Competitive Differentiator: Snowflake and Data

Competitive Differentiator: Snowflake and Data

87% of executives agree that data is the most important competitive differentiator in the business landscape today [2]. Enterprises must innovate and become more agile as the modern tech world continues to grow. One platform growing in popularity is Snowflake.

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Scale and Growth  

Snowflake allows data users to execute unlimited concurrent queries against data lakes without affecting performance [6]. As companies grow and scale, the need to transform and update data becomes more important. Snowflake allows you to build and run integrated, performant, and extensible data pipelines to process virtually all your data, and easily unload the data back into your data lake. Companies including McKesson, Adobe, and Door Dash all utilize Snowflake’s data storage and analysis tools for cloud infrastructure [3]. 

Holding the record for the biggest software IPO in the United States, Snowflake is valued at roughly $70 billion.  The platform was initially created to run on Amazon Web Services (AWS) and has since expanded to Microsoft Azure and Google Cloud. This allows for Snowflake to be both a customer and a competitor for these providers so even if they decide to cut ties with Snowflake, a “cloud lock-in” would occur which most enterprises generally want to avoid [4].  

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Security and Governance  

With recent security breaches and increased compliance and governance standards, it is more important than ever to have a data platform that simplifies security and governance integrations. Snowflake has the ability to ensure data governance and security even when the data is found in your existing cloud data lake. The benefits of being distributed across availability zones of the platform on which it runs like AWS or Azure allow Snowflake to tolerate component and network failures with minimal impact on customers. It is also SOC 2 Type II certified, with added levels of security like support for PHI data for HIPAA customers, and encryption across all network communications available [6]. Snowflake is also proving to be quite modern preventing your data lake from becoming a data swamp with the structure and control necessary.  

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Data Architecture and Data Lake  

Snowflake’s unique, cloud-built, multi-cluster shared data architecture makes the dream of modern data lakes a reality. It also allows organizations to easily share data with any data consumer through reader accounts created directly from the user interface allowing the provider to create and manage a Snowflake account for a consumer. On top of that, more than 2,000 customers implement Snowflake as the sole source of their analytics data [5]. In a recent STAND 8 case study, a client had to migrate a legacy warehouse into a modern data lake which enabled more than 1000 fields with scalable benefits. Our client is now able to predict outcomes with 91% accuracy [8]. Technologies like Snowflake can be implemented as a solution for companies that want to use a modern platform in situations like these.  

Competitors and Shortcomings   

Just like any platform in the tech world, there are several competitors and options for Data Lake solutions.  AWS announced their partnership with Moderna to create a vaccination for COVID-19 by helping pharmaceutical companies' scientists and engineers aggregate results from experiments. The team chose Redshift over Snowflake due to its speed of performance delivery and better optimization and customization [3]. 

Snowflake also has some limitations around ingestion and ETL offerings with Snow pipe known for being immature and non-optimal for enterprises [1] and may require more investments around those elements. 

Implementing Solutions

Data lakes offer significant advantages but also come with significant risks if not responsibly managed [8]. STAND 8 maximizes its value through a rigorous assessment, implementation, and end-to-end IT solutions to match the needs and scale. This can be the difference between scaling with success or holding back your enterprise needs especially when it comes to Data.  

Click the link below to learn about STAND 8’s previous article on data science with a focus on Apache Airflow or our case study on data lake deployment and management.  

https://www.dhirubhai.net/pulse/workflow-solutions-apache-airflow-jessica-delaney/  

https://www.stand8.io/insights/data-lake-deployment-powers-predictive-business/ 

 

By: Haley Graven and Jessica Delaney


 Resources:  

  1. Friday Night Analytics. “Top 5 Benefits and Detriments to Snowflake as a Data Warehouse.” https://fridaynightanalytics.com/snowflake-data-warehouse-pros-cons/  
  2. Maguire, James (2021) “Snowflake and Enterprise Data Platform.” https://www.datamation.com/big-data/snowflake-and-the-enterprise-data-platform/   
  3. Novet, Jordan (2020). “Snowflake’s complicated ties to Amazon present a long-term risk to IPO investors.”  https://www.cnbc.com/2020/09/16/snowflakes-ties-to-amazon-are-a-risk-as-investors-prepare-for-ipo.html   
  4. Sloan, Molly (2020). “How Snowflake Became a $70 Billion Company with the Largest Software IPO in History.” https://www.drift.com/blog/how-snowflake-grew/  
  5. Smoot, Rob (2019). “Snowflake as Your Modern Data Lake or Even Data Ocean.” https://www.snowflake.com/blog/snowflake-as-your-data-lake-or-even-data-ocean/  
  6. Snowflake (2021). “Snowflake for Data Lake.” https://www.snowflake.com/workloads/data-lake/   
  7. Snowflake (2021). “10 Predictions About Data Cloud Analytics in 2021.” https://www.snowflake.com/blog/10-predictions-about-data-cloud-analytics-in-2021/     
  8. STAND 8 (2021). “Data lake Deployment and Management from STAND 8 Powers Predictive Business.” https://www.stand8.io/insights/data-lake-deployment-powers-predictive-business/  
  9. Stitch (2021). “What is a Snowflake Data House? 5 Benefits to your Business.” https://www.stitchdata.com/resources/snowflake/   







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