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Amazon QuickSight, Business Analytics Service: Hyperscale unified business intelligence

What is Amazon Quicksight?

You may utilize Amazon QuickSight, a cloud-scale business intelligence (BI) tool, to provide your colleagues with clear insights no matter where they are. Data from several sources is combined via Amazon QuickSight, which links to your data in the cloud. QuickSight can combine data from AWS, third parties, spreadsheets, SaaS, B2B, and other sources into a single data dashboard. As a fully managed cloud-based solution, Amazon QuickSight offers built-in redundancy, worldwide availability, and enterprise-grade security. You can scale from 10 users to 10,000 with its user-management features, and you won’t need to deploy or manage any infrastructure.

QuickSight provides a visual environment that allows decision makers to examine and analyze information. Any device on your network, including mobile devices, can safely access dashboards.

Amazon QuickSight BI

Created with all end users in mind

Answers with pertinent visuals can be provided to end users in organizations who ask queries in natural language.

Analysts for business

Business analysts don’t need client software or server infrastructure to generate and distribute pixel-perfect dashboards and visualizations in a matter of minutes.

With strong AWS APIs, developers can scale and implement integrated analytics for apps with hundreds or thousands of users.

Managers

QuickSight adapts to the demand automatically, allowing administrators to deliver constant performance. Because of its pay-per-session model, QuickSight is affordable for both small and large-scale implementations.

What Makes QuickSight Unique?

Individuals inside your company make decisions that impact your company on a daily basis. They can take the decisions that will steer your business in the right path if they have the proper information at the right time.

For analytics, data visualization, and reporting, Amazon QuickSight offers the following advantages:

Pay just for the things you use.

Add tens of thousands of users.

It’s simple to incorporate statistics to make your apps stand out.

All users can enable BI with QuickSight Q

The response time of the SPICE in-memory engine is lightning fast.

The total cost of ownership (TCO) is inexpensive and there are no license fees up front.

Analytics for collaboration without requiring the installation of an application.

Consolidate several data sources into a single study.

Share your analysis as a dashboard by publishing it.

Activate the dashboard’s functions.

You can avoid managing fine-grained database permissions because dashboard visitors can only see the content you share.

More capabilities are available for more experienced users with QuickSight Enterprise edition

Includes the following additional enterprise security features:

Single sign-on (IAM Identity Center), federated users, and groups using AWS Directory Service for Microsoft Active Directory, SAML, OpenID Connect, or Identity and Access Management (IAM) Federation.

Specific authorization to access AWS data.

Row-level protection.

At-rest, extremely safe data encryption.

Access to Amazon Virtual Private Cloud data as well as on-premises data

For users assigned to the “reader” security role dashboard subscribers who view reports but do not generate them it provides pay-per-session pricing.

Enables you to integrate QuickSight with your own apps and websites by implementing dashboard sessions and console analytics incorporated.

Enables value-added resellers (VARs) of analytical services to use our business’s multitenancy features.

Allows you to write dashboard templates programmatically so they may be shared across different AWS accounts.

Organizes and manages access more easily with shared and private folders for analytical resources.

More frequent scheduled data refreshes and higher data import quotas for SPICE data intake are made possible.

Watch the video below for a two-minute overview of Amazon QuickSight and to find out more. All the pertinent information is in the audio.

Amazon Q in QuickSight

With the help of your generative AI helper, gain insights more quickly and make smarter decisions.

For everyone, generative business intelligence

Make decisions more quickly and increase company efficiency with QuickSight’s Generative BI features, which are powered by Amazon Q. With dashboard-authoring capabilities, business analysts can quickly create, discover, and disseminate insightful information through natural language prompts. Make data easier for business users to grasp with configurable data stories, executive summaries, and a context-aware Q&A experience that uses insights to guide and influence choices.

Visual dashboards that are dynamic and created by you

It’s simple to create impressive dashboards by using natural language to express your goals. You can use natural language prompts to create, find, hone, and share valuable insights in a matter of minutes.

Use your data to create intriguing narratives

Produce eye-catching documents and presentations that make your data come to life. Highlight important discoveries, clearly communicate complicated concepts, and provide doable next steps to advance your company.

Your Q&A experience was transformed

Investigate your data with confidence outside of the constraints of pre-made dashboards. Suggested inquiries, data previews, and support for ambiguous searches make it simple to find important insights in your data.

More methods QuickSight’s Amazon Q provides faster insights.

Quickly create intricate computations

It’s no longer necessary to commit syntax to memory or look up computation references. Amazon Q makes it easy and uncomplicated to build computations using natural language.

Produce executive summaries in real time

Create executive summaries, period-over-period changes, and important insights quickly from anywhere on your dashboard with Amazon Q.

Amazon Q in QuickSight benefits

Get more done with AI

Business users can quickly create, find, and share actionable insights with Amazon Q’s Generative BI features in QuickSight. When new queries arise, users don’t have to wait for BI teams to update dashboards. Self-serve querying, automated executive summaries, and interactive data storytelling with natural language prompts are all made feasible by generative BI. By rapidly creating and improving computations and graphics, business analysts can increase productivity with Generative BI.

Ensure privacy and security

With security and privacy in mind, Amazon Q was created. It can comprehend and honor your current governance identities, roles, and permissions to tailor its interactions. Amazon Q is made to satisfy the most exacting business needs in QuickSight. Users cannot access data within Amazon Q if they are not allowed to do so without it. No one other than you can utilize your data or Amazon Q inputs and outputs to enhance models of Amazon Q.

Utilize AI analytics to empower everyone

Amazon Q in QuickSight makes it easy and clear for anyone to confidently understand data. AI-driven analytics enable data-driven decision-making for everyone with easily accessible and actionable insights, regardless of experience level. Even ambiguous questions in natural language are addressed with thorough, contextual responses that provide detailed explanations of data together with images and anecdotes to ensure that everyone can examine the information and comprehend it more thoroughly.

Amazon QuickSight pricing

Amazon QuickSight on the Free TierPRODUCTDESCRIPTION FREE TIER OFFER DETAILS PRODUCT PRICINGAmazon QuickSightFast, easy-to-use, cloud-powered business analytics service at 1/10th the cost of traditional BI solutions.30 Days Free10 GB of SPICE capacity for the first 30 days for free for a total of 4 usersAmazon QuickSight Pricing

AWS Console to Code

AWS Console-to-Code, which makes it simple to turn AWS console actions into reusable code, is now generally available (GA). When you launch an Amazon Elastic Compute Cloud (Amazon EC2) instance, for example, you can record your actions and workflows in the console using AWS Console-to-Code. You can then evaluate the AWS Command Line Interface (AWS CLI) commands for your console actions.

Using the infrastructure-as-code (IaC) format of your choosing, such as the AWS CloudFormation template (YAML or JSON) or the AWS Cloud Development Kit (AWS CDK) (TypeScript, Python, or Java), Amazon Q can generate code for you with a few clicks. This may be included into pipelines, further tailored for your production workloads, and utilized as a foundation for infrastructure automation.

Customers have responded well to AWS Console-to-Code since it revealed the preview last year. Since it has been working backwards from customer feedback, it has been significantly enhanced in this GA version.

GA’s new features

Encouragement of additional services Amazon EC2 was the sole service that was supported during the preview. Amazon Relational Database Service (RDS) and Amazon Virtual Private Cloud (Amazon VPC) are now supported by AWS Console-to-Code at GA.

Simplified experience: Customers can now more easily handle the workflows for prototyping, recording, and code creation with the updated user interface.

Preview code: Customers can now create code for EC2 instances and Auto Scaling groups without actually establishing them with updates to the launch wizards.

Advanced code generation: Amazon Q machine learning models power the creation of code for AWS CDK and CloudFormation.

How to begin using AWS Console-to-Code

Let’s start with a straightforward example of starting an Amazon EC2 instance. Open the Amazon EC2 console first. To begin recording, find the AWS Console-to-Code widget on the right and select Start recording.

Next, use the Amazon EC2 console’s launch instance wizard to start an Amazon EC2 instance. To finish the recording, select Stop once the instance has been launched.

Examine the recorded actions in the Recorded actions table. To filter by write actions (Write), utilize the Type dropdown list. Select the action RunInstances. To copy the relevant AWS CLI command, select Copy CLI.

It is simple to change this command. For this example, You can modify it to start two instances (–count 2) of type t3.micro (–instance-type). Although this is a simplified example, other workflows can use the same method.

You can use AWS CloudShell to run the command, and it launched two t3.micro EC2 instances as planned:

The API commands used when actions were conducted (during the EC2 instance launch) form the basis of the single-click CLI code creation experience. It’s intriguing to see that when you finish operations in the console, the companion screen displays the recorded actions. Additionally, it is simple to clearly scope activities for prototyping because of the interactive user interface’s start and stop capabilities.

Creating IaC with AWS CDK

An open-source framework called AWS CDK is used to specify cloud architecture in code and provision it using AWS CloudFormation. You may create AWS CDK code for your infrastructure workflows with AWS Console-to-Code. Currently available in Java, Python, and TypeScript.

Let’s move on to the use case for the EC2 launch instance. Locate the AWS Console-to-Code widget on the right side of the Amazon EC2 console, select Start recording, and then start an EC2 instance if you haven’t already. Once the instance has started, select the RunInstances action from the Recorded actions table and select Stop to finish the recording.

Select the Generate CDK Python button from the dropdown menu to begin generating AWS CDK Python code.

You can modify the code to make it production-ready for your particular use case, or you can use it as a starting point.

You made a new Python CDK project since you already had the AWS CDK installed:

Then entered the code that was generated into the Python CDK project. To make sure the code was correct for this example, modified the EC2 instance type, refactored the code into an AWS CDK Stack, and made a few other little adjustments. Using CDK deploy, was able to deploy it successfully.

You can replicate the same outcome by launching an EC2 instance from the console action and then going all the way to the AWS CDK.

Additionally, you can create CloudFormation templates in JSON or YAML format:

Preview code

Additionally, you may use the Preview code capability in Amazon EC2 and the Amazon EC2 Auto Scaling group launch experience to directly access AWS Console-to-Code. This implies that you can obtain the infrastructure code without actually creating the resource.

Try this out by following the instructions to use a launch template to build an Auto Scaling group. But click Preview code rather than Create Auto Scaling group. The options to replicate the AWS CLI command or produce infrastructure code should now be visible to you.

Things to be aware of

When using AWS Console-to-Code, keep the following points in mind:

To create AWS CLI commands for their infrastructure operations, anyone can use AWS Console-to-Code. There is a free monthly limit of 25 generations for the code generation feature for AWS CDK and CloudFormation formats; after that, an Amazon Q Developer subscription is required.

Prior to deployment, it is advised that you test and validate the generated IaC code.

Only actions in the Amazon EC2, Amazon VPC, and Amazon RDS consoles are recorded by AWS Console-to-Code at GA.

Actions from past sessions or other tabs are not retained by the Recorded actions table in AWS Console-to-Code; it only shows actions made within the current browser tab. Keep in mind that all recorded actions will be lost once the browser tab is refreshed.

Currently accessible

All commercial regions offer AWS Console-to-Code. The Amazon Q Developer user manual contains additional information about it. Try it out in the Amazon EC2 console and email the AWS re:Post for Amazon EC2 or your regular AWS Support contacts with your thoughts.

Amazon Web Services, En Yetenekli Üretken Yapay Zeka Destekli Asistanı Amazon Q’yu Genel Kullanıma Sundu Amazon Q, Amazon Q Developer ile geliştiricilerin zaman ve emek tasarrufu elde etmesini desteklerken, Amazon Q Business’ın yeni özelliği Amazon Q Apps, çalışan...

Amazon Web Services (AWS) just introduced Amazon Q, a super smart AI assistant that helps make software development faster and easier. This awesome tool not only writes precise code, but it also helps with testing, fixing errors, and planning out complicated tasks. It can even help with things like updating Java and adding new code. Plus, Amazon Q makes it simple to access important company information, like rules and product details, by organizing and analyzing data.

AWS also came out with Amazon Q Apps, a cool feature that lets employees create their own AI apps using company data. All they have to do is describe what they want the app to do, and Amazon Q will make it happen. This makes work faster and more efficient!

Dr. Swami Sivasubramanian, who is in charge of AI and data at AWS, said that Amazon Q is the best because it's super accurate, has really smart features, and is super secure. It's going to make developers and business people way more productive.

Amazon Q Developer is another great tool that helps developers and IT professionals with lots of different tasks. It can help with coding, testing, updating apps, and making the most of AWS resources. It even has special features like giving great coding suggestions, doing tasks on its own, and keeping everything safe and secure.

AWS Supply Chain’s four new capabilities optimize supply chains with Amazon’s nearly 30 years of experience, managed service resilience, security, and business continuity. The 2024 capabilities will improve data lake, demand planning, and ML insights. AWS Supply Chain offers manufacturers and upstream supply chain processes like supplier orders supply planning, collaboration, sustainability, and generative AI.

Customers can forecast, plan, position, and replenish components and finished goods with AWS Supply Chain Supply Planning to reduce inventory costs and respond faster to demand changes and supply disruptions. Two, AWS Supply Chain N-Tier Visibility streamlines customer-multiple-tier supplier supply plan and demand change communication. Customers can securely collaborate with trading partners within clicks. Third, AWS Supply Chain Sustainability will centralize sustainability data request, collection, and audit. Finally, Amazon Q in AWS Supply Chain uses generative AI to summarize inventory, demand variability, and scenario tradeoffs.

AWS Supply Chain improves inventory visibility, minimises stock-outs and overstocks that damage consumer trust and raise carrying costs. AWS Supply Chain’s Demand Planning improves demand forecasts with Amazon’s supply chain and ML expertise. Machine learning-based AWS Supply Chain Insights recommends inventory and lead-time risk mitigation for customer supply chain data. Normalize ERP customer data with AWS Supply Chain. Customers want more upstream AWS Supply Chain Demand Planning and Insights support. Due to customer demand, 4 new capabilities were announced today.

They impress customers with supply chain management. Diego Pantoja-Navajas, vice president of AWS Supply Chain, said industry-leading analytics and ML help customers track and plan products from manufacturing to distribution. Inventory visibility, supply chain risk mitigation, cost reduction, and customer satisfaction improve with AWS Supply Chain. Generative AI-powered Amazon Q in AWS Supply Chain answers complex supply chain questions.

Enhanced upstream capabilities improve AWS Supply Chain visibility and insights

Supply chain leaders serve manufacturers, distributors, retailers, and suppliers. Integration of trading partners’ data stores often requires expensive customizations, long development cycles, or manual workarounds. Forecasts, order confirmations, shipment quantities, etc. are reconciled by supply planners. Siloed data, demand variations, supply disruptions, and vendor lead-time uncertainty make demand forecasting and inventory optimization difficult for many companies. Prices and availability of raw materials and components plague manufacturers.

Trading partner responses to customer data requests vary in quality, frequency, timeliness, and structure and are not always tracked or audited. Carbon emissions and hazardous materials have been reported via email, fax, and messaging apps without tracking or auditing. Many companies struggle to meet demand or stricter regulations with enough goods on time. Today, AWS Supply Chain helps customers manage their upstream supply chain, forecast materials and inventory, confirm supplier supply plans and commitments, and get accurate environmental data.

AWS Supply Chain Supply Planning’s advanced facility inventory prediction models use Amazon’s ML expertise. Supply Planning uses AWS Supply Chain Demand Planning demand forecasts, product, facility, BOM, and inventory data. Purchase orders and inventory transfer requests let customers order, store, and choose unit quantities.

Customers see their direct and multiple external trading partners with AWS Supply Chain N-Tier Visibility. Add trading partners with few clicks. Automation improves trade partner forecasting and communication. AWS Supply Chain N-Tier Visibility monitors trading partner inventory, demand forecasts, and purchase orders. Export purchase orders and supply plans to Amazon S3 for ERP integration. Chat and messaging from AWS Supply Chain simplify collaboration. Inventory managers can notify AWS Supply Chain of late component shipments. Shared supplier and manufacturer data helps customers identify sourcing risks and component shortages and reduce disruptions.

Sustainability professionals can securely access supplier network data and documents with AWS Supply Chain Sustainability. These customers can request, collect, and export product life cycle assessments, safety certificates, and hazardous substance reports through the supply chain. Customers can upload their own data collection form for suppliers to document sustainability issues, use a standard workflow process to remind them to respond, and communicate changes based on supplier responses. This feature lets customers report ESG compliance in one auditable document.

Customers can query supply chain data with generative AI

Customer want to easily identify causal relationships between factors that affect their supply chain decisions, such as demand fluctuations and supply disruptions, but it takes time and effort to gather and analyze data from many sources. Visualizing and trading complex supply chains is difficult. Without data, supply chain leaders plan and position inventory. Amazon Q in AWS Supply Chain answers data analysis and supply chain decision questions in natural language, boosting customer productivity.

Amazon Q, powered by Amazon Bedrock, intelligently answers AWS Supply Chain Data Lake “what?”, “why?”, and “what if?” questions using a natural language interface. Customers can customize Amazon Q to see complex supply chain tradeoffs. Customer asks AWS Supply Chain, “What is the financial impact of delayed replenishment orders in the Southeast?” “8 delayed replenishment orders could deplete 20 regional fast-moving products,” Q said. Revenue will drop $150K due to delay.”

Clients may ask “Why are we not moving product from other regions to make up this shortfall?” Amazon Q said network inventory is low next week. Customers ask, “What if I expedite air freight orders?” Amazon Q says, “Air freight typically arrives in 2 days and could reduce revenue impact by $95K, but adds $2.4K in expedite costs.” Amazon Q’s fast, accurate responses help supply chains.

BCG is an AWS strategic partner. BCG and AWS balance agility, resilience, service, cost, and sustainability to grow supply chains. Drake Watten, BCG managing director and partner, said the partnership deploys, scales, and promotes AWS supply chain solutions. “We are supporting projects with the generally available capabilities and preparing customers for the upcoming AWS Supply Chain releases that will improve material, component, and finished goods planning, partner management, and supply chain management with generative AI.”

The leading independent material-handling equipment supplier and rental source, Equipment Depot, has over 50 branches and 850 technicians. Equipment Depot Operations director Joakim Langkaas is excited to work with AWS on a massive digital transformation strategy for rapid growth. “AWS Supply Chain will improve inventory, planning, and data-driven supply decisions. Demand Planning, Supply Planning, and Insights predict low inventory and OEM delays and make real-time recommendations to improve service, customer experience, and equipment downtime. The early adopter of this technology expects these new capabilities to help their teams place parts on time.

Woodside is creative and determined in Australia. From WA to the Gulf, Woodside powers homes, lights, and industry. “They remote locations prevent us from using supply chain processes like overnight shipment of spare parts, so they rely on stocking the right parts across they warehouse network and leveraging multiple modes of transport to support they operated facilities,” said Woodside Energy Supply Chain vice president Tracey Simpson they shared vision with AWS Supply Chain improved supply chain visibility for they company.

Order Insights’ proactive order status, delivery issues, and recommendations should boost system and workflow efficiency if scaled. Rescheduling maintenance and reducing material expedites should help business. They are also excited about AWS Supply Chain‘s next phase, which includes advanced supply planning, partner collaboration, and generative AI to improve supply chain performance.

Amazon are excited  to introduce to you today Amazon Q, a new generative AI-powered personal assistant that can be customized for your company and is meant for work. By connecting to the code, data, enterprise systems, and information repositories of your organization, Amazon Q enables you to engage in dialogues, solve issues, produce content, acquire insights, and take action. Amazon Q gives staff members quick access to pertinent information and guidance to help them complete activities more quickly, make decisions and solve problems more quickly, and encourage creativity and innovation at work.

With Amazon Q’s user-based plans, you may customize the product’s features, cost, and options to suit your needs. Based on your company’s current identities, positions, and permissions, Amazon Q can customize its interactions for every single user. Amazon Q user content is never used by AWS to train the underlying models. Put another way, your company’s information is kept secret and safe.

Your go-to source for business advice is Amazon Q

Let’s examine a few instances of how business customers can employ straightforward natural language suggestions from Amazon Q to accomplish tasks. As a marketing manager, you could ask Amazon Q to summarize a press release, use the release as the basis for an email draft. For example, Amazon Q looks through internal style requirements while searching your company’s content to deliver a response that adheres to your brand standards.

Subsequently, you may request that Amazon Q create customized social media prompts to share your tale on all of your accounts. You can later ask Amazon Q to evaluate your campaign’s outcomes and compile a summary for leadership evaluations.

You can restrict irrelevant topics, set the context for responses, and decide whether to supplement responses with information from the underlying model or solely use reliable company information when responding as an administrator. Hallucinations, a prevalent problem where the underlying model provides responses that sound convincing but are based on misread or nonexistent data, are mitigated by limiting responses to trusted company information.

How to customize Amazon Q for your company

Go to Amazon Q in the console, pick Applications from the left menu, and then click Create application to customize Amazon Q for your company.

The workflow that follows is now underway.

Step 1: Make an application. Give your application a name, and select or create an AWS Identity and Access Management (IAM) service role that already exists that Amazon Q is permitted to take on. Select Create after that.

Step 2: Choose the retriever. During a chat, a retriever retrieves data in real time from the index. You have two options: use a current Amazon Kendra retriever or use the native Amazon Q retriever. The data sources that are supported by Amazon Q can be accessed by the native retriever. You can link the related data sources to your Amazon Q application by selecting the current Amazon Kendra retriever if you currently use Amazon Kendra. you choose to use the native retriever. Select Next after that.

Step 3: Assemble data sources. Connectors for widely used data sources and enterprise systems are pre-installed on Amazon Q.

Once the retriever displays the correct number of documents and the data source sync has finished successfully, you can test the online experience and initiate a chat. Keep in mind that depending on the volume and size of data to index, the data source sync may take a few minutes to several hours.

Plugins that control access to enterprise systems, such as Salesforce, Jira, Zendesk, and ServiceNow, can also be connected. Using plugins, Amazon Q can carry out user-requested operations like generating support tickets and estimating sales.