
In addition to BusinessIntelligence (BI), Process Mining is no longer a new phenomenon, but almost all larger companies are conducting this data-driven process analysis in their organization. For analysis the way of BusinessIntelligence this normalized data model can already be used. Click to enlarge!
“During the preview, early indications signaled Amazon Q could help our customers’ employees become more than 80% more productive at their jobs; and with the new features we’re planning on introducing in the future, we think this will only continue to grow,” shared Dr. Swami Sivasubramanian, vice president of Artificial Intelligence and Data at AWS.
In this post, we share AWS guidance that we have learned and developed as part of real-world projects into practical guides oriented towards the AWS Well-Architected Framework , which is used to build production infrastructure and applications on AWS. To learn more, see Log Amazon Bedrock API calls using AWS CloudTrail.
With generative AI on AWS, you can reinvent your applications, create entirely new customer experiences, and improve overall productivity. You can use this post as a reference to build secure enterprise applications in the Generative AI domain using AWS services. An Amazon Simple Storage Service (Amazon S3) bucket.
To create and share customer feedback analysis without the need to manage underlying infrastructure, Amazon QuickSight provides a straightforward way to build visualizations, perform one-time analysis, and quickly gain business insights from customer feedback, anytime and on any device. The Step Functions workflow starts.
Reduced operational overhead – The EMR Serverless integration with AWS streamlines big data processing by managing the underlying infrastructure, freeing up your team’s time and resources. Runtime roles are AWS Identity and Access Management (IAM) roles that you can specify when submitting a job or query to an EMR Serverless application.
Visualization – Generate businessintelligence (BI) dashboards that display key metrics and graphs. The following screenshot shows an example request prompt taken from the Amazon Bedrock playground on the AWS Management Console. You can also consider alternate services such as AWS Step Functions or AWS Batch.
To address this challenge, AWS recently announced the preview of Amazon Bedrock Custom Model Import , a feature that you can use to import customized models created in other environments—such as Amazon SageMaker , Amazon Elastic Compute Cloud (Amazon EC2) instances, and on premises—into Amazon Bedrock.
Modern Cloud Analytics (MCA) combines the resources, technical expertise, and data knowledge of Tableau, Amazon Web Services (AWS) , and our respective partner networks to help organizations maximize the value of their end-to-end data and analytics investments. Core product integration and connectivity between Tableau and AWS.
Modern Cloud Analytics (MCA) combines the resources, technical expertise, and data knowledge of Tableau, Amazon Web Services (AWS) , and our respective partner networks to help organizations maximize the value of their end-to-end data and analytics investments. Core product integration and connectivity between Tableau and AWS.
Amazon’s AWS Glue is one such tool that allows you to consume data from Apache Kafka and Amazon-managed streaming for Apache Kafka (MSK). You can also configure a cloud-based tool like AWS Glue to connect with your on-premise cloud hardware and establish a secure connection. A three-step ETL framework job should do the trick.
Modern Cloud Analytics (MCA) combines the resources, technical expertise, and data knowledge of Tableau, Amazon Web Services (AWS) , and our respective partner networks to help organizations maximize the value of their end-to-end data and analytics investments. Core product integration and connectivity between Tableau and AWS.
Amazon Lookout for Metrics is a fully managed service that uses machine learning (ML) to detect anomalies in virtually any time-series business or operational metrics—such as revenue performance, purchase transactions, and customer acquisition and retention rates—with no ML experience required. Following is a brief overview of each service.
The application of Artificial intelligence and BusinessIntelligence in affiliate marketing has been actively discussed for quite a time. In AI it refers to computer intelligence, while in BI it is about smart decision-making in business influenced by data analysis and visualization. BusinessIntelligence.
It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing businessintelligence (BI) tools. AWS offers tools such as RStudio on SageMaker and Amazon Redshift to help tackle these challenges. I acknowledge that AWS CloudFormation might create IAM resources with custom names.
Data Warehousing ist seit den 1980er Jahren die wichtigste Lösung für die Speicherung und Verarbeitung von Daten für BusinessIntelligence und Analysen. Delta Lake baut auf Apache Spark auf und ist auf mehreren Cloud-Plattformen verfügbar, darunter AWS, Azure und Google Cloud Platform. So basieren z.
In our recent webcast , IBM, AWS, customers and partners came together for an interactive session. In this session: IBM and AWS discussed the benefits and features of this new fully managed offering spanning availability, security, backups, migration and more. Where can I provide feedback? Scalability 5. . Amazon RDS
Across 180 countries, millions of developers and hundreds of thousands of businesses use Twilio to create personalized experiences for their customers. As one of the largest AWS customers, Twilio engages with data, artificial intelligence (AI), and machine learning (ML) services to run their daily workloads.
. “The media and entertainment industry has undergone a significant digital transformation, with viewers consuming content across different devices and platforms,” said Vitaly Tsivin, EVP BusinessIntelligence at AMC Networks. The solution will also be available in AWS Marketplace.
This post was co-written with Anthony Medeiros, Manager of Solutions Engineering and Architecture for North America Artificial Intelligence, and Blake Santschi, BusinessIntelligence Manager, from Schneider Electric. He specializes in delivering high-value AI/ML initiatives to many business functions within North America.
In this post, we describe how AWS Partner Airis Solutions used Amazon Lookout for Equipment , AWS Internet of Things (IoT) services, and CloudRail sensor technologies to provide a state-of-the-art solution to address these challenges. This protocol is used to feed sensor data into a CloudRail edge gateway and loaded into AWS IoT Core.
Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for businessintelligence. Downtime, like the AWS outage in 2017 that affected several high-profile websites, can disrupt business operations.
This can enable the company to leverage the data generated by its IoT edge devices to drive business decisions and gain a competitive advantage. AWS offers a three-layered machine learning stack to choose from based on your skill set and team’s requirements for implementing workloads to execute machine learning tasks.
This allows you to create unique views and filters, and grants management teams access to a streamlined, one-click dashboard without needing to log in to the AWS Management Console and search for the appropriate dashboard. On the AWS CloudFormation console, create a new stack. amazonaws.com docker build -t. docker tag :latest.dkr.ecr.us-east-1.amazonaws.com/
Industry-recognised certifications, like IBM and AWS, provide credibility. Additionally, familiarity with Machine Learning frameworks and cloud-based platforms like AWS or Azure adds value to their expertise. Key Features: In-Depth AWS Training: Learn about AWS Glue, Athena, Redshift, and more. Who is a Data Analyst?
The import job copies all the model artifacts from the user’s account into an AWS managed S3 bucket. When the import job is complete, the fine-tuned model is made available for invocation from your AWS account. Additionally, all data (including the model) remains within the selected AWS Region. This is an asynchronous method.
The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements. ETL is one of the most integral processes required by BusinessIntelligence and Analytics use cases since it relies on the data stored in Data Warehouses to build reports and visualizations.
As part of this post, we provide the prompts used to solve the tasks and discuss architectures to integrate these results in your AWS Contact Center Intelligence (CCI) workflows. Prerequisites For this post, make sure that you have set up an AWS account with appropriate resources and permissions.
Inconsistent or unstructured data can lead to faulty insights, so transformation helps standardise data, ensuring it aligns with the requirements of Analytics, Machine Learning , or BusinessIntelligence tools. AWS Glue AWS Glue is a fully managed ETL service provided by Amazon Web Services.
We organize all of the trending information in your field so you don't have to. Join 17,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content