On premises or cloud data warehouses for Enterprise Data Analytics

On premises or cloud data warehouses for Enterprise Data Analytics

“Cloud computing is often far more secure than traditional computing, because companies like Google and Amazon can attract and retain cyber-security personnel of a higher quality than many governmental agencies.” 

Vivek Kundra, former federal CIO of the United States

A comparison study to evaluate different aspects of cloud data and on premises to conclude which one is the best choice  

WHAT DOES A DATA WAREHOUSE LIKE CLOUD OR ON PREMISES DO? 

A data warehouse also called an enterprise data warehouse is a system which gives reports and data analysis to assist in the ongoing decisions making in the organization. For this reason, it is also considered to be a core component of business intelligence. DWs are the best solution for analytics reporting and business intelligence, since transactional databases aren’t much suited to analytical processing. Its main function is to offloads analytical processing from transactional databases and provides faster processing speed through the use of data store, which allows the users to have access to any relevant data they search for.  

On premises and cloud are the two types of enterprise data warehouses and both are quite prevalent among its users. To choose between the two would become easy once we understand their benefits and challenges:- 

BENEFITS OF ON-PREMISES AND CLOUD DATA WAREHOUSE 

ON-PREMISES  

  • Complete control over the tech stack; with an on-premise deployment, an organization has complete control over the hardware and software, its use, who will have access to it and where the data gets stored. In the event of a breach or failure, an IT team doesn’t have to reply on third party vendors to get the data and system back up and to keep the business running.  
  • Local speed and performance; one of the biggest benefit that you get by using on-premises is to have a really good level of speed when you are looking for a specific data, as information is stored in hardware form and the user can have access to it even if there is no network latency.  
  • Governance and regulatory compliance; it is easier to achieve data governance and regulatory compliance. Many organizations struggle to meet GDPR requirements as it is easier to locate and to identify data.  

CLOUD DATA WAREHOUSE 

  • On-demand scalability; within Cloud data warehouse, the problem of limited storage doesn’t come, that’s why data can flow easily as the capacity for its storage is limitless.  
  • Cost efficiency; by using cloud data warehouse, companies no-longer have to invest in buying physical servers and they are required to pay for only what they need.  
  • Bundled capabilities such as IAM and analytics; cloud data warehouse can leverage other cloud services platforms, e.g., identity and access management services as well as data analytics tools.   
  • Security; It has been reported that cloud data posture security is better than the on-premises security, even though the risk are higher in cloud data warehouses, but organisations invest heavily in physical and logical security tools. They secure their security controls with certifications such as ISO 27001 and SOC 2.  
  • System uptime and availability; cloud service providers focuses quite diligently on availability and reliability of their services, therefore a service level of 99.9% availability is seen in cloud services than on-premises. Even in the event of failure, cloud environment makes your data available within different time zones and regions.   

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CHALLENGES OF ON-PREMISE AND CLOUD DATA WAREHOUSE 

ON PREMISES 

  • On-premise data warehouse cannot handle and adapt to bursts of activity which need more compute and memory work.  
  • While using O-premises, an organization loads all the memory in storage device to the level of peak and only portion of data is required at times, other storage is there to engross the space.    
  • This warehouse is not great when it comes to changing needs of new demands, which is a very feature required in our times. 

CLOUD DATA WAREHOUSE 

  • The problems that come with cloud data warehouse services are in data integration, provider lock-in, security, possibility and latency. 
  • Ingesting data into a cloud warehouse isn’t easy as it requires writing ETL code, which is time consuming and involves using expensive resources. 
  • Changing to a different cloud data warehouse provider is harder as it involves technical challenges and contractual issues.  
  • Within cloud data warehouse takes a lot of time to store and retrieve data, therefore data latency is rather challenge for cloud service providers.  

As reported by Forrester Ware: Cloud data warehouse, Most organizations are deploying cloud services and their usage is on the rise, as it helps them 70% to 80% in savings. 

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