What are the benefits of using QuickSight?

What native AWS service integrations does QuickSight provide?
Amazon QuickSight provides various robust security features to safeguard data and ensure compliance standards are met. These features include role-based access control, which allows organizations to define specific permissions for different users based on their roles within the system. Integration with Active Directory allows for seamless user management and authentication processes. CloudTrail auditing helps monitor and track user activity within QuickSight for enhanced security and accountability. The platform also supports single sign-on for easier and more secure access management.

QuickSight offers the ability to set up private VPC subnets, which create an additional layer of network isolation and data protection. Data backup functionality ensures that valuable insights and information remain secure and accessible in case of unexpected data loss scenarios. QuickSight complies with various industry standards, including FedRamp, HIPAA, PCI PSS, ISO, and SOC, demonstrating its commitment to strict regulatory requirements.

The platform incorporates row-level security, enabling dataset owners to control access at a granular level based on the specific permissions associated with individual users interacting with the data. This feature enhances data protection by restricting access to sensitive information only to authorized personnel, thereby minimizing the risk of unauthorized data exposure.

How does QuickSight enable self-service BI for end users?
QuickSight enables self-service BI for end users through its Q feature. Users can ask simple questions without requiring BI training, allowing them to delve deep into data and obtain insights without extensive technical knowledge.

What ML integrations does QuickSight offer for insights?
QuickSight offers ML integrations for insights, such as Anomaly Detection, which analyzes data in real-time for anomalies and variations. It also provides the ability to forecast business metrics and run interactive what-if scenarios using machine learning capabilities.

One key feature is the inclusion of customized auto-narratives that provide context-sensitive insights, enabling users to understand the data in a clear and concise manner. Additionally, users can access ML-powered anomaly detection to continuously monitor their data for unusual patterns and outliers. The platform also offers ML-powered forecasting capabilities, allowing users to predict key business metrics.

Does QuickSight offer mobile access?
QuickSight offers mobile access through its iOS, Android, and mobile web applications. This allows users to access and interact with data on-the-go, providing flexibility and convenience.

Can QuickSight send customized email reports and alerts to end users?
Yes, QuickSight has the capability to send customized email reports and alerts to end users. This feature allows users to receive relevant updates and insights directly in their email inbox.

How does QuickSight enable the creation of customizable dashboards?
Amazon QuickSight provides a dashboard design that is pixel-perfect, allowing users to create customized, use-case-specific dashboards. In addition, the platform offers drag-and-drop interactivity, making it easy for users to build and customize visuals regardless of their experience level. Users can choose from a variety of visualizations, including charts, graphs, tables, and maps, to create compelling and informative dashboards. Moreover, Amazon QuickSight Embedded Analytics themes allow users to customize visualizations according to personal preferences and business needs, such as changing colors or adding labels for improved readability. These features ensure that users can easily tailor their visuals to meet specific requirements and create visually appealing and effective dashboards.

Can QuickSight combine data from different sources to build complex data models?
Yes, QuickSight allows users to combine data from various sources and build complex data models. This enables governed data sharing and the ability to create comprehensive data models for analysis.

What is SPICE in-memory storage and how does it enable simultaneous data exploration?
SPICE in-memory storage is a feature of QuickSight that allows thousands of users to explore data simultaneously. It stores data in memory for faster retrieval and analysis, enabling efficient data exploration.

Amazon QuickSight leverages the SPICE engine by utilizing a blend of columnar storage and in-memory technologies. Data within SPICE is retained until manually deleted by the user, ensuring data persistence. Additionally, SPICE automatically duplicates data to enhance availability and facilitate seamless scalability within QuickSight. Enabled by the SPICE engine, QuickSight can handle data sets of up to 250 million rows and 500 gigabytes, providing robust support for processing and analyzing large volumes of data effectively.

How does QuickSight enable users to connect to various data sources?
QuickSight allows users to connect to their entire data set in AWS, third-party clouds, or on-premises. It provides the capability to connect to different data sources. It offers native AWS service integrations with services like AWS Redshift, Snowflake, Exasol, Amazon RDS, and others. It also provides private VPC connectivity for these services, ensuring secure and seamless data exploration.

It boasts compatibility with various data sources, including on-premises databases, APIs, IoT devices, CSV files, and SaaS applications. Users can also leverage QuickSight’s integration with different data storage services such as Amazon S3 and its ability to query relational databases like those powered by Presto.  End-users can conveniently upload new data to an S3 bucket or file for enhanced data exploration through incremental data uploads.

Key Features

Amazon QuickSight is a powerful analytics service designed to offer business intelligence tools and data visualization capabilities for quick and efficient data analysis. By utilizing interactive dashboards and visualizations, QuickSight allows organizations to delve deep into their data to uncover actionable insights swiftly. This service can ingest data from various sources, including databases, files, and streaming data. Through its features and functionalities, Amazon QuickSight enables companies to make informed decisions by exploring data and identifying valuable insights that may have previously been hidden.

QuickSight facilitates self-service business intelligence for end users through its innovative ‘Q’ feature. This unique functionality empowers users to ask straightforward questions without the need for specialized BI training, enabling them to explore data deeply and extract valuable insights without requiring extensive technical expertise. By embracing self-service BI, QuickSight empowers users across the organization to make informed decisions efficiently and effectively.

Quicksight Q

This is machine learning capabilities utilized to better allow Quicksight to understand queries and spit out relevant information in a legible format in an incredibly short time.  It already comes pre-trained with terms and data sets from a variety of industries so that it’s already primed to understand and regurgitate information relative to users’ intentions.  Finally, the longer users interact with Q, the better it becomes accustomed to the internal lingo of an organization and their inquiry habits.

Embedded Interactive Elements

The dashboard is highly customizable with many options to change the look and feel from coloring to font.  With just a single click, it’s incredibly easy to embed these tools into apps, wikis, and portals without the need to call embedding APIs.  The Enterprise Edition of Quicksight also sports the option to generate custom emails embedded with dashboard reports, including the header and the footer of the emails.  Furthermore, it’s capable of deeper insight with ad-hoc analysis and machine learning tools for anomaly detection, forecasting, and natural language queries.  Finally, the serverless architecture can be arranged to keep multiple end-users separate, moving dashboards between accounts, automating payments, and more.

ML (machine learning) Insights

Outliers and trends can very easily fall under the radar under tides of other data points.  ML Insights can continuously analyze all data gathered to find anomalous patterns and understand the causes.  With that, it can also establish accurate estimates for future business metrics.  These predictions are then woven into the dashboard with all of the necessary context to fully explain to the users along with controls to customize the story.

Built for Enterprise-scale Workloads

Quicksight scales automatically to compensate tens of thousands of users at any time without infrastructure or capacity to plan ahead.  Additionally, it can import from data sources either on-premises or in the cloud, including various SaaS applications.  Quicksight’s Super-fast, Parallel, In-memory, Calculation Engine - also known as SPICE - automatically replicates data for multiple users to run analysis simultaneously.  It’s designed with being a global application in mind and is localized in ten major languages and is available in most AWS availability regions. Furthermore, Quicksight is designed as a global application, localized in ten major languages, and accessible in most AWS availability regions, ensuring a seamless user experience across diverse locations and languages.

Additional Features

Native AWS Integration

• • Private VPC connectivity for secure AWS access to Amazon Redshift, Snowflake, Exasol, Amazon RDS, and more
  • Native IAM permissions for Amazon S3 and Amazon Athena with fine-grained access control for serverless data exploration
  • Amazon SageMaker integration allows easy integration of sophisticated ML models
    without complex data pipelines

Minimal Maintenance Required

• • Serverless architecture auto-scales to hundreds of thousands of users with high availability; no need to over-provision for peak usage
  • SPICE in-memory engine auto-scales to provide consistent fast response times for end-users and analysts; no need to scale databases for high workloads
  • Pay-per-session optimizes costs by only paying for actual usage; no need to buy thousands of end-user licenses for large-scale BI or embedded analytics

Minimal Maintenance Required

• • Serverless architecture auto-scales to hundreds of thousands of users with high availability; no need to over-provision for peak usage
  • SPICE in-memory engine auto-scales to provide consistent fast response times for end-users and analysts; no need to scale databases for high workloads
  • Pay-per-session optimizes costs by only paying for actual usage; no need to buy thousands of end-user licenses for large-scale BI or embedded analytics

Cost and Pricing

Standard Edition

• • $9/month with a yearly subscription or $12/month for each month individually
    • 10 GB/user of SPICE capacity
    • $0.25 per GB of extra capacity

Enterprise Edition

• • Authors - create and share dashboards with other users.

• • Readers - can explore dashboards, download data, and receive email reports.

Capacity Pricing

• • Reader Capacity is for hosting multiple Q sessions in tandem, making it ideal for mass deployments.

• • Q question Capacity

Anomaly Detection

SPICE usage