Characteristics - Data Analytics Lens

Characteristics

Scalability: Ensure that the underlying BI infrastructure is able to scale up vertically and horizontally both in terms of concurrent users as well as data volume. For example, QuickSight SPICE, and web applications automatically scale up server capacity to accommodate a large number of concurrent users without any manual intervention in terms of provisioning additional capacity for data, load balancing, and other services.

Connectivity: BI applications must be able to not only connect with data platforms such as traditional data warehouses and databases, but also support connectivity to a data lake and modern data architectures. The application must also have the capacity to connect to non-traditional sources, such as SaaS applications. Typically, data stores are secured behind a private subnet and BI tools and applications must be able to connect in a secure mechanism using strategies, such as VPC endpoints and secure firewalls.

Centralized security and compliance: BI applications must allow for a layered approach for security. This includes: Securing at the perimeter using techniques such as IP allow lists, security groups, ENIs and IAM policies for cloud resource access, securing the data in transit and data at rest using SSL and encryption, and restricting varying levels of access through fine-grained permissions for users to the underlying data and BI assets. The application must also comply with the governmental and industry regulations for the country or region the company is bound by.

Sharing and collaboration: BI applications must support data democratization. They must have features that allow sharing of the dashboards with other users in the company as well as for multiple report authors to collaborate with one another by sharing access to the underlying dataset. Not all BI tools have this capability. QuickSight allows the sharing of assets, such as data sources, data sets, analyses, dashboards, themes, and templates.

Logging, monitoring, and auditing: BI applications must provide adequate mechanisms to monitor and audit the usage of the application for security (to prevent unwanted access to data assets and other resources) and troubleshooting. QuickSight can be used with Amazon CloudWatch, AWS CloudTrail, and IAM to track record of actions taken by a user, user role, or an AWS service. This provides the who, what, when, and where of every user action in QuickSight.

Perform advanced analytics

Modern BI applications must be able to discover hidden insights from your data, perform forecasting and what-if analysis, or add easy-to-understand natural language narratives to dashboards. The business users need the ability to perform analytics without deep statistical and machine learning knowledge.

QuickSight ML Insights provide features that make it easy to discover hidden trends and outliers, identify key business drivers, and perform powerful what-if analysis and forecasting with no technical or ML experience. 

Enable self-service business intelligence

The common challenges of BI tools are how to make data more accessible to more people without extensive user training and technical understanding. Data must be available in all format - raw, semi-processed and processed. Self-service BI should allow users to interact with data on an as-needed-basis without involving IT. 

QuickSight Q allows user to ask business questions in natural language and receive answers with relevant visualizations that help them gain insights from the data. QuickSight Q uses machine learning to interpret the intent of a question and analyze the correct data to provide accurate answers to business questions quickly