The decision to choose between data modeling on Snowflake or Google Cloud can be challenging considering both platforms deliver excellent data modeling capabilities, especially if your business deals with big data. Ultimately, for any business that is deciding on selecting a data modeling tool, the top three considerations should include: Capabilities, Pricing, and Scalability. Here’s a quick guide.
Data modeling advantages for your business
Businesses today deal with massive amounts of data and it’s increasing exponentially. In order to understand customers, gain business advantage, and improve business decision making, this data needs to be effectively processed – a task that could take days or weeks, without advanced data modeling platforms such as Snowflake and Google Cloud Platform.
What is data modeling?
Data modeling is the process of organizing and mapping data in a simplified manner via the use of easy-to-understand diagrams, symbols, and text that represent different data associations and flow. Per Wikipedia:
“Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations. Therefore, the process of data modeling involves professional data modelers working closely with business stakeholders, as well as potential users of the information system.”
Top 6 benefits of data modeling
- Improved accuracy and consistency, as well as data predictability and standardization
- Expands access to business critical actionable insights
- Faster identification of data errors or data oversight and helps in reducing business risk
- Supports seamless integration of data systems with shorter development time
- Improved collaboration between developer and non-developer teams.
- Faster and more cost-effective maintenance and software updates
What is Snowflake?
Provided as a Software-as-a-Service, Snowflake is a highly flexible analytic data warehouse. Snowflake is provided on three major cloud serves, namely – Google Cloud Storage (GCS), Microsoft Azure, and Amazon Web Services (AWS). Supporting a SQL database engine, and Snowflake houses all data in one location. It is designed to be faster, while allowing for a simplified data usage. Uniquely suited to the cloud infrastructure, Snowflake supports simultaneous data access to multiple client business units, which improves business decision making. Snowflake features robust security capabilities and can provide businesses with an enhanced level of data accuracy and management, regardless of the business size and type. The cloud solution is also designed to provide support for a wide array of data types (both structured and unstructured) and features advanced set of BI tools unlike traditional data solutions that offer limited capabilities and capacities.
Plus, a major advantage of Snowflake is that it is designed to automatically scale up or down thereby delivering the needed balance between performance and cost.
What is Google Cloud Provider (GCP)?
Google Cloud Provider is a leading provider of cloud-based solutions which includes Infrastructure as a Service (IAS) and Platform as a Service (PAS), as well as serverless computing solutions. The extensive range of services provided by GCP are supported on the same cloud platform that supports Google’s highly popular end-user products. This includes Gmail, the search giant’s email service, Google Search and Google Photos, as well as its video platform YouTube.
According to Wikipedia:
“Google Cloud Platform (GCP), offered by Google, is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search, Gmail, file storage, and YouTube. Alongside a set of management tools, it provides a series of modular cloud services, including computing, data storage, data analytics, and machine learning.”
With robust security capabilities and infrastructure flexibility, Google Cloud Platform is a top choice among enterprises of all sizes that develop and run web-based applications.
Related Read – The Enterprise Guide to Google Cloud Services
Is Snowflake a good data modeling tool?
If you are considering Snowflake data modeling, then you should know that the solution supports multiple data modeling approaches. The Snowflake solution is ANSI-SQL compliant. So, you have at your disposal a wide range of SQL modeling tools. Snowflake has also introduced a VARIANT data type for semi-structured data storage such as AVRO, JSON, XML, Parquet, among other data storage formats.
In addition, Snowflake also supports the Oracle SQL Developer Modeler (SDDM). Oracle SQL Developer Data Modeler software helps in boosting productivity and again simplifies different types of data modeling tasks. Oracle’s SDDM tool allows developers to reconstruct or re-engineer Snowflake databases quickly and effectively. The Oracle SQL Developer Data Modeler tool is designed to support creation, browsing, and editing of data type models that are either logical, relational, physical, or multi-dimensional. For all these reasons, Snowflake is a terrific tool of choice for meeting data modeling needs of any business.
To know more about Snowflake data modeling, you can visit their Data Modeling Page.
Is Google Cloud good for data modeling?
Google’s BigQuery delivers a number of excellent advantages to address different data engineering requirements of businesses. Designed as a fully serverless solution in the cloud, BigQuery is capable of delivering super fast petabyte-scale data processing. The solution is also ANSI-SQL compliant and can effectively run machine learning and manage analytics processes at scale. And the fact that BigQuery can do all of this in a cost-effective manner, is what makes it a constructive data modeling option for businesses with big data requirements which is about every single one of them.
Cloud based data warehouses such as BigQuery are optimized and can effectively manage full table scans. This in contrast to traditional solutions which are designed for joins and tend to lean heavily towards indexing. This capability can make a huge difference when migrating analytical data to the cloud. Although Google Cloud Platform has its own data modeling software, most third party tools also have support for GCP. And while the degree of support can vary, nevertheless, your data modeling toolkit will work with GCP.
Do I need a Snowflake or GCP consulting partner near me?
Partnering with a data modeling consulting organization can be advantageous in several ways. Consider the following:
- Your chosen Snowflake or GCP consulting partner can work along with your internal analytics teams as well as system architects to help with the designing and implementation of data model tools unique to your business requirements.
- They can also assist your business in boosting the efficiency and quality of the data thereby reducing redundancy and also assist with streamlining integration, which in turn can help in designing a data model that is highly reliable, consistent, and intuitive.
- Finally, working with data modeling consultants also enables your team leaders and decision makers to quickly access accurate and real-time business information as and when needed. This is a money saver on every level. Time too!
It may be advisable to partner with a locally-based Snowflake or GCP consulting partner. They can work on-site with your analytics team and can seamlessly collaborate with your on-premise or cloud data center. Alternatively, when partnering with a data modeling consultant who is located remotely, ensure your chosen consulting partner has an established communication plan and virtual workflow to ensure a hassle-free data modeling process.
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