A frequently required application in recent job-offers.
Let's kick this story in with an me info-bomb: here you find a link collection that I read through while checking the functionality of the SnowFlake environment.
As far as I checked the requested software skill lists in job offers on several web platforms, SnowFlake is more and more present in those. I became interested in this service and at first sight it seemed to me highly clean, well-organised and user friendly web-service.
„A PLATFORM LIKE NO OTHER
Snowflake’s single platform eliminates data silos and simplifies architectures,
so you can get more value from your data.”
The motto and the short description suggests that this platform simplifies working with data starting from data loading and storing, through data handling and modification to demonstrations. Simple graphs as line or bar chart are optional output formats, however heat map is also an option but does not have the shiniest graphical representation. On the other hand this is not a problem as SnowFlake mainly serves as a background datastore for BI tools for example Power BI or Tableau. Additionally such full-service (or software as a service) platforms as Microsoft Fabric may also use SnowFlake as data source in its complex system.
SnowFlake is a cloud-based data storage and processing platform designed to manage and analyse large volumes of data. Although it is not the market leader, Snowflake is easily comparable to other similar applications, i.e. cloud-based data management and data analytics data warehouses, such as Amazon Redshift, Google BigQuery, and Microsoft Azure Synapse Analytics (formerly Azure SQL Data Warehouse) and ranks quite well in the comparison.
On the very first sight it is clearly visible that the developers of SnowFlake had an intention to create a clear and user friendly outlook and they really did an amazing job.
SnowFlake’s services, beside data storing include Python and/or SQL based data manipulation both of which can be used in the platforms’ Notebooks. AI & ML applications can be also easily developed on the Cloud platform. It offers customable resources as storage volume, computational power, numbers of users, projects… in one word a scalable engine. Easy integration of 20+ external resources so other platforms can serve as data storage in the background or may be chosen as options for migrating data to other platforms and get further benefits from involving other services. Scalable, customizable and a real „pay what you use” type of system.
Advantages of SnowFlake
Scalability and performance
- Snowflake uses a unique, distributed architecture, which means that compute and storage resources can be scaled completely separately, making the data warehouse more cost-effective to run. In similar applications, compute and storage are not separated to this extent, which sometimes limits the flexibility of scalability.
- With auto-scaling, Snowflake can automatically scale its resources based on workload, enabling high-performance data analysis even under varying workloads.
Simple use and administration
- Snowflake users do not need to manage separate servers or infrastructure, so the administration of data management is much simpler than at some other platforms.
- It provides easy integration with other cloud services, which simplifies the consistent storage and access/management of different data. Snowflake supports multiple cloud platforms, such as AWS, Google Cloud, and Azure, giving users the freedom to choose between infrastructures and making it easier to build a multi-cloud strategy.
Data sharing and security
- Snowflake's innovative data sharing capabilities enable secure and real-time data sharing with other Snowflake users without the need to create data copies. This makes data sharing more efficient and reduces problems related to managing redundant data.
Deficiencies
Costs
- Although flexible and cost-effective in terms of scalability, in some cases long-term costs may be higher. With some providers, large enterprise discounts may be more cost effective.
Limitations of integrations and tools
- Although well integrated with major cloud providers, the range of data integration and ETL tools may seem limited compared to some other platforms.
SQL support and custom functionality
- Snowflake has the
SnowSQL engine that does not support all special statements outside the
SQL standard. This may be a slight disadvantage for those who want to use the custom SQL syntax that is common in other SQL engines. But of course, this can also be seen as a standards-compliant approach.
Dependence on cloud providers
- Although it supports several cloud providers, being a fully cloud-based solution it is not available as a locally deployed version, which some companies prefer for security and privacy reasons.
If you got interested, see
pricing or how to
become a pro (unfortunately, I have no interest in sharing the links).
Updates
On 01 Dec 2024
How should I have started using and practicing?
My free trial period is over since a week, but it came to my knowledge - when I arranged learned things and these posts - that there are free online discussions organized by Snowflake quite often that may newbies in starting the excursion.
For example I would have watched these:
"ZERO TO SNOWFLAKE IN 90 MINUTES - Virtual hands-on-lab"
or
"SNOWFLAKE DISCOVER - Build the Right Data Foundation to Maximise Your Potential"
As those are ahead of me, I will still attend to get a deeper understanding of the power and functionality of the services.
Continue with
No comments:
Post a Comment