Seamless Migration Journey to Cloud Data Warehouses with Cubet's Expertise

  • Vishnu K BVishnu K B
  • Cloud Application
  • 3 months ago
Seamless Migration Journey to Cloud Data Warehouses with Cubet's Expertise

Did you know that the world creates and uses 328.77 million terabytes of data daily? Recent developments in cloud technology make managing this vast amount of data possible and more accessible.

However, the question arises: how does a company manage so many TBs of data daily?

One solution to this problem is cloud data warehousing. This is not only efficient but also cost-effective.

 

What is a Cloud Data Warehouse? 

Cloud data warehouses are platforms developed for enterprises designed explicitly for query and analysis rather than transaction processing. This is why they are used to analyze and report semi-structured structured data. 

Data warehouses typically store historical data and are often optimized for reporting and analysis. The data used for this purpose is collected from multiple sources and integrated into a unified format in the data warehouse. This integration process often involves cleaning, transforming, and restructuring the data to ensure consistency and quality.

All data stored in the cloud is backed up automatically, providing 99.99 percent data availability. This is mainly why so many MNCs worldwide prefer data warehousing.

That’s why creating a data warehouse is extremely important for your business in this age.

 

Importance Of Cloud-Based Data Management 

Given the availability aspect of data because of a data warehouse, it has become increasingly imminent for businesses to have one for their company. But why else should they have it? Let’s understand this better:

Scalability: Cloud platforms offer elastic resources that can quickly adjust to changing data volumes and processing requirements. This scalability ensures that organizations can handle fluctuations in demand, further supporting business growth. It can also help adapt to evolving needs without physical infrastructure constraints.

Cost-effectiveness: By eliminating investments in hardware and infrastructure maintenance on storage servers, data management using cloud warehouses can help the company optimize costs. 

Accessibility and flexibility: Anything stored on the cloud can be accessed from anywhere in the world. This flexibility fosters collaboration among remote work teams. Additionally, it allows companies to integrate a wide range of data management services and tools into their workflows, and these systems can also be customized to their specific business requirements.

Reliability and resilience: The systems also have a robust infrastructure with built-in redundancy and failover mechanisms. Such resilience ensures that data is highly available and durable. This reliability reduces the risk of data loss and downtime, which can give the company peace of mind and for continuous operations.

Security: Cloud providers invest heavily in security measures to protect data from unauthorized access, breaches, and loss. They invest in developing tools like advanced encryption and access controls that meet compliance certifications to ensure data confidentiality. This can easily surpass the security capabilities of on-premises storage facilities.

 

The Need For Scalable, Performance, Security, And Integration Features

In short, the need for scalability, security, integration, and performance features in a data warehouse empowers organizations to manage and leverage their data assets effectively. This helps them drive business growth by reducing costs and increasing innovation, giving them a competitive advantage.

But let’s understand this in detail. Let's look at how Amazon's AWS (Amazon Web Services) does it.

Amazon Web Services (AWS) offers a wide range of services, including computing power, storage, databases, analytics, machine learning, and more. AWS serves millions of customers globally, from startups to large enterprises across various industries, which is why it handles a massive array of data on its servers. 

To manage this, AWS provides elastic resources that allow users to scale their infrastructure up or down based on demand.  For example, during major retail events like Black Friday, AWS allows its customers, who are e-commerce companies, to scale storage resources to handle the surge in website traffic and transactions uninterruptedly.

Since it also handles companies that ask for bank details and other important information, it also has a robust security system. Given the sensitivity of customer data stored on their cloud, AWS has:

  • encryption, network firewalls, and identity and access management (IAM) controls 
  • Complies with industry standards and certifications such as ISO 27001 and SOC 2

In addition to these features, AWS's use of SSD-backed Elastic Block Store (EBS) volumes ensures low latency storage, improving communication between different regions and availability zones.

 

Data Management Challenges

Data management can be a daunting task if it's not done correctly. Some of the challenges are:

  • Managing large volumes makes it extremely difficult to store them. Plus, the data increases with time. Handling such scaling data volumes efficiently is crucial for maintaining performance and scalability.
  • Large amounts of data come in various formats, including structured, semi-structured, and unstructured. This requires complex data management solutions.
  • While running a business like e-commerce, real-time data processing and analytics require systems capable of handling high data velocity. To derive timely insights and support decision-making, high support from good cloud solutions is needed

If managed internally, such challenges can cause a lot of trouble. One of our clients, a renowned sports facility that aims to revolutionize the athletic experience, also faced similar challenges.

 

Here’s How Cubet Helped?

Migrating to the cloud can be complex and time-consuming. With its data management expertise, Cubet Techno Labs can help streamline this process, ensuring a smooth transition with minimal disruption. Here's how:

  1. We begin by thoroughly assessing your existing data warehouse environment. This includes understanding the data sources, structures, current transformation processes, etc., among other factors. Based on the assessment, they will develop a comprehensive migration plan outlining the tools, techniques, and timeline for the migration. This plan should prioritize minimizing downtime and ensuring data integrity throughout the process.
  2. Our data management specialists can handle the ETL process efficiently. This involves extracting data from your existing warehouse and transforming it to fit the new schema of the target warehouse.
  3. A successful migration doesn't end with the data transfer. Cubet provides ongoing support to ensure the new data warehouse functions optimally. This might include performance monitoring, data quality checks, and addressing post-migration issues.

 

Benefits of Cloud Data Warehouses

  1. Cloud-based data warehouses effortlessly scale to accommodate growing data volumes and fluctuations in demand. 
  2. Leveraging machine learning and AI enables predictive analytics and actionable insights, driving innovation and informed decision-making.
  3. Cloud providers guarantee high uptime and reliability, surpassing traditional on-premises systems. This helps in ensuring continuous access to critical data and analytics capabilities.
  4. Cloud providers fully manage data warehousing. This helps you to focus entirely on other activities.
  5. Cloud data warehouses support real-time analytics, which can help you work and improve data analysis. Let's understand this in detail.

 

How Data Warehouse Improves Data Analytics?

Let's consider a retail company that operates both online and brick-and-mortar stores. The company collects data from various sources, including sales transactions, website interactions, social media engagement, and customer feedback.

Before implementing a data warehouse, the company faced several challenges:

  • Data was stored in multiple siloed systems, making it difficult to consolidate and analyze.
  • Reporting and analysis took time and often involved manual data extraction and manipulation.
  • Data quality had issues, such as inconsistencies and duplicates, hindering accurate analysis and decision-making.
  • Limited scalability and performance of on-premises systems

By implementing a cloud data warehouse, the retail company could address these challenges and improve its data analytics capabilities by:

  • Integrating and storing data from various sources, providing a single source of truth for business analytics.
  • With the scalability of the cloud data warehouse, the company could handle large volumes of data in surge periods as well. 
  • It could now perform complex analytics tasks.
  • It was able to ingest and analyze real-time data, allowing the company to monitor sales trends, inventory levels, and customer sentiment in real time. 
  • Lastly, it could make data-driven pricing, promotions, and inventory management decisions.

Thus, the company has improved the accuracy and efficiency of resources used in the entire decision-making process.

 

Steps To Shift To Cloud-Based Servers (Cloud Migration)

After thoroughly understanding the advantages of cloud-based servers, you must now be thinking about how to shift to data warehousing. For the same, we have outlined the step-by-step process so you can understand it better. You can even use this as a checklist when you start with cloud migration.

  1. Define your cloud migration objectives: Before diving in, articulate clear goals for your migration strategy and identify key performance indicators (KPIs) to measure success.
  2. Establish your budget: When setting your budget, factor in the costs associated with the migration process to ensure financial alignment with your cloud objectives.
  3. Select your cloud destination(s): When choosing the partner from whom you want to use cloud storage, consider pricing, security features, scalability options, expansion opportunities, etc. You can also make things easier by determining whether a public, hybrid, or private cloud option best suits your needs.
  4. Reconfigure your applications: Assess whether adjustments to your on-premises applications, such as virtualization, containerization, or code refinements, are required to optimize performance in the cloud environment.
  5. Explore migration tools: To streamline the migration process, consider leveraging native cloud provider offerings or third-party tools, such as AWS Migration Hub or Azure Migrate.
  6. Choose a transfer method: Evaluate transfer methods, including public Internet, private networks, or physical transfers, weighing factors such as downtime, speed, security, and cost.
  7. Develop a migration plan: Create a detailed project plan outlining the sequence and timeline for transferring data, ensuring alignment with strategic objectives and customer communication regarding potential service disruptions.
  8. Pilot a small migration: Begin with a small-scale migration of non-critical data or applications to test the process and address any issues before proceeding to broader migration efforts.
  9. Execute full-scale migration: Once testing is successful, migrate all on-premises applications to the cloud, verify data transfer integrity, and enjoy the benefits of your new cloud solution.

 

Choosing the Right Partner for Cloud Migration

Selecting the right partner for your cloud migration ensures a smooth and successful transition. Cubet, with years of experience and expertise in cloud technologies, might be the right partner for you. 

From initial planning and assessment to execution and ongoing support, our team of experts ensures you receive a seamless transition to the cloud. Partner with Cubet to maximize the benefits of cloud technology for your firm today. 

 

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