Sisense Snowflake Integration: 3 Easy Methods

on Data Analytics, Data Driven, Data Integration, Data Visualization, Data Warehouse, ETL Tutorials, Sisense, Snowflake • September 20th, 2021 • Write for Hevo

Sisense Snowflake Integration FI

Database and Data Warehousing technology is continuously growing, and new developments are becoming more prevalent. Many solutions now exist to assist you to link various Data Warehouses so that you may make use of both technologies. One such solution is connecting Sisense and Snowflake.

Snowflake is a prominent Cloud Data Warehousing solution that has shown steady growth in recent years. It enables businesses to build a Data Warehouse solution to store data. After data has been stored in a Data Warehouse, companies try to extract insights from it. The Sisense Analytics platform enables Data Engineers, Developers, and Analysts to create analytic apps with a rich user interface.

This article will give you a comprehensive guide to set up Sisense Snowflake integration. It will also provide you with a brief overview of Sisense and Snowflake with their key features. You will also explore 3 popular methods for Sisense Snowflake integration. Moreover, the benefits of setting this integration will also be discussed in further sections. Let’s get started.

Table of Contents

Prerequisites

  • An active Snowflake Account.
  • An active Sisense Subscription.
  • Working knowledge of Databases and Data Warehouses.

Introduction to Snowflake

Snowflake Logo
Image Source

Snowflake is a Cloud-based Data Warehousing tool founded in the year 2012. Storage, Reporting, and Analysis are the key factors of the leading cloud computing-based Data Warehousing solution. Over time, Snowflakes has also built strong roots in Data Management, Data Analytics, and Data Warehouse markets. With the help of Snowflake’s cloud-based hardware and software tools, many corporate users can now easily store and analyze data. 

The tool is highly beneficial for corporate houses as it can keep a record of both structured and semi-structured data, deliver faster reports, and perform data analysis at any scale. Snowflakes run on Microsoft Azure, Amazon S3, and the Google Cloud platform, regardless of your data structure or volume, cloud or region. Snowflake’s unique approach has enabled organizations of all sizes to analyze, securely share data, reduce operational complexity, and accelerate business value.

Key Features of Snowflake 

The Snowflake data platform runs on cloud infrastructure and has some of the best key features that make Snowflake a distinct Cloud Data Warehouse. Have a look at the key features of Snowflake:

  • Scalability: Snowflake architecture comprises independent layers – storage and compute. This strategy makes it easier for the users to scale up or down resources as per their requirements. For faster data loading, users can scale up the resource and pull back down as the process is completed. Without causing any interruption to the service, customers may commence the extra-small virtual warehouse and work on it as needed.
  • Auto-scaling and Auto Suspend Feature: It works great during unpredictable resource-intensive processing as it helps to start and stop clusters automatically. It also helps put a halt to the virtual warehouse if the clusters are not working for a defined period.
  • Concurrency and Workload Separation: As per Snowflake’s multi-cluster architecture design, storage and compute resources work independently. Thus, queries from one virtual warehouse will hardly cause any effect due to the queries from another resource. Concurrency is nowhere an issue in Snowflakes. The Workload Separation mechanism enables smooth running of ETL/ELT process, better data analysis operations, and faster report delivery.
  • Near-Zero Administration: Snowflake does not require the involvement of any DBA (Database Administrator) or IT ()Information Technology) team for installing software or hardware. Snowflake is a cloud computing-based Data Warehouse solution delivered as a service that incorporates new features and patches that help enhance virtual warehouse size and increase clusters.
  • Security: Snowflake can discover hundreds of sensitive data elements, making it crucial to have a high level of security system. Snowflake encrypts all customer data, offers dynamic data masking, and supports two-factor authentication, SSO for your data security.

To know more about Snowflake, visit this link.

Introduction to Sisense

Sisense Logo
Image Source: Sisense

Sisense is an AI-driven (Artificial Intelligence) end-to-end BI (Business Intelligence) solution that provides insights on complex data for the smooth working of business operations and achieving better results. Sisense provides analysis and data visualization of multiple complex data sets faster than any other platform. It infuses analytics into every workflow, process, or application and provides rapid ROI (Return On Investment) reports. Further, it consolidates, stores, and accumulates data. Many organizations look forward to embedding Sisense into their businesses for better outcomes.

Key Features of Sisense

Sisense has gained wide popularity in the market. Some of the key features of Sisense include:

  • Easy to use reports interface.
  • Provides a wide range of widgets including gauges, charts, and graphs.
  • Consolidates data correctly and delivers 100% accuracy.
  • Ad-hoc analysis of data.
  • Does not require programming or SQL (Structured Query Language) writing for complex business queries.
  • Collect data in large volumes from multiple sources at high speed.
  • Creates robust dashboards for any device with additional features to customize easily.
  • Reduces the redundancy of distributed reporting.
  • Improves cost forecasting.

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Methods to Set Up Sisense Snowflake Integration

Sisense Business Intelligence (BI) solution offers quick access to databases. Sisense Snowflake integration will enable users to access the collected information in the databases, tables, and views for better reporting, analysis, and other activities. Check out some of the different methods to set up Sisense Snowflake integration.

Method 1: Sisense Snowflake Integration by Creating Live Connection

To set up Sisense Snowflake integration, one needs a connection string responsible for identifying the Snowflake database and its credentials. It is essential to add the warehouse name (warehouse=<name>) and database name (db=<name>) in the connection string.

In case you can’t provide user credentials, opt for Key-Pair credentials for authentication.

Follow the steps to add Snowflake live connection in Sisense:

Step 1: To create a new live model, go to the Data page section. Open a live model or click + Live

Step 2: Under the Model Editor section, click +Data, and Add Data dialog box will pop up.

Step 3: Select Snowflake in the Add Data dialog box.

Step 4: Add your connection string to your Snowflake database.

Step 5: Fill Snowflake user name and password or use the Key Pair value by selecting Use Key Pair Authentication.

Step 6: Click next to view all the tables and views associated with Snowflake.

Step 7: Choose the relevant table or view from the Table list you want to work on.

Step 8: After selecting the tables, click on Done and it will be added to your schema.

Method 2: Sisense Snowflake Integration by using ODBC Drivers

Sisense has made it easy to connect and integrate the Snowflake Data Warehouse. The process has become quick, easy to generate, and offers better analysis. In this method, you will get to know how to set up Sisense Snowflakes integration using the desktop ElastiCube Manager. Let’s discuss the ODBC driver provided by Snowflake to connect with ODBC-based client applications like Sisense. This method can be categorized into 3 sections:

  • Downloading Snowflake ODBC Driver
  • Adding DSN
  • Importing Snowflake Tables into Sisense Projects

1) Downloading Snowflake ODBC Driver

Step 1: Visit Snowflake’s official website to download and install the Snowflake ODBC Driver.

Step 2: Go to Sisense, click Add Data and later select Generic ODBC Driver.

Step 3: See if you have a DSN file or not. If you have one, select DSN from the dropdown list, and click on Test Connection. If you have to create a DSN file, choose the option to add a DSN visible on the screen. After setting up the connection, click Ok. Have a look at the tables generated through the Snowflake ODBC driver.

Or

Go for Connection String (DSN-Less). Fill in your connection string details and click Test Connection.

2) Adding DSN

If you can’t find a way to create DSN, try adding it manually. It is important to run the Sisense ElastiCube Manager as an administrator to run a DSN.

Step 1: Press DSN and choose the System Data Source option. This option helps create a data source that applies to all users in a specific machine and who all log in to the machine. Click Next.

Create New Data Source: Sisense Snowflake Integration
Image Source: sisense.com

Step 2: Click on the Snowflake ODBC Driver, and click Next.

Step 3: Now, click on the Finish button.

Step 4: A Snowflake Configuration Dialog box will pop up. Fill in the following details in the Snowflake ODBC Driver DSN Setup window:

Snowflake Configuration Dialog Box
Image Source: sisense.com
FieldDescription
UserAdd Snowflake user name
PasswordAdd your Snowflake password
ServerSnowflake provides a domain name for your account
DatabaseSpecify the default database initiated by the driver to use for sessions
SchemaList the default schema initiated by the driver to use for sessions
WarehouseUpdate the default warehouse initiated by the driver to use for sessions
RoleSpecifies the default role initiated by the driver to use for sessions. Make sure the specified role has to be assigned to the driver. Note: The role cannot be used for sessions initiated by the driver if not properly assigned.
TracingDetails to be logged in the driver trace files:0 = Disable tracing1 = Fatal only error tracing2 = Error tracing3 = Warning tracing4 = Info tracing5 = Debug tracing6 = Detailed tracing

Note the following facts when entering the above-listed parameters:

  • To create a DSN, you only need a Data Source, User, and Server.
  • The Password field does not save your value for security purposes.
  • Apart from these, the other listed parameters in the configuration Dialog box are optional.
  • Click OK.

3) Importing Snowflake Tables into Sisense Projects

Once you have set up the DSN, add the table from the displayed Snowflake Tables window. With the help of this window, you can easily transfer Snowflake tables to Sisense. Additionally, under the Query Preview section, you may view the SQL syntax and modify it by clicking on the edit button.

Follow the below steps to add Snowflake Tables to your Project:

  • Use the Sisense ODBC Tool to connect Snowflakes.
  • Now, add your data source.
  • Choose the table you wish to add to Sisense from the Snowflake Tables window.
  • Press on the add button, and the selected tables will be transferred to Sisense.

Method 3: Sisense Snowflake Integration for Cloud Data Teams

Make sure to have a Snowflake account with an Account Admin Role before you begin connecting Sisense for Cloud Data Teams to Snowflake.

Step 1: Setting up a Sisense Role

As you know, Snowflake exercises role-based access control. Thus, the first step to create a Sisense role is to make sure you have permission to access the database that has to be connected. Any permission granted to the new role will be inherited by the parent role.

Create Sisense Role
Image Source: website-files.com

Step 2: Setting up a Sisense User

Go to the User section within the Snowflake Account tab to add a new user for Sisense.

Set Up Sisense User
Image Source: website-files.com

Add a name to the account and choose a password.

Create User
Image Source: MongoDB

Do not miss on filling in the user preferences. In the default namespace section, add the database name you want to connect

Step 3: Configuring Permissions for Sisense Roles

Login in with the Account Admin role and open the Worksheet tab of Snowflake. As visible in the screenshot, run a few commands, substitute your warehouse and database information. Make sure that every command gets executed. However, there is a setting in the worksheet according to which only the first command will be executed.

Worksheet Tab of Snowflake
Image Source: website-files.com

Step 4: Adding DB Credentials

Go to the address bar of your browser and copy the account name as visible in the Image.

Adding DB Credentials - Sisense Snowflake Integration Method
Image Source: website-files.com

Select a display name and fill in all the credentials. Now press the add button to complete the connection.

Adding Database - Sisense Snowflake Integration Steps
Image Source: website-files.com

Benefits of Setting Up Sisense Snowflake Integration

Some of the benefits of setting up Sisense Snowflake integration include:

  • Sisense Snowflake integration allows you to easily create rich, interactive dashboards and adapt to changing user needs.
  • Sisense Snowflake integration enhances the user experience and also provides non-technical users with access to analytics and control over data models.
  • Sisense Snowflake integration allows you to use R and AI Exploration Paths, NLQ, Insight Miner, and other tools to do advanced analytics on your data.
  • With Sisense Snowflake integration, you can easily scale up and down in real-time to match spikes in hit rates.

Conclusion

The Sisense platform eases the procedure of analysis and data visualization of any size from a unified data layer for business leaders. Further, it provides customized and unique data experiences. Thus, Sisense Snowflake integration can perform advanced analysis, create a single store for your data through SQL, Python, and R, power self-service dashboards, and actionable analytic apps that can be implanted anywhere.

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Share your experience of learning about Sisense Snowflake integration in the comments section below!

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