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.
Prerequisites
- An active Snowflake Account.
- An active Sisense Subscription.
- Working knowledge of Databases and Data Warehouses.
Introduction to Snowflake
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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
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.
Hevo Data helps you directly transfer data from 100+ data sources (including 30+ free sources) to Business Intelligence tools, Data Warehouses, or a destination of your choice in a completely hassle-free & automated manner. Hevo is fully managed and completely automates the process of not only loading data from your desired source but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.
Hevo takes care of all your data preprocessing needs required to set up the integration and lets you focus on key business activities and draw a much more powerful insight on how to generate more leads, retain customers, and take your business to new heights of profitability. It provides a consistent & reliable solution to manage data in real-time and always have analysis-ready data in your desired destination.
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Check out what makes Hevo amazing:
- Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
- Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to the destination schema.
- Minimal Learning: Hevo, with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
- Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
- Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
- Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, E-Mail, and support calls.
- Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.
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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.
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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:
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| Field | Description |
| User | Add Snowflake user name |
| Password | Add your Snowflake password |
| Server | Snowflake provides a domain name for your account |
| Database | Specify the default database initiated by the driver to use for sessions |
| Schema | List the default schema initiated by the driver to use for sessions |
| Warehouse | Update the default warehouse initiated by the driver to use for sessions |
| Role | Specifies 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. |
| Tracing | Details 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.
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Step 2: Setting up a Sisense User
Go to the User section within the Snowflake Account tab to add a new user for Sisense.
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Add a name to the account and choose a password.
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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.
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Step 4: Adding DB Credentials
Go to the address bar of your browser and copy the account name as visible in the Image.
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Select a display name and fill in all the credentials. Now press the add button to complete the connection.
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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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Businesses can use automated platforms like Hevo Data to set the integration and handle the ETL process. It helps you directly transfer data from a source of your choice to a Data Warehouse, Business Intelligence tools, or any other desired destination in a fully automated and secure manner without having to write any code and will provide you a hassle-free experience.
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Share your experience of learning about Sisense Snowflake integration in the comments section below!
Hitesh is skilled in freelance writing within the data industry. He creates engaging and informative content on various subjects like data analytics, machine learning, AI, big data, and business intelligence byusing his analytical thinking and problem solving ability.