Are you looking for a fully managed Visualization tool that can create appealing Visualizations in no time? Well, your search ends here. In this blog post, you will get in-depth knowledge about Amazon QuickSight – a fully managed Cloud-based Visualization tool that can allow you to convert unstructured data into actionable intelligence. In today’s date, a huge amount of data is present which when modeled and mined accurately can be used to gain a considerable edge over one’s competitors. BI tools like these are used by enterprises to analyze and visualize this data on the basis of business requirements.
Table of Contents
- Introduction to Amazon QuickSight
- Key Features of Amazon QuickSight
- Understanding How Amazon QuickSight Works
- Steps to Create a Visualization in Amazon QuickSight
- Advantages of Amazon QuickSight
- Data Sources Supported By Amazon QuickSight
- Analytical Functions Supported By Amazon QuickSight
Introduction to Amazon QuickSight
Amazon QuickSight is a Cloud-based Business Intelligence tool and is available under the hood – Amazon Web Services. With Amazon QuickSight, you can develop easy to understand insights from data while allowing you to connect your data from the Cloud and combine data from various sources.
Amazon QuickSight can include AWS data, third-party data, Big Data, Spreadsheet data, SaaS data, B2B data, and more in a single data dashboard. It is a fully managed Cloud-based service, and it provides enterprise-grade security, high availability, highly scalable with no infrastructure to deploy or manage.
Key Features of Amazon QuickSight
Amazon QuickSight is Amazon’s entry into the Business Intelligence space that takes advantage of machine learning to identify the anomalies in data and make predictions through the ML Insights feature. Here are a few salient features that establish Amazon QuickSight as a tool to reckon:
- Amazon QuickSight has an in-memory engine, called SPICE, that performs the data analysis with blazing speed.
- It is a fully Cloud-based system and allows people to work collaboratively with no hustle to manage infrastructure or applications.
- It will enable users to combine data from various sources into one single dashboard.
- Easy to collaborate and share with easy to manage permission and accessibility.
- It provides utmost security to the data at rest and data at motion.
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Understanding How Amazon QuickSight Works
Amazon QuickSight is a straight-forward tool to work. When you log-in, Amazon QuickSight discovers all your data sources in AWS services like AWS Redshift, AWS Athena, etc. Following this step, you can then connect to any of these data sources and get meaningful insights in no time. Amazon QuickSight is a Cloud solution completely integrated with AWS(Amazon Web Services). A typical Amazon QuickSight workflow will look like this:
- Create a new analysis.
- Add datasets (New/Existing).
- Choose the fields from the datasets to create charts. Amazon QuickSight will give suggestions based on the fields.
- You can add more charts, tables, or insights.
- Publish the charts to the dashboard and share them across the organization.
The following illustration shows the basic workflow:
- If you don’t have an Amazon Web Service account, sign up on the link below to access free-tier products with a new account setup. Click here to signup.
- A basic understanding of Visualization and data analytics is required.
Steps to Create a Visualization in Amazon QuickSight
- Step 1: Sign up for an AWS free-tier account.
- Step 2: Create an IAM user that will have access to Amazon QuickSight.
- Step 3: Sign up for an Amazon QuickSight subscription.
- Step 4: For this example, you can use the sample dataset – Web and Social Media Analytics provided by Amazon QuickSight to create a Visualization.
- Step 5: Download the sample web-and-social-analytics.csv.zip dataset. Unzip the file and save web-and-social-analytics.csv to desktop.
- Step 6: Choose New Analysis on the Amazon QuickSight page and then select New Dataset.
- Step 7: Upload the web-and-social-analytics.csv file from your computer.
- Step 8: Choose Visualize on the next screen.
- Step 9: On the Datasets page, choose the download dataset option, and then choose Create Analysis.
- Step 10: From the Fields list pane, select Date, and then select Mailing list adds.
- Step 11: The AutoGraph technique is used to auto-select the most compatible chart with those fields. In this case, a line chart is selected by default.
- Step 12: Stretch the Field Wells pan to gain more control over visuals.
- Step 13: Choose the X-axis field well, choose Aggregate, and then choose Month.
The line chart updates to show the summation of the mailing list adds by date.
Advantages of Amazon QuickSight
Amazon QuickSight is known to provide cost-effective, fast, and interactive Business Intelligence for any enterprise. It is remarkably capable of handling multiple Big Data sources and performing smart Visualizations on them. This BI tool also optimizes productivity with features like interactive GUI with shared Visualizations. Here are a few advantages that make this tool an indispensable component of your workflow:
- Data Source Compatibility: Data source entities can either be CSV files, SaaS data sources, file sources, or relational data sources like Amazon Athena, Amazon Redshift, etc. Any other data sources are often accessed by either linking them or importing them through supported ones.
- Slick and Smooth SPICE Engine: The SPICE engine is an extremely fast, parallel, in-memory, calculation engine and is swift and easy to use. This feature has unique columnar storage that when combined with the latest hardware technology can empower its users to query large amounts of data, process and analyze them at a lightning pace, simultaneously. This engine is meant to be extremely powerful and makes data readily available through its replication process. It enables even the novices to use this BI tool with relative ease and clarity, by simply logging-in, connect to the data source,s and perform analysis.
- Portable: Amazon QuickSight is a very handy tool, especially for all business owners since it can literally be accessed from anywhere; laptop, desktop, smartphone, tablets, and even offline after installing offline mode. Just install the app and log in, and you are good to go. There exists a native mobile app for iOS as well.
- Flexible: Amazon QuickSight is designed in such a way that business users are not constrained by a conservative Cloud design. Users can fiddle with massive data without delving much into its behind-the-scenes working. As soon as you login you are directed to the dashboards where you can create your Visualizations in a jiffy. With a world-class data engine and endless documentation, the flexibility of the tool increases with each usage.
- Smart Interactive Visualizations: The SPICE calculation engine helps model accurate processes and retrieves the required data faster than usual. It has a built-in Visualization tool that generates a string of suggestions by observing patterns in the backend data sets. The feature ‘Autograph’ evolves itself to accurately predict data analyses supported by your analytical patterns over time.
- Self-Service Analyses: Business users are equipped with self-service exploratory analytics. The GUI available on the dashboard enables to slice and dice the info as per the specified analysis and save them up as stories. These stories can later be shared with others in your organization. With the advent of this unique option, the user can perform self-service analytics by Visualizing all analyses/stories on the dashboard and generating the most optimal one, thus customizing the app just for you.
- Highly Scalable: Amazon QuickSight can be used across several business domains to measure business metrics independently. It is often scaled across tens of thousands of users who can work independently and simultaneously across all data sources.
Data Sources Supported by Amazon QuickSight
This BI tool supports a large number of data sources. Once New Dataset on the homepage is clicked, it gives you options for all the data sources that can be utilized. The following list jots down the list of all external and internal sources that can be used by Amazon QuickSight:
- Amazon Athena
- Amazon Aurora
- Amazon Elasticsearch Service 7.7 or Later
- Amazon Redshift
- Amazon Redshift Spectrum
- Amazon S3
- CSV (Comma Separated Values) and TSV (Tab Separated Values)
- ELF and CLF: Extended and Common Log Format Files
- JSON: Flat or Semi-Structured Data Files
- JSON Data
You can find more details about supported data sources on the Amazon QuickSight official page.
Analytical Functions Supported by Amazon QuickSight
Amazon QuickSight offers all sorts of analytical functions that can be applied to the data while creating a Visualization. Users without any prior coding experience can explore data and extract different meaningful insights using this handy tool.
- Aggregate Functions: Aggregate functions are used to perform calculations over the fields. It includes functions like average, max, min, count, distinct, stddev, sum, and many more.
- Conditional Functions: Conditional functions are used when there is a need to perform calculations based on some conditions. It includes functions like coalesce, if, else, isNull, isNotNull, and many more.
- Date Functions: Date functions are used to perform date-related calculations like add date, epoch time, subtract date, now, trunc date, etc.
- Numeric Functions: Numeric Functions for calculated fields include intToDecimal, float, round, etc.
- Mathematical Functions: Mathematical Function includes log, ln, mod, sqrt, abs, etc.
- String Functions: String functions for calculated fields include – concat, ltrim, rtrim, substring, toString, replace, and many more.
- Table Calculations: Table calculations include a group of functions to provide enriched aggregations to the field. It includes calculation over a window, ranking, percentage total, etc. It is divided into further categories:
- Lookup based function: lag, lead, percentage difference, etc.
- Over Function: aggOver, countOver, sumOver, etc.
- Ranking Function: rank, denseRank, percentileRank, etc.
- Running Function: runningAvg, runningCount, etc.
- Window Function: firstValue, lastValue, windowAvg, windowCount, etc.
To learn more about the analytical functions, follow the Amazon QuickSight Official Guide.
The article teaches you in-depth about Amazon QuickSight, its use case, its advantages, and steps to create appealing Visualization. The article then gives you a brief overview of the data sources and the analytical functions supported by Amazon QuickSight.
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