[Cloud Data Warehouse]
6 Reasons for Rapid Adoption in 2021

BI Connector Team |

Reasons for Rapid Adoption of Cloud Data Warehouse

Moving to the cloud is a new normal for businesses in 2021. 

The cloud craziness started around a decade ago with the birth of the SaaS business model in the Information Technology world.

In the early stages of the SaaS model, the offerings were focused primarily on an entire business function, say Marketing, Sales, Human Resources, etc.

However, as the years went by, a lot of SaaS solution creators have limited the breadth of their offering and deep-dived on the depth aspect. 

These SaaS offerings get a minor part (of a specific business function) of the job done, but with macro-level functionalities!

Examples: Zoom for web conferencing, Stripe for payments, Calendly for scheduling, Woodpecker for email campaigns. The list goes on in thousands!

Many leading SaaS solutions in every space also addressed the major objection – security concerns by achieving regulatory compliances such as HIPAA, SOC-2 based on their customers’ industry and unique needs.

Zooming back to the present, businesses are now moving their entire data warehouse to the cloud more than ever! 

And there’s heavy competition among the cloud giants like Microsoft, Amazon, Google, Snowflake in the Data Warehouse landscape!

In this blog post, we’ll see the 6 reasons for the rapid adoption of Cloud Data Warehouses in 2021.

What’s Cloud Data Warehouse

In layman’s terms, a Cloud Data Warehouse is just a database but hosted in a public cloud, instead of your company’s own hardware infrastructure.

Anyone with appropriate permissions to the Cloud Data Warehouse can store, edit, delete data, just like it’s done in a traditional Data Warehouse.

When you migrate to a cloud-based data warehouse, you can forget about your hardware infrastructure, as the hosting and managing tasks are entirely taken care of by your cloud solution provider.

The leading Cloud Data Warehouse providers rely on the columnar storage method (unlike row-based storage of a traditional data warehouse), and achieve a faster query performance.

There are many cloud data warehouse products available. In fact, cloud adopters are now facing challenges in choosing the best one that suits their needs. 

When the choices are limited, it’s quite easy to make a decision!

Google BigQuery, Amazon Redshift, and Snowflake are some of the major players in the Cloud Data Warehouse space.

At a high level, these products’ architectures are based on a cluster or serverless model.

Cluster-based Architecture

A cluster is a set of shared computing resources, usually referred to as nodes. 

Each node in the cluster comprises CPU, RAM, and Hard disk space. 

When more than one node is included in a cluster, one of the nodes is set up as a Master node, and the rest are Slave nodes. 

Therefore, the nodes in a cluster work based on a master-slave hierarchy. Amazon Redshift offers a cluster-based model.

In a cluster-based cloud data warehouse, you pay for a specified number of clusters as decided by you. 

Hence, the cost is easily predictable when you choose a cluster-based model.

Serverless Architecture

In the Serverless model, the hardware allocation is taken care of by the cloud vendor. The memory and computing resource allocation happens dynamically on a shared basis.

The cost is usually based on the data storage and queries executed at a given time. In most cases, the memory utilized by the queries is taken into account for pricing, rather than the number of queries.

As one cannot easily predict the queries at a given time, it is quite difficult to make an approximate prediction of the cost upfront while choosing the Serverless model.

Some individual queries may cost a fee higher than $1000 as well. It is important to caution your users and provide them with training when going for a Serverless model.

Google BigQuery and Snowflake offer the Serverless model.

Traditional Data Warehouse vs Cloud Data Warehouse

In this section, we’ll see how a cloud data warehouse differs from a traditional data warehouse.

FactorTraditional Data WarehouseCloud Data Warehouse
Hardware setupFalls under your company’s scope

Setup in the company’s server cabins (on-prem) private to your company
Falls under your cloud vendor’s (Amazon, Google, Snowflake etc) scope

Setup in Public, Cloud servers 
Hosting and maintenanceManaged by your organizationManaged by your cloud vendor
UpdatesManual

Timing and frequency decided by your company
Automatic

Timing and frequency decided by your cloud vendor
Data storage methodUsually as rowsColumnar storage provided by leading vendors
Backup servers for Business Continuity (in unforeseen scenarios)Created by your companyTaken care of by your cloud vendor
Query performanceVaries. 

Highly Depends on the volume of data queried, and the complexity of the query
Usually fast. 

For example, Google BigQuery can query several billion rows in a few seconds

6 Reasons for Rapid Adoption to Cloud Data Warehouse

Now we’re in the core part of this blog post. Let’s see the top 5 reasons for the rapid adoption of Cloud Data Warehouse in 2021.

The reasons are listed below:

  1. Simplified access from a browser with an internet connection
  2. Elimination of hardware infrastructure setup and maintenance
  3. Scalable-friendly (on both directions)
  4. Faster query performance
  5. More focus on core operations
  6. Flexible pricing options

Let’s run through them one-by-one in detail.

Simplified Access from a Browser with Internet Connectivity

The recent, ongoing pandemic is one of the major drivers for rapid cloud adoption. 

More and more businesses are migrating to the Cloud Data Warehouse now, and Work From Home (WFH) became a new normal back in 2020.

Though the situation seems to be getting back to normal, there are some pessimistic predictions by the World Health Organization (WHO) about the coming years.

These predictions made businesses take action proactively and switch to a Cloud Data Warehouse.

In many countries around the world, businesses are doubtful about opening their physical offices. 

Here, in the Western world, a lot of businesses, including some big brands have successfully adapted to the WFH culture.

Cloud Data Warehouse enables these businesses to let their employees work from home with a browser and an internet connection. The access to data is a lot more simplified.

Elimination of Hardware Infrastructure Setup and Maintenance

The biggest advantage of moving to the cloud (not just for Data Warehousing), is the elimination of associated hardware infrastructure setup and maintenance.

Your cloud solution vendor takes care of the hardware infrastructure. You’re just going to migrate the data to the cloud, connect your applications and start using your Cloud Data Warehouse right away.

The painful process of creating server cabins, purchasing the right set of hardware and setting them up, creating backup servers, maintaining their temperatures, etc is not required. 

Further, the upfront costs of setting up the hardware, and getting the server up for live are also eliminated.

Scalable-friendly (on both directions)

Just like a traditional Data Warehouse, the Cloud Data Warehouse providers also provide scalable-friendly solutions.

If your business is booming, it will generate more customers, and transactions, which are stored as data. 

Data scientists and AI practitioners rely on huge amounts of historic data to make predictions or automate decisions.

It’s not just about scaling up, but also about scaling down. 

When you scale up and realize that a smaller number of clusters (or queries) will work, most cloud solution vendors provide you with the option to downgrade (and scale down) in your next subscription cycle.

Faster Query Performance

As mentioned earlier, the leading Cloud Data Warehouse providers use the columnar storage method.

Hence, your queries perform at lightning speed compared to an equivalent query executed in a traditional data warehouse.

Further, in Cloud data warehouses, multiple computing resources can be deployed to run the same query paralelly and complete the execution much faster.

The cloud data warehouses equip your data scientists to analyze billions of rows of historic data in a matter of a few seconds.

More Focus on Core Operations

A Cloud Data Warehouse enables businesses to focus more on their core operations.

Before using a Cloud Data Warehouse, businesses spent a lot of time, money, and human resources on creating and maintaining an on-prem data warehouse.

Now they don’t have to worry about hosting, maintenance, hardware infrastructure setup, and associated issues, as all these falls under the scope of the Cloud Data Warehouse solution provider.

Flexible Pricing Options

The leading Cloud Data Warehouse providers all offer flexible pricing options.

The customers can simply start a free trial, and choose the pay for what’s used option, or fixed price on a monthly/yearly subscription on a range of plans.

It’s hard for businesses to choose the right plan that suits their needs. 

So you can upgrade or downgrade within a plan, or even switch between plans that work optimally to your needs and usage, at any time based on the frequency of your account’s subscription.

Data Warehouse Migration to Cloud: Critical Considerations 

If the reasons given above are good enough to migrate your business’s data warehouse to the cloud, here’s a quick heads-up on the critical considerations list:

  1. Regulatory compliances
  2. Architecture
  3. Applications integration
  4. User training

Regulatory Compliances

The leading cloud warehouse solutions are compliant with the major data privacy and security regulations like HIPAA, SOC-2, etc. 

However, you must ensure the solution you choose is compliant with such regulations applicable for your business/industry.

In fact, the regulatory compliance could filter out the providers who are not compliant and help you narrow down to a few potential options.

Architecture

The architecture is another key decision-influencing factor to help you narrow down and choose the right cloud solution provider.

If your business is budget-conscious and needs a clear estimate of the cost, a product with cluster-based architecture, such as Amazon Redshift is good to go.

If your business is not much concerned about the cost estimate and wants a “pay for what’s used” model, then Serverless architecture is the best choice. It’s good to opt for Google BigQuery or Snowflake.

Applications Integration

How many applications are connected to your on-prem data warehouse? How critical are they for your business? What are the dependencies among them?

Have a clear roadmap for integrating them to your Cloud Data Warehouse, and migrating your existing data to it.

There could be a learning curve here for the developers as they’ll have to adapt to the querying language of the solution you are opting for.

User Training

This is usually the most underrated consideration but has the potential to make or break the project. If users are not adapting to the change, there’s a high chance of project failure.

Hence, it is good to onboard your users to the new Cloud Warehouse before you go live.

Conclusion

Cloud Data Warehouse is well poised to become a necessity for all businesses in the near future, given its advantages over traditional data warehouses. 

The advantages of cloud data warehouses far outweigh the challenges in migrating to them.

The most critical step in your business’s cloud warehouse adoption is choosing the right product. Then it all comes down to people and processes. 

The success of your cloud adoption depends heavily upon how well the challenges mentioned above are tackled.