BI Tools on Snowflake
Which is the best BI tool for Snowflake data? Let’s find out!
Table of Contents:
BI Tools on Snowflake- Final Thoughts
Introduction
The Snowflake cloud data platform has grown to become one of the largest cloud vendors in the world in 2023. Snowflake reported revenue of $1.2 billion in the financial year ending January 31, 2022. This was more than double the company’s revenue generated the previous year. The company’s workforce has also grown rapidly over the recent years, with a total of 4,991 employees in July 2022, which represented a yearly increase of about 53 percent.
After storing and structuring your data in Snowflake, the next step should be turning the countless meaningless columns into insights. This is possible with Business Intelligence (BI) tools that connect Snowflake to dashboards that update in real-time. In this article, we have compiled a list of the best BI tools that are interoperable with Snowflake.
Looker
Looker is a powerful BI tool that offers an innovative approach to real-time data exploration and analytics. It was recently added as part of the Google Cloud Platform. Other than Snowflake, Looker integrates well with SQL-based data sources. However, Looker doesn’t integrate with NoSQL data sources.
Looker queries are run on individual databases, but it doesn’t join between databases. However, you can create dashboards and visualizations using data from different sources.
Looker comes with powerful dashboard capabilities that can be used for various data discovery use cases. However, Looker requires a full semantic model for storing all metrics and business logic without the need to add any versions of a slightly different metric to the database tables.
Thus, you cannot take Looker, connect it to Snowflake, and get visualizations within minutes. You must do an upfront definition using LookML, Looker’s own language, which might take you some time to learn.
Looker supports different types of visualizations that Snowflake users can use to make sense of their data. Each visualization comes with unique settings that can be used to customize its look. Examples of these visualizations include cartesian charts, progression charts, pie and donut charts, maps, texts, and tables.
Looker also has an embedded analytics feature that can give your customers the data they need to get the job done. However, it doesn’t have native support for machine learning.
Looker has not made its pricing information public. Instead, they offer a customized approach where they create a suitable pricing structure for different businesses based on their needs. They have added a “Request a quote” button on their website that you can click to request a price quote.
However, the merger between Looker and Google Data Studio has caused confusion in terms of naming, features, pricing, etc. Looker has also laid off support (DCL) for US customers, making it difficult for them to troubleshoot issues with the BI tool.
Power BI
Power BI is a common BI tool among enterprises that adopt the Microsoft ecosystem. Power BI supports a good number of data sources, including Snowflake, helping enterprises to centralize their data in a single place. It can connect essentially to any structured or SQL-based data source. To connect Power BI to NoSQL sources, you must rely on third-party connectors such as ODBC (Open Database Connectivity) drivers that translate into SQL. You can also use ETL tools and processes to move data into your data warehouse and apply schema.
Power BI comes with a variety of data visualization tools that you would expect from a Microsoft product. It has all the standard and advanced visualization options for visualizing your Snowflake data. With Power BI, you can create your own custom visualizations and put them in their App source marketplace.
Power BI has good data analytics features for both beginner and advanced users. It supports a natural query language for performing analytics with conversational questions.
Power BI has an embedded analytics feature that you can use to embed reports and dashboards created from your Snowflake data in web applications. Its secure embed feature ensures that only users with a Power BI license can view the report or dashboard.
It also lets you create various machine learning models due to its integration with the Azure platform. Power BI also supports text analytics and computer vision via cognitive services APIs.
Power BI has two pricing plans namely Power BI Pro and Power BI Premium.
Power BI Pro is good for individual users and costs $13.70 per user/month. The Power BI Premium is good for both individual and organizational use. It can be licensed to an individual user or to an organization. The plan costs $27.50 per user/month or $6,858.10 per user/month.
Tableau
Tableau has the largest user base of all BI tools in the market and it comes with a native connector for Snowflake. It also comes with native connectors that support integration with SQL-based data sources.
To connect Tableau to NoSQL data sources such as MongoDB, you can use third-party ODBC drivers/connectors that can translate into SQL. However, relationizing the data from NoSQL form to SQL form has a number of limitations.
With Tableau, you can create beautiful and powerful visualizations from your Snowflake data. It allows you to create amazing graphs, charts, maps, dashboards, and stories that you can customize to meet your own needs.
Tableau has a join feature that can help you to combine your Snowflake data with data from other sources. Tableau supports INNER JOIN, LEFT OUTER JOIN, FULL OUTER JOIN, and RIGHT OUTER JOIN operations.
For the join operations to run successfully, the data sources must share a common field. The inner join is the default join type in Tableau.
Although Tableau is popularly known as a data visualization tool, it is also a powerful tool for advanced data analytics. It has the Ask Data feature that lets non-technical users type questions in plain English and get responses.
Tableau also offers machine learning features through its built-in machine learning features such as clustering and predictive analytics as well as through integration with third-party machine learning tools and platforms. Tableau can also be integrated with Aible to come up with a seamless BI + AI experience. Snowflake users with experience in Python can also use the TabPy library to build machine learning models and deploy them directly into Tableau.
Tableau is also good for embedded analytics, allowing its users to take their products to the market faster. It generates a simple HTML embed code that can be used for embedding dashboards into web pages. Users can also embed their visual analytics into custom web portals, third-party applications, data products, and custom-facing software.
Tableau has three pricing plans namely Creator, Explorer, and Viewer. The Creator plan offers full Tableau functionality and costs $70/user/month. The Explorer plan is good for individual users who need to perform self-service analytics. It costs $42/user/month for cloud deployment and $35/user/month for on-premise deployment. Tableau Viewer only allows users to view already created visualizations and it costs $15/user/month for cloud deployment and $12/user/month for on-premise deployment.
Domo
Domo is a BI tool created for all business users regardless of their technical expertise, to extract insights from data and make better decisions. Domo has a Snowflake connector that you can use to connect to your Snowflake data. It comes with 1000+ prebuilt data connectors. Data sources without a native connector can be accessed via the Domo Workbench Connector or via API.
Domo is good for creating scalable and attractive visualizations. It supports more than 150 charts for data visualization, including period-over-period charts, data science charts, and Trellis charts, all powered by Domo’s visualization engine. Domo comes with pre-built pages that can self-assemble depending on data inputs. Domo has a Card Builder tool that lets users create visualizations through drag and drop.
However, Domo doesn’t have Natural Language Processing capability.
Domo users can get various types of alerts, including new customer alerts, revenue increase/decrease alerts, sales benchmarks, etc. With Domo, users can configure custom alerts to be notified after data changes, when a metric reaches a set threshold, when particular KPIs change, etc.
Domo supports machine learning through its Auto ML feature which provides automatic insights. Sagemaker powers the feature. With Auto ML, Domo users can tell the platform which parts of their data they need insights and predictions on. Domo will then apply various machine learning models to their data and return the results. This feature lets Domo users perform forecasting, classification, and prediction tasks.
Domo also supports embedded analytics, helping users deliver data experiences to their partners and customers. They can create self-service dashboards and embed them directly into portals, websites, and apps.
Domo supports the four types of primary joins, that is, INNER JOIN, LEFT OUTER JOIN, FULL OUTER JOIN, and RIGHT OUTER JOIN. It also supports the LOOP JOIN. These joins can be used to combine data from multiple sources into one.
Domo’s pricing is customizable depending on the usage of the platform, and it depends on factors such as data refresh rates and the number of users.
Domo requires Snowflake data to be sent or stored on its platform first before being used for analytics and visualization. This can introduce delays, especially when dealing with large datasets.
Knowi
Knowi is a unified analytics platform from raw data all the way to business users. It uses a data virtualization feature to save you from taking your Snowflake data through cumbersome-time-consuming ETL steps. Knowi has native support for integration with Snowflake as well as over 36 structured and unstructured data sources such as ElasticSearch, MongoDB, Apache Cassandra, and others.
Unlike other BI tools, Knowi comes with native connectors to NoSQL data sources, hence, you don’t have to install third-party drivers. It is also fully native without the need to “relationalize” the data.
Knowi also supports over 30 different visualizations that you can use to present your Snowflake data visually. It can also be used to create customizable dashboards and visualizations. Knowi users can also create custom visualizations using JavaScript to meet their specific needs.
Knowi also supports joins across different multiple data sources to blend and store combined data. Thus, Snowflake users can combine their data with data from other sources. The join operations are done using a common field among the data sources.
Knowi’s Data Engineering layer makes it a unique BI tool in the market. Knowi’s Data Engineering feature allows you to query directly against Snowflake, cache the results, or store the results (and incrementally update the results). This can reduce the Snowflake compute costs since you will not be hitting Snowflake for all queries, but a Dataset as a Service layer that encapsulates if the query is direct/cached/stored with multi-source joins, transformations, etc. With Knowi, you can also write datasets into Snowflake.
Knowi comes with a natural query language that supports search-driven analytics. Knowi has gone further to introduce search-driven analytics on Slack and Microsoft Teams, making it a unique BI tool in the market. Non-technical users can ask questions in plain English and get instant responses. The responses can be in the form of charts and graphs.
Knowi is integrated with machine learning features to help users perform tasks such as Classification, Regression Analysis, and Time-Series Anomaly Detection. Knowi is also planning to integrate deep learning and clustering algorithms into its platform.
Knowi can also be integrated with third-party machine learning platforms such as TensorFlow and Amazon Sagemaker.
Knowi has numerous options for supporting embedded analytics. A user can generate a URL of a dashboard and embed it in external applications. Knowi users can also create a secure URL that uses parameters to ensure that users only see the data they are supposed to see. It also provides the Single SignOn API that facilitates token exchange from users in your system to map to Knowi with user rights and permissions.
Knowi has an alerts feature that can keep you updated about important changes to your Snowflake data. The alerts facilitate data management by sending real-time notifications when specific conditions, thresholds, and anomalies are detected in the data. The alert notifications can be sent via Slack, webhook, or email. The alerts can also be set up directly on a widget based on a threshold, anomaly, or custom condition in the data.
Knowi has not made its pricing information publicly available, but they have provided a form on the official website that you can fill out and request for the same. They offer three pricing plans namely Basic, Team, and Enterprise. Each plan comes with full onboarding and technical support. Knowi also offers discounts for startups and non-profits. It doesn’t charge for email reports that require a user etc. in other systems.
BI Tools on Snowflake- Final Thoughts
All the above BI tools can work with Snowflake, but you should choose the one that meets your organizational needs and expectations.
If your company is looking for a simple BI tool to generate simple and customizable visualizations from snowflake data, choose Looker. It offers a flexible pricing plan suitable for both small and medium-sized organizations.
Domo is good for any company that seeks to manage the entire organization from a single platform. It provides a single dashboard where individuals across all ranks in a business can access data and extract deep insights for decision-making.
If you are a big company seeking to create complex reports and beautiful visualizations from Snowflake data, choose Tableau. However, make sure that you can meet the budget. If you are on a tight budget and you don’t need much scalability, go for Power BI.
Knowi will help you save more than both Tableau and Power BI if your user base will grow in the future.
