Sisense Integration With Snowflake
Author: Ayushi Sharma
This blog is about Sisense Integration with Snowflake.
What is Sisense?
Sisense is an agile business intelligence (BI) solution that provides advanced tools to manage and support business data with analytics, visuals, and reporting.
Benefits of Sisense:
- This software stands out for its ability to draw large amounts of data from multiple data sources at high speeds.
- It quickly creates robust dashboards that are accessible on any device. The system can be easily customized for multiple user levels.
- The Sisense platform enables a centralized data strategy, reducing the redundancy of siloed or distributed reporting.
- Sisense allows product managers and R&D teams to build BI and analytic apps with a full suite of APIs and software developer kits (SDKs).
- Improves your cost forecasting by setting limits on pivot tables queries for easier planning and governing cloud data warehouse usage.
Most of our day-to-day work involves employing multiple applications with various datasets sitting in different databases. When analyzing this data, blending it in a consumable fashion is a consistent challenge for users across an organization.
As a tech professional, how do you provide complex data from multiple sources in a consumable fashion to analysts or perform advanced analysis to meet specific needs? As a business analyst, how do you leverage the power of data without going to a data engineer for every question? Specifically, two areas need attention: discoverability and performance. There needs to be a way to store massive amounts of data and ingest relevant data for analysis while maintaining high performance.
- Snowflake innovates in an effort to democratize data analytics for all business users. As a data warehouse-as-a-service, Snowflake provides a platform that allows users to focus on BI projects while accelerating business intelligence tool performance.
- The built-for-the-cloud warehouse delivers an efficient BI solution with an array of BI products. Mining the best analytics is impossible with conventional data warehouses.
- In Snowflake’s cloud architecture, users can leverage meaningful insights at scale through the best BI tools. Snowflake interoperates with several leading BI tools.
Why Sisense and Snowflake?
- Sisense and Snowflake share highly available and scalable cloud-native architectures deployed cross-cloud– meeting and exceeding complex data demands across an increasingly common customer base.
- The purpose of the integration is two platforms, working side by side to develop the next phase of consumer-friendly and accessible insights, focused on making analytics invisible and approachable.
- Through Sisense, you can connect and integrate your Snowflake data warehouse quickly and easily to generate and analyze your data. Snowflake provides an ODBC driver for connecting to Snowflake using ODBC-based client applications such as Sisense.
Sisense enables easy and quick access to databases, tables, and views within Snowflake which can be further used for reporting, analysis, and other BI functionalities. Sisense data connectors connect on-premises and cloud data to power your dashboards. It connects to all the widely used connectors such as Amazon Redshift, Snowflake, Google BigQuery, etc. Additionally, the Sisense connector allows customers to join, clean, and create data with code-free and code-first editors that write directly back to the Snowflake platform for decentralized uses. Sisense offers a 14-day free trial version.
Connecting to Snowflake using JDBC Driver — Live connection:
- On the Data page, open a live model or click +Live to create a new live model.
- In the Model Editor, click +Data. The Add Data dialog box is displayed.
- In the Add Data dialog box, select Snowflake.
- In Connection String, enter your connection string to your Snowflake database. To create a connection string.
- In User Name, enter your Snowflake user name.
- In Password, enter your password. OR Select Use Key Pair Authentication, and enter your Key Pair value.
- Click Next. All tables and views associated with Snowflake are displayed.
- From the Tables list, select the relevant table or view you want to work with.
- After you have selected all the relevant tables, click Done.
After selecting relevant objects, relationships between objects can be defined, enabling you to query and combine data from multiple tables in the dashboard.
After creating and designing a live model, the next step is to publish it. Publishing a live model adds the model to the list of the data sources selected when creating a dashboard or changing a data source. Now it is time to create visualizations.
Builders can connect to any data model created using the Sisense data engine when creating dashboards or visualizations on the front-end. Each dashboard can connect to more than one data model. All the tables and fields from the selected models are available to build visualizations in a drag-and-drop interface. Sisense provides several quick functions to do time-series and other math functions from an out-of-the-box library.
Filters can be added at a formula level, widget level, or dashboard level to enable slicing of the data by users. Again, every field in the data model is available for filtering. Due to the dynamic on-the-fly generation of queries and semantic data layer, end users can select slices of visualization to add a filter automatically (“Select”) or can drill into any visualization (if allowed by the designer and with security constraints in place) to find their own path of exploration.
Sisense Pulse is a centralized location where one can stay on top of your most important KPIs across multiple dashboards or manage the data and build alerts. By adding important KPIs from your dashboards to Sisense Pulse, one can get a comprehensive picture of your data from a single location. Sisense Pulse contains tiles that display information from the dashboards and the status of your ElastiCube builds.
The Sisense platform simplifies end-to-end data and analytics, reducing time-to-insights by empowering data and IT teams to build advanced data models and perform advanced analysis for their needs. It also provides a governed layer for business teams to autonomously analyze and visualize data of any size from a unified data layer.
Sisense provides a robust set of APIs to create fully customized and unique data experiences for users which is easily accessible to the users. Sisense connects directly to Snowflake’s data warehouse using the certified connector to flexibly deliver access to all present and future data for detailed data exploration and insights. Sisense can perform advanced analytics on your Snowflake data with R and AI Exploration Paths, NLQ, Insight Miner, and more. With a live link to a data warehouse, it can build rich, interactive AI-driven dashboards.