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Cloud Data Warehouse Impact On Modern Business Industries

KEY TAKEAWAYS

Cloud data warehouses are a managed service central repository, delivering better scalability, performance, and cost-effectiveness. They offer hassle-free data management, easy data access, real-time analytics, AI and MI applications, and can be beneficial for businesses looking to leverage the cost and scalability that managed services can provide. While on-premises data warehouses have advantages such as control, governance, and speed, they require technical staff and have limited scalability.

In today’s world, enterprise cloud infrastructure has moved many complex business applications like databases, ERPs, and Marketing solutions to the cloud. Therefore, organizations preserve and maintain critical data of most businesses in the cloud nowadays. However, the data warehouse system for the cloud is a quite new chapter in this trend.

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For smooth business operations, companies require a coherent solution to store, access and maintain that enormous amount of data. So, they realized the need for such storage that can flawlessly store the data from all the different cloud-based applications. At that time, modern technology introduced Cloud Data Warehouses in the market.

However, before going forward, we first need to know what a data warehouse is. So let’s get started.

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A Brief About Data Warehouse

A data warehouse is a storehouse of the organization’s present and historical information that creates the root of an organization’s business intelligence infrastructure. 

Companies use it for structured and semi-structured data analysis and reporting of various data generated from multiple sources, such as sale transactions, marketing automation, customer relationship management etc.

Despite being a Relational Database Management System (RDBMS) that runs SQL-like queries, a data warehouse runs analytical queries on large data sets. It is competent for ad hoc analysis and custom reporting. 

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What Is Cloud Data Warehouse?

It is a managed service central repository delivered in a public cloud that is effective for analytics, scale, and usability. Cloud service provider companies manage and host data in the cloud infrastructure. Cloud data warehouses collect data from various sources and store it in a structured way. They offer better access, scalability, and performance that help companies concentrate on their businesses rather than managing a server room.

Traditional Data Warehouse vs. Cloud Data Warehouse

Unlike traditional ones, cloud data warehouses don’t need a physical location, hardware devices, server rooms, or technical staff. Cloud service providers manage everything instead.

Benefits of Cloud Data Warehouse

With the grace of modern technology, several companies now prefer to use cloud data warehouses. From the business perspective, this approach helps them leverage the saving cost and scalability that managed services can deliver.

Here’s a list of some benefits that cloud data warehousing offers:

Hassle-free Data Management

Companies can concentrate on their business operations, and development plans by putting the technical responsibilities to the cloud provider company for data storage, management, and security purposes.

Better Scalability

Because of the flexibility of cloud computing, businesses can scale up and down as per customers’ requirements. The cloud data warehouse doesn’t need to buy new hardware and the scaling can occur automatically when needed.

Cost-effectiveness

Users can eliminate the charges to purchase hardware, server rooms, manpower, maintenance, upgrades, overhead, and installation.

ML/AI Applications and Analytics

By implementing the latest technologies like machine learning (ML) and artificial intelligence (AI), companies can run predictive analytics for making advanced business decisions.

High-speed Performance

A cloud data warehouse allows requests to be executed much faster than they are against a traditional on-site data warehouse, for a cheaper cost.

Data Access

Keeping their data in the cloud allows organizations to give their analysts access to real-time data from various places which helps them to run advanced analytics fast.

On-premises Advantages

Control, governance, speed, security, and availability are all advantages of on-premises data warehouses.

Control

With the on-site deployment, a business has complete control over what software and hardware to use, its location, and who has access to it. The equipment may be storage devices and commodity servers that are already used for other applications, or customized servers.

An IT worker has physical access to hardware and each layer of software to refine troubleshooting in the case of any issues. 

They can look into and repair hardware as required. They don’t have to depend on outside help to get the system back to functioning again.

Speed

While some data sources can be off-site and only accessible through the Internet, having all the hardware and tools on-site alleviates concerns about network latency. Other factors may have a larger impact on performance than network slowdown. This happens if the on-premises solution isn’t properly sized.

Governance

By using an on-premises data warehouse, regulatory compliance and data governance are quite easier to attend. Several businesses, fail to meet the General Data Protection Regulation (GDPR) standards to spot the data location. Using an on-premise data warehouse, one knows precisely where the data remains. 

On-premises Challenges

Maintenance

On-premises, the data warehouse provides total control. The devices are installed by network engineers, system engineers, network security experts, database admin etc. They take care of the maintenance of the entire system and manage the all hardware and software parts of it.

Their tasks involve device installation, moves, and software updates. That’s why they are fully responsible to make the infrastructure up and running with high efficiency in a protected manner.

Scalability

Moreover, on-premises data warehouses are not enough capable to handle multiple activities that need additional computation. In high usage time, companies must purchase the necessary infrastructure to upscale their data warehouse to handle it. Sometimes it doesn’t satisfy the demands.

When compared to on-premise solutions, what are the advantages of cloud data warehouses?

The traditional data warehouse is often not capable to meet an enterprise’s demand. It has failed to provide companies with the required speed, scalability, and agility they want. Therefore, industry specialists expect the cloud data warehousing market may reach $3.5 billion by 2025.

On-premises data warehouses are tough to build than cloud-based data warehouses. The latest cloud data warehouse allows high data volumes, and may create stores, and processes data from different places, both on-premises and in the cloud.

Also, most cloud data warehousing systems permit Pay-as-you-go services, unlike the old ones.

Cloud Data Warehouse Provider Companies

In the competitive cloud technology market, there are a couple of big enterprises that offer quality data warehouse services. Some of the names are Google Big Query, Amazon RedShift, Snowflake etc.

Final Thoughts

Experts hope that cloud data warehousing is a game changer in cloud technology and the next generation of data warehousing. If people can utilise it appropriately, cloud data warehouses can be a highly cost-saving system and enough efficient to fulfil all future business requirements.

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Written by Kuntal Chakraborty | IT Engineer

Kuntal Chakraborty is an IT Engineer by profession and education. He has worked as a Systems Engineer and Network Engineer at Siemens and Atos.

Kuntel's current passion is Artificial Intelligence(AI) and Machine Learning (ML). The skills he has developed for Amazon's Echo can be acccess through the Alexa app or Amazon website.

Kuntal Chakraborty is an IT Engineer by profession and education. He has worked as a Systems Engineer and Network Engineer at Siemens and Atos.

Kuntel's current passion is Artificial Intelligence(AI) and Machine Learning (ML). The skills he has developed for Amazon's Echo can be acccess through the Alexa app or Amazon website.

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