So far technology has been taking us for a spin, we have been drowning under that mass called data, and if that is not enough, Big Data keeps pulling us 5 ways (volume, velocity, variety, veracity, and value).
Not painting a great picture, am I? But then a host of data engineers, data Scientists, and infrastructure support members came to everyone’s rescue, helping us ensure that the integration between systems is flawless. But we haven’t gone that far, have we? Still talking to the wall instead of the engineering team, too many touch points, fragmented environments resulting in lack of cohesive monitoring, silos of data and meta data, and an incoherent security architecture.
The data and analytics workload continues to move in large numbers from private on-premises data centers to public cloud environments. Organizations try their best to reduce expenditures like those incurred procuring hardware and keep hoping to soon reach that point so they can speed, scale, and be agile.
So how prepared is your organization to address the role of cloud in their lives? How prepared are you to increase your efficiency, improve your cash flow, and lower your operational costs?
Data warehousing, simply put, allows you to electronically store ginormous amounts of information. So usually, this system is used for reporting and data analysis purposes- in short what those in BI (business intelligence) use extensively. You can store historical data in these warehouses by integrating transaction data from various sources.
So using a cloud platform for data warehousing, speaking in plain English, means using a platform that allows you to securely share and consume shared data. It will provide you with services like servers, storage, databases, networking, data analytics, and intelligence on the cloud so you can innovate faster, and scale quicker.
Here are the top 3 reasons why moving to cloud is a good idea:
I wouldn’t give the credit as much to cloud as to COVID for better team collaboration in these times. But yes, Cloud does help you collaborate better on shared data with your teams, and one major reason is because you can access it anywhere, and using multiple devices.
Storing data physically is a tad expensive and expanding your data footprint is going to be tough with cables attached. In order that your analytical needs are met, you scale independently, compute as much as you want, and store perfectly, choosing a Cloud data warehouse is what will work best.
And you thought having things right where you can see this is secure. Digital copies are more secure now more than physical copies, so having your data warehouse in the cloud is any day more secure than an on-premise system. It is important that you choose the right cloud platform and the right business model that stresses more on encryption and security.
And here is another reason I think, that is as important, Cloud can help you simplify your infrastructure and reduce your capital investments since you then use even more services linked to data warehouse like data management, business intelligence, etc.
Now that you have the reasons why you should go the cloud route when it comes to data warehousing.
Let’s take the next step, and find out in what way can a data analytics platform help you solve your problems with data and ship you off to cloud in a much faster and seamless way?
Not much apart from it being able to:
That sure does answer some questions people have, like maybe do I really want a data warehouse on the cloud?
Let me take you a step further into that question, you need to choose the right cloud data platform so that your data warehousing, data lakes, data engineering, and data science needs are taken care of correctly.
So, a cloud data platform as I was saying can give you an infinite amount of flexibility, analyze better and securely share your data. Since it has a multi-cluster shared data architecture, all your data can be accessed by you virtually without your performance being impacted. Being on one single platform makes Snowflake the right choice for you since security, performance, and maintenance can all happen in one place.
|Criteria||Snowflake||Shared Data (Traditional DW)||Shared Nothing (Netezza/ Redshift)||Hub and Spoke (S3 +Athens)||Cloud Query Engines (Athena)||Importance|
|Low-latency, high- performance across simple and complex queries||Yes||Yes||No||Limited||Delivers faster business results|
|Easily join structured and semi-structured data for analytics||Limited||Limited||More complex||Limited||Enables 360o views, multi-channel data analytics|
|Unlimited query concurrency within a single, integrated platform||Limited||Limited||No||Limited||Eliminates data duplication costs and complexity|
|Unlimited connections within a single, integrated platform||Limited||Limited||No||Limited||Supports as many accesses to platform as needed, while avoiding data duplication|
|Multi-statement ACID transactions||Yes||Yes||No||No||Assures pipeline and transactional integrity for single and multi- table inserts|
|Workload isolation, within the same integrated platform and single source of truth||No||No||No||No||Matches resources to business needs with maximum simplicity|
|Instantly scale up, down, out or in without disruption||No||Limited||Very Limited||Limited||Delivers fast execution and ensures environment stays up and running when scaling|
|Simple management, e.g., no indexing, no manual partitioning||No||No||No||Yes||Enables data teams to attain higher strategic focus|
|ZeroCopy Cloning||No||No||No||No||Simplifies test-dev with full production data, while eliminating storage duplication|
|Cross-cloud operation||No||No||No||No||Provides strategic and operational flexibility across clouds|
So, using the right solutions expert, can help provide end user access to raw data sets in Snowflake, and your data engineers can focus on activities that increase analytics, including integrating more data sets. Snowflake’s pay-per-second model offers significant cost savings compared to the instance-based pricing of traditional data analytics solutions.
You can maximize your return on investment with single analytics repository & gain richer insights for a fraction of the cost and effort if you use the right cloud platform. It is important that you have the right software solutions company providing you with a scalable solution so you can experience fast and reliable system performance at a low cost.
This is perhaps reason enough for you to invest in a cloud data warehouse, right about now. Write to us, to learn more about our services, and to learn how we can help you overcome barriers to scalable data analysis and data science.
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