Snowflake's data cloud solution has already been adopted by over 4,000 organizations. It's one of the best data platforms for managing and combining multiple sources of data.

Modern businesses need as much data as possible to make the best decisions possible. They need to learn about their customers and trends in their industry, understand what’s happening within their organization, and be able to project outwards as a result. An integrated data platform solution is the best way to achieve this.

Read our guide to learn more about Snowflake storage integration. You'll discover how it works and how to approach it.

How Data Integration Works

Data integration combines and stores different types of data in a single, accessible location within the Snowflake warehouse via interfaces or open APIs.

This centralized storage unit is called a data warehouse which organizes the data for use in analytics and reporting scenarios. 

Data integration works by accessing source systems via APIs or interfaces to gather the data that’s needed in the data warehouse.  The data integration process handles multiple types of data, business rules, and transformation operations to standardize the data into formats that are usable. Snowflake data storage integration is a bi-directional operation that can place data in and take data from the data warehouse.

Several types of data may be stored in a Snowflake data warehouse. They include non-volatile, time-variant, subject-oriented, and integrated.

Nonvolatile data is used for operational updates. It needs to be loaded and accessed but doesn't require control mechanisms, recovery, or transaction processing.

Time-variant data keeps the information in the data warehouse current. It also ensures that the data is generated in real-time. 

Subject-oriented data contains categories such as customers, sales, products, and services. It allows businesses to focus on these individual subjects. They can create models and analyses for decision-makers.

Integrated data comes from a variety of sources. Examples include relational databases, online transactions, applications, and flat files. 

Snowflake Data Integration and Management

The most basic integration approach for Snowflake is ETL. The extract, transform, and load process is a set of steps that get the data into a format that is usable in the data warehouse. 

The extract phase involves exporting data from its source. The transform phase involves modifying it as needed. It uses a predefined set of rules, merges, lookup tables, and other conversion methods. The load phase involves importing the transformed data into a target database.

These steps can be performed in any order during Snowflake data integration. The program allows you to transform data after it's been loaded.

The process doesn't end once you've moved your data to a warehouse. The next step is to decide what to do with it.

Snowflake data management is part of the data integration process. It refers to the steps a business must take to acquire, store, protect, and process data. The goal is to make it compliant, accurate, and accessible.

While ETL provides the basics for getting data into and out of Snowflake it often doesn’t meet the needs of operational scenarios such as real-time analytics, governance, or quality.

Data integration via APIs is a preferred way to integrate into a data warehouse because all of the functions that are needed for faster processing, better data hygiene, and cross-platform connectivity are built into the integration layer.

Often this integration is done via a Snowflake connector which is purpose-built and can be either created by manual coding or a no-code configuration solution.

How to Use No Code Snowflake Integration

Fast and easy access to create integrated data from different sources is essential for every department, including sales, marketing, and customer service to prosper in the digitally-led environment.

Combining and managing all of this information on your own with code is a frustrating waste of time. You need an effective integration solution to take the burden off your shoulders.

Snowflake is a powerful data management platform. It has plenty of features of its own for managing data within itself and is strengthened with additional power tools like no code data integration.

There are 2 main solutions for Snowflake data integration as mentioned above, ETL and API centric.

A configuration-based alternative from a trusted provider like Put It Forward delivers the real-time, flexible and secure solution that simplifies the Snowflake data integration story

Risks of Using Snowflake ETL Solutions

Businesses need to trace their data history so they can intelligently notice hidden patterns, satisfy compliance needs and make successful business decisions.

A Snowflake data warehouse is useful for storing your data but it doesn't provide you with any capabilities to find hidden patterns by tracing its quality or lineage.

This makes it difficult to make Snowflake analytics-based decisions and causes problems in data compliance situations. It will leave your business unable to answer where the information originated from and how it’s been managed.

Snowflake's data governance solutions are basic and inhibit your data from being loaded into the environment by leveraging multiple-point vendor solutions that are difficult to layer together which can create more governance issues.

Multiple 3rd party solutions also make it difficult to scale your data management tools with conflicting ownership and SLA’s that move independently of your roadmap. You can't manage them yourself, and expanding them requires extra money, time and introduces complexity.

Single sourced configuration-based solutions offer an onramp for improving and controlling data governance within Snowflake.

Put It Forward's Configuration-Based Solution

Put It Forward offers an all-in-one data management system delivered for the Snowflake data warehouse. 

38% of businesses struggle with manual coding while Put It Forward's configuration-based solution eliminates the need for this complex process and the overhead with manual coding.

Our configuration-based solution increases the quality of your data. It lets you trace every piece of information that goes in and out of your Snowflake data warehouse. This helps with business decisions, compliance issues and improves everything driven by Snowflake analytics.

Our configuration-based Snowflake connector makes it easy to scale using the API delivering all of the important functions in a single easy to use interface. It eliminates the need to write new code or pay outrageous fees whenever you want to grow your Snowflake data warehouse.

Learn more about our Snowflake data integration solutions today.