Choosing the Best Snowflake Reporting Tool for Your Team
Which Snowflake reporting tool should I choose for my team?
Table of Contents:
Introduction
Snowflake is a widely used cloud-native data warehousing and analytics platform. Since Snowflake is cloud-native, there is no software or hardware to select, install, configure, or manage, making it ideal for enterprises that don’t want to dedicate resources to setting up and managing in-house servers. Snowflake can work in multi-cloud infrastructure environments and it allows both storage and compute to scale independently. In this article, we have put together a list of the best reporting tools that natively connect to Snowflake and help you to make sense of your data.
Best Snowflake Reporting Tools
Tableau
Tableau is a powerful data analysis and visualization tool that supports native integration with Snowflake. Tableau’s Snowflake connector requires you to know the name of the server that you want to connect to. You can choose an option from the three authentication methods that are provided: OAuth, SAML IDP, and Username and Password. The sign-in credentials will depend on the authentication method that you choose. Tableau’s Snowflake connector requires you to install a driver to talk to the database. The driver and installation instructions are on Tableau’s official website. Tableau users have access to amazing and powerful visualizations to visualize their Snowflake data.
Tableau Features
Tableau is shipped with the following features:
- Integrations
Tableau comes with native connectors to cloud data warehouses, spreadsheets, PDFs, and files. Tableau users can pull data from cloud data warehouses such as Snowflake, Redshift, Databricks, BigQuery, and others. They can also pull data from relational databases such as MySQL, PostgreSQL, and others.
Its Snowflake connector supports three authentication methods, OAuth, SAML IDP, and Username and Password. You must install a driver for Tableau to talk to Snowflake.
However, Tableau doesn’t have connectors to NoSQL databases such as Apache Cassandra and MongoDB. Users must depend on third-party ODBC connectors capable of translating to SQL.
2. Visualizations
Tableau provides its users with beautiful and powerful visualizations for presenting their data. They can create charts, dashboards, maps, and stories to make sense of their data. Tableau allows users to customize their visualizations to meet their unique needs.
3. Search-based Analytics
Tableau has a search-based analytics feature known as Ask Data. It enables you to type a question in a common language and get an instant response in Tableau. The answers are in the form of automatic data visualizations, without the need to drag and drop fields manually or understand the underlying data structure.
4. Cross-database joins
Tableau supports cross-database joins, allowing analysts to join data across multiple sources within Tableau. It enables Tableau users to bring all their data together using drag and drop. They can perform inner join, right outer join, left outer join, and full outer join operations by relying on a common field across the sources involved.
5. Alerts/Anomaly Detection
Tableau users can set up data-driven alerts on their views and dashboards and be notified when their data reaches certain thresholds. You can receive the notifications in your email, Tableau, or connected Slack workspace.
6. Embedded Analytics
Tableau allows you to embed your dashboards, visualizations, and analytical capabilities into your products. You can generate a simple HTML embed code and use it to embed analytics into custom web portals, third-party applications, and custom-facing software and data products.
7. Customer Support
Tableau has a knowledge base with written materials categorized into Tableau products such as Tableau Desktop, Cloud, etc. Users can type their questions within the knowledge base and get article suggestions that can answer them as they type.
8. Pricing
Tableau has three pricing plans namely Tableau Creator, Tableau Explorer, and Tableau Viewer.
The Tableau Creator plan provides users with a suite of products needed for end-to-end analytics and it costs $75 per user/month, billed annually. The Tableau Explorer plan helps users answer their data questions through self-service analytics and it costs $42 per user/month, billed annually. The Tableau Viewer plan enables users to view and interact with dashboards and visualizations and it costs $15 per user/month, billed annually.
Tableau Benefits
Choosing Tableau comes with the following benefits:
- Integrates with Snowflake
Tableau supports native integration with Snowflake, allowing you to pull data for analysis and visualization.
2. User authentication
Tableau users can choose an option from the three authentication methods it provides while connecting to Snowflake. This can keep your Snowflake data secure.
3. Beautiful Visualizations
Tableau users have access to beautiful and powerful visualizations to visualize their Snowflake data.
4. User-friendliness
Tableau has a simple design, making it fit for use by users of all backgrounds. Its Ask Data feature enables non-technical users to understand their data by issuing questions in a common language.
Limitations of Tableau
Tableau users encounter the following challenges:
- Complex integration
Integrating Tableau with Snowflake involves installing a driver for the two platforms to communicate. This can be a complex process that requires an individual l with strong technical skills.
2. Doesn’t integrate with NoSQL data sources
Tableau doesn’t have connectors to NoSQL data sources, hence, it can be challenging to combine your Snowflake data with data from other sources.
3. Limited data support
Tableau only excels when handling structured data due to limitations in its architecture. It doesn’t support unstructured data.
4. Legacy Architecture
Tableau users must use Tableau Desktop to publish their workbooks to the Tableau Server or Cloud. Tableau also requires the user data to be structured and ready for analysis.
Knowi
Knowi is a unified business intelligence tool that provides native integration into Snowflake. Knowi enables warehousing, visualizing, and reporting automation from Snowflake as well as with other structured and unstructured data sources. Knowi doesn’t require you to install any driver to communicate with Snowflake, but it uses a data virtualization feature to query directly against Snowflake, cache, or store the results and update them incrementally. Knowi’s intelligent query execution capabilities enable you to store query results within Knowi to reduce your Snowflake storage and compute costs. Knowi users can interact with their Snowflake data by issuing questions in plain English and getting instant results even in the form of graphs and tables.
Knowi Features
Knowi gives you access to the following key features:
- Data-as-a-Service
Knowi has a data-as-a-service layer that enables it to work with any data, anywhere. It supports integration with SQL, NoSQL, files, REST APIs, and other sources. It has a unique Data Engineering layer that enables it to work with any type of data, whether structured or unstructured, small or big data.
Snowflake users can connect to their data natively from Knowi and take advantage of its intelligence query execution capabilities to store their query results within Knowi to reduce their compute and storage costs on Snowflake.
2. Visualizations
Knowi users have access to over 40 visualization types to present their Snowflake data visually. Each visualization comes with unique settings for customizing its appearance. Knowi offers drill-downs, filters, ad hoc slice & dice analysis, and more to help users dig deep into their data. Knowi users with JavaScript/CSS skills can create custom visualizations to meet their unique needs.
3. Ask Questions of your Data
Knowi has a search-based analytics feature powered by Natural Language Processing for conversational analytics. You can ask questions about your Snowflake data in plain English within Knowi and get instant answers. The answers can be in the form of charts and tables.
You can also embed this feature into your own applications to ask questions directly from the applications and get answers.
Knowi has also added its search-based analytics feature to Slack and Microsoft Teams, allowing you to ask data questions directly from these apps and get immediate responses.
4. Machine learning
Knowi is shipped with built-in machine learning algorithms, allowing you to build and train machine learning models from your Snowflake data. Currently, it supports Regression, Classification, and Time Series Anomaly Detection machine learning use cases. Knowi is expected to implement clustering and deep learning algorithms soon. It has a data preparation wizard to help you clean your data before feeding it into the algorithms.
5. Multi Data Source joins
Knowi users can perform joins across multiple data sources to store and process combined results. Hence, they can combine their Snowflake data with data from other SQL or NoSQL sources. It supports inner join, right outer join, left outer join, full outer join, and loop join, and they all depend on a common field among the data sources.
Knowi’s architectural design makes it fit for performing large-scale join operations involving millions of rows across multiple sources. The join operations can be optimized for faster performance.
6. Embedded Analytics
Knowi supports embedded analytics, allowing users to embed their dashboards, visualizations, and its analytical capabilities into their applications and cloud applications. The embedded content can be customized for a better customer experience.
Knowi supports simple URL-based embedding, secure URL embedding with encrypted request payload, and Single SignOn (SSO) API embedding that enables token exchange from your system users to map to Knowi with user rights and permissions.
7. Alerts/Anomaly Detection
You can configure Knowi to alert you when your data meets certain conditions or when anomalies are detected in your data. This can help you to monitor important changes as they happen to your business and take quick action. You can receive the alert notifications via email, Slack, Webhook, or Microsoft Teams.
8. Customer Support
Knowi comes with release notes to help you learn how to use the BI tool. It also has a knowledge base with product documentation and tutorials on how to complete various tasks on the platform. You can type your question on the knowledge base and get the top article suggestions to answer you as you type.
Knowi has a community section with sourced questions and answers that can be of help to you. It also has a Zendesk-powered chat system through which you can create and submit a support request to its support team and they will get back to you via phone or email.
9. Pricing
Knowi has not disclosed its pricing information to the public. It has provided a form on its website that you can fill out to request pricing information. It has three pricing plans namely Basic, Team, and Enterprise. Each plan offers full onboarding and technical support when needed. Knowi has special pricing for early-stage startups and non-profits. It also doesn’t charge for email reports that require a user and such in other systems.
Benefits of Knowi
- Native integration with Snowflake
Knowi integrates natively with Snowflake, without requiring you to install any driver.
2. Can reduce Snowflake costs
Knowi uses intelligent query execution to reduce Snowflake compute and storage costs. It stores or caches your Snowflake query results to avoid hitting Snowflake every time you need the data.
3. Supports many integrations
Knowi supports native integration with multiple data sources, including NoSQL databases such as MongoDB, ElasticSearch, and others. It lets you join your Snowflake data from other data sources.
4. Fit for non-technical users
Knowi has a search-based analytics feature to help non-technical users explore their Snowflake data using natural language.
5. Supports machine learning
Knowi has built-in machine learning algorithms, allowing you to fit machine learning models and make predictions using your Snowflake data.
Limitations of Knowi
Knowi comes with the following limitations:
- Visualizations are not very beautiful
Knowi does not have the most beautiful out-of-the-box visualizations. However, users with CSSJavaScript skills can customize them to get the desired look and feel.
2. Sophisticated user interface
Knowi’s user interface for business users is very intuitive. However, its user interface for data engineers is sophisticated, and one may take some time to get used to.
3. Not open source
Knowi is a commercial tool.
Looker
Looker is a unified business intelligence platform that supports native integration with Snowflake. It requires you to first create a Looker user in Snowflake and grant them access to your Snowflake data warehouse. Once the user is created, you can establish a connection to Snowflake directly from Looker. Looker comes with user attributes to help you assign separate Snowflake warehouses to Looker groups or individual users. Looker supports OAuth for Snowflake connections, allowing each user to authenticate into Snowflake and authorize Looker to run queries against the database using their Snowflake user account. It also provides a wide variety of configurable visualizations for presenting your Snowflake data visually. You can also share the insights you extract from your Snowflake data with the rest of the world.
Looker Features
Looker offers the following features:
- Integrations
Looker supports integration with cloud data warehouses such as Snowflake, Amazon Avalanche, Redshift, Databricks, Dremio, and others. It also supports integration with SQL databases such as PostgreSQL, MySQL, PrestoSQL, and others. However, Looker doesn’t have native connectors to NoSQL data sources such as MongoDB, ElasticSearch, and Apache Cassandra. Looker requires users to put the data in an SQL database for it to query against.
2. Visualizations
Looker is shipped with different visualizations to help you chart your data in various ways. It offers cartesian charts, progression carts, donut charts, tables, and maps for data visualization. Each visualization comes with unique settings for customizing its appearance. You can install additional visualization plugins from the Looker marketplace or create custom visualizations using JavaScript.
3. Analytics
Looker is shipped with pre-built models for the common data sources and analytical patterns known as Looker Blocks. These can be installed from the Looker marketplace. With Looker blocks, you don’t have to start from scratch, but you can reuse the work done by others. You can customize the blocks to meet your desired needs.
4. Alerts/Anomaly Detection
Looker lets you configure conditions in your data that will trigger notifications when met or exceeded. The notifications will be sent to the specified recipients at the set frequency. You can also view alerts created by other users. The alerts can be sent via email or Slack.
5. Embedded Analytics
Looker has an embed solution to enable users to embed visualizations, dashboards, or data exploration experiences into external applications. The embedding can be done by manually including an iframe with a signed URL or by using its embed SDK. It has the private embed modality to ease the process of authenticating users viewing the embedded content.
6. Customer Support
Looker Studio has a help page with various topics on how to use the platform. You can also type your question on the help page and get the top article suggestions to answer you as you type.
You can also post your question to the help community forum and get help from other Looker users.
7. Pricing
Looker (Google Cloud Core) has divided its pricing plans into two, that is, Platform pricing and User pricing. Platform pricing is the cost of running a Looker instance while user pricing is the cost of licensing users to access the Looker platform. Looker (Google Cloud Core) has three platform pricing plans namely Standard, Enterprise, and Embed, and their pricing is custom-based. There are three user pricing plans namely Developer User, Standard User, and Viewer User, and their pricing is custom-based.
Benefits of Looker
Looker offers its users the following benefits:
- Seamless integration with Snowflake
Looker integrates well with Snowflake, making it easy for its users to connect, analyze, and visualize their Snowflake data.
2. Data Security
Looker supports OAuth for Snowflake connections, allowing users to control access to their Snowflake data.
3. Customizable
Looker users can customize the Looker Blocks to suit their needs. They can also edit their visualizations or create custom ones to help them meet their needs.
4. Multi-cloud friendly
Looker is a multi-cloud friendly BI tool, giving users flexibility when choosing where to deploy it plus the underlying databases.
Limitations of Looker
Looker has the following challenges:
- Lacks machine learning features
Looker doesn’t have built-in machine learning algorithms to enable users to build and train models from their Snowflake data.
2. Doesn’t support multi-source joins
Looker doesn’t enable its users to join data across multiple data sources, hence, they cannot join their Snowflake data with data from other sources.
3. May require a learning curve
Looker users may have to learn LookML, its proprietary, markup language to use some of its features, a process that may require a learning curve.
4. Doesn’t integrate with NoSQL data sources
Looker doesn’t have native connectors to NoSQL data sources. To pull data from such sources, users must work their way out, like putting the data in the form of an SQL database for Looker to query against.
5. Limited US customer support
Looker has undergone several changes after its acquisition by Google in 2019, creating confusion even in its naming (Looker Studio). It has also scaled down its US customer support.
Power BI
Power BI is a business intelligence tool created by Microsoft and it supports native integration with Snowflake. It is easy to connect to Snowflake from the Power BI service using basic authentication. Power BI users can also connect to Snowflake using single sign-on (SSO), and parts of the integration will require different administrative roles in Snowflake, Azure, and Power BI. Choosing the SSO option will eliminate the need for on-premises Power BI gateway implementations as Power BI service uses an embedded Snowflake driver to connect to Snowflake. Power BI users have two options to get data from Snowflake, they can import the data into Power BI or create a DirectQuery in Power BI to get the Snowflake data when needed.
Power BI Features
Power BI has the following features for its users:
- Integrations
Power BI offers multiple software-as-a-service connectors to enable users to connect to apps, data, and cloud platforms such as Snowflake. Power BI Desktop users can easily connect to Snowflake by clicking the “Get Data” option from the Home ribbon and following the on-screen prompts to complete the connection. Power BI Service users can connect to Snowflake using basic authentication or single sign-on (SSO) for improved security. Power BI integrates well with other Microsoft products such as Excel, Forms, Office 365, and others. It also has native connectors to SQL databases such as PostgreSQL, and MySQL as well as NoSQL databases such as MongoDB. Power BI users can create custom connectors and submit them to Microsoft for certification.
2. Visualizations
Power BI comes with a wide variety of visualizations that you can add to your reports and dashboards. Examples include waterfall charts, treemaps, column charts, decomposition trees, funnel charts, doughnut charts, and others.
You can download additional visualizations from the Microsoft AppSource and use them in your reports and dashboards. You can also create your own visualizations and add them to its community site.
3. Ask Questions of your Data
Power BI has a Q&A feature that enables users to explore data using natural language capabilities and get answers in the form of graphs and charts. Q&A chooses the best visualization depending on your data, or you can specify the type of visualization in your question.
4. Alerts/Anomaly Detection
You can configure Power BI to notify you when data in your dashboard changes beyond certain limits. You can set the frequency with which Power BI will check your data for the alert condition. The alerts are sent to your Power BI notification center or optionally via email.
5. Customer Support
Microsoft has added Power BI support to Microsoft Fabric Support. Power BI comes with written documentation to help users learn how to complete various tasks using the BI tool. You can also post your question on the Microsoft Fabric community forum and get answers from other Power BI users. Power BI users can contact the support team by creating a support request via the official Microsoft website.
6. Pricing
Power BI has a free plan and two other priced plans namely Power BI Pro and Power BI Premium.
Power BI Pro is fit for self-service analytics, allowing users to publish reports and dashboards and view content across an entire organization. It costs $10 per user/month. Power BI Premium gives users access to enterprise-scale features such as more frequent refreshes, larger model sizes, deployment pipelines, and such. It costs $20 per user/month.
Benefits of Power BI
Power BI gives its users the following benefits:
- Integrates with Snowflake
Power BI enables its users to connect to Snowflake with basic authentication. They can pull their Snowflake data into Power BI or create a DirectQuery to get the data when needed.
2. User authentication
Power BI allows single sign-on while connecting to Snowflake to facilitate user authentication. This is good for data security.
3. Fit for non-technical users
Power BI’s Q&A feature enables non-technical users to explore their data using natural language capabilities.
4. Customizable visualizations
Power BI users can create custom visualizations to help them meet their unique data visualization needs.
Power BI Limitations
- Integration can get complex
Power BI users can easily connect to Snowflake with basic authentication. However, the integration can get complex where advanced authentication is needed.
2. Bulky user interface
Power BI has a bulky user interface. Users may encounter challenges trying to move from one component to another.
3. Limited integrations
Power BI lacks connectors to some data sources. Hence, users may have to create custom connectors to meet their data integration needs.
4. Limited data support
Power BI doesn’t have strong support for unstructured support compared to other BI tools in the market.
Final Thoughts
Snowflake is a cloud-native data warehousing solution. It is a suitable data storage solution for enterprises that don’t want to dedicate resources to setting up and maintaining in-house servers.
Tableau, Knowi, Looker, and Power BI are some of the best Snowflake reporting tools that you can choose for your team.
Tableau has a Snowflake connector that enables you to connect to Snowflake. The connector requires you to know the name of the server that you want to connect to. You must install a driver for Tableau to communicate with Snowflake.
Knowi is a unified BI solution that enables warehousing, visualizing, and reporting from Snowflake. It uses intelligent query execution to query directly against Snowflake and cache the results to save you from hitting Snowflake every time you need data. This reduces Snowflake compute and storage costs.
Looker is a unified business intelligence platform that supports native integration to Snowflake. It requires you to first create a Looker user in Snowflake before establishing the connection from Looker.
Power BI is a BI tool created by Microsoft and it comes with a Snowflake connector. You can easily connect Power BI to Snowflake with basic authentication. You can also connect through Single Sign-On and the integration will require different roles in Snowflake, Azure, and Power BI.
