Workload optimisation and improved audit logging in
Amazon Redshift
- Categories
- Date
- Author
- Data & Visualisation, Analytics
- March 10, 2022
- Jodie Rhodes
Today’s insight takes a broader look at two elements shaping Amazon Redshift into the data warehousing behemoth of the 21st century. We begin with the recent AWS article that highlights how the new automatic query rewrite feature can optimise analytical workloads.
Amazon Redshift is taking even larger strides in the world of data warehousing
Amazon Redshift materialised views enable you to significantly improve performance of complex queries that are frequently run as part of your extract, load and transform (ELT), business intelligence (BI) or dashboarding applications. Materialised views precompute and store the result sets of the SQL query in the view definition. Materialised views speed up data access, as the query doesn’t need to rerun the computation each time the query runs (further reducing the resource consumption).
The AWS feature describes, in detail, how the automatic query rewrite feature works as well as some scenarios where you could take advantage of this feature.
We were excited to see that materialised views can have their own distribution and sort keys, enabling optimisation joins for tables and data sets that have multiple join paths. To check out the detailed instructions and examples, soaking in new elements within optimising table scans and joins between two large tables, we highly recommend visiting the official source here.
SQL statement that demonstrates the speed and compute advantages to the automatic query rewrite feature.
Setting up cross-account audit logging for your Amazon Redshift cluster
Next on the Amazon Redshift agenda are the new audit logging features, enhancements driving monitoring, security and troubleshooting. Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. With Amazon Redshift, you can analyse all your data to derive holistic insights about your business and your customers. One of the best practices of modern application design is to have centralised logging. Troubleshooting application problems can be easy (when you can correlate all your data together).
When you enable audit logging, Amazon Redshift logs information about connections and user activities in the database. These logs help you monitor the database for security and troubleshooting purposes, a process called database auditing. The logs are stored in Amazon Simple Storage Service (Amazon S3) buckets and provide convenient access with data security features for users who are responsible for monitoring activities within the database.
If you want to establish a central audit logging account to capture audit logs generated by Amazon Redshift clusters located in separate AWS accounts, you can use the solution in this post to achieve cross-account audit logging for Amazon Redshift.
Jason Golding, Solutions Architect at Firemind says – “The new audit logging features within Amazon Redshift are gamechangers! As an Advanced AWS Partner, we’re continually looking for ways to improve both security within our customer solutions and enhancing troubleshooting features.”
The importance of using AWS CLI
The Amazon Redshift console only lists S3 buckets from the same account (in which the Amazon Redshift cluster is located) while enabling audit logging, so you can’t set up cross-account audit logging using the Amazon Redshift console. However, in the featured article, AWS demonstrate how to configure cross-account audit logging using the AWS Command Line Interface (AWS CLI).
There are a few prerequisites in order to follow along with the featured walkthrough, so make sure you have/can access the following:
• Two AWS accounts: one for analytics and one for centralised logging.
• A provisioned Amazon Redshift cluster in the analytics AWS account.
• An Amazon S3 bucket in the centralised logging AWS account.
• Access to the AWS CLI.
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Explore Solutions Get in touchExciting New Features in Amazon QuickSight
- Categories
- Date
- Data & Visualisation, Data & Analytics, Generative AI
- April 26, 2024
Amazon QuickSight has recently introduced several exciting new features that enhance the platform’s capabilities. These updates include improved security and control, enhanced data analysis and reporting capabilities, as well as new solutions for specialised use cases.
In this article, we’ll dive deeper into the key updates to Amazon QuickSight and explore how they can benefit your organisation’s data analytics and decision-making processes.
AWS PrivateLink support for Amazon QuickSight
One of the major announcements is the integration of AWS PrivateLink with Amazon QuickSight. This integration provides private connectivity between the QuickSight service, virtual private clouds (VPCs), or on-premises networks, without routing traffic to the public internet.
With this feature, administrators can use VPC endpoint policies to restrict access to QuickSight accounts that are not authorised on their network. This added layer of security and control is particularly valuable for organisations with strict data governance requirements or those operating in sensitive industries.
AWS Marketplace Usage Dashboard for Sellers
AWS Marketplace has also introduced a new Amazon QuickSight dashboard that displays customers’ product usage for AWS Marketplace sellers. This dashboard, accessible under the Insights > Sales operations tab of the AWS Marketplace Management Portal (AMMP), provides sellers with a visualised reporting experience for their customers’ product usage information.
The key features of this usage dashboard include:
Dynamic search and filtering: Sellers can easily search and filter the data across various dimensions, such as offer visibility type (public, private, channel, etc.) and custom date ranges.
Comprehensive usage insights: The dashboard offers pre-built metrics and charts that enable sellers to identify trends and issues in their customers’ product usage patterns.
Downloadable data: Sellers can download the granular usage data directly from the dashboard in CSV or Excel formats for further analysis.
This new dashboard empowers AWS Marketplace sellers to make more informed decisions regarding product support, pricing, conversion from public to private offers, and product discontinuation.
Enhancements to KPI visuals in Amazon QuickSight
Amazon QuickSight has also introduced a range of exciting enhancements to its KPI (Key Performance Indicator) visual capabilities. These improvements include:
Templated KPI layouts: QuickSight now offers a user-friendly onboarding experience, allowing authors to select from pre-designed KPI layouts tailored to various use cases and configurations. This makes it easier for users to create visually appealing KPIs with just a few clicks.
Support for sparklines: The KPI visual now supports the inclusion of sparklines, which are small, line chart-like visualisations that provide a concise representation of data trends.
Improved conditional formatting: QuickSight has enhanced its conditional formatting capabilities, enabling authors to apply more sophisticated formatting rules to their KPI visuals.
Revamped format pane: The format pane for KPI visuals has been redesigned to provide a more intuitive and streamlined user experience.
These enhancements to KPI visuals in Amazon QuickSight empower users to create more engaging and informative dashboards, helping them retrieve greater insights in less time from their data.
Clickstream Analytics on AWS solution
In addition to the updates within QuickSight, AWS has also introduced a new end-to-end solution called “Clickstream Analytics on AWS.” This off-the-shelf deployable reference architecture allows you to capture, ingest, store, analyse, and visualise clickstream data from your web and mobile applications using various AWS services with visual analytics ultimately surfacing in QuickSight.
By leveraging this solution, businesses can gain valuable insights into user behaviour, website performance, and customer engagement, driving more informed decision-making.
To conclude
The recent updates to Amazon QuickSight demonstrate the platform’s continued evolution and commitment to providing businesses with powerful data visualisation and business intelligence capabilities. From enhanced security and control through AWS PrivateLink integration to improved KPI visuals and new data analysis solutions, these features empower users to unlock deeper insights and make more informed decisions.
As an AWS Specialist Data and AI Partner, Firemind can help you leverage the full potential of Amazon QuickSight.
To learn more about how the new features in Amazon QuickSight can transform your organisation’s data analytics capabilities, reach out to our team using the form below.
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