Strengthening Your Data Foundation With Cloud Data Warehouse

Organizations are always looking for ways to accelerate insight and speed up decision-making. In its recent survey on data insight, the Enterprise Strategy Group found that only 4% of IT leaders achieve real-time insight and 45% take weeks or longer.

A cloud data warehouse provides the agility that enterprises need to stay ahead of the curve. It allows access to critical data when needed, using it extensively by overcoming the limitations of siloed and redundant on-premises repositories. On-premises data warehouses, on the other hand, need heavy investments in hardware, licensing and specialized talent. They require extensive data analysis and engineering time to gather data from multiple source systems.

The evolving need for digital businesses to embrace a cloud data warehouse

• Scalability and flexibility: Cloud data warehouse platforms offer autoscaling capabilities to manage fluctuating workload volumes. Client organizations can manage frequent spikes and dips in user demand for analytical resources. Cloud data warehouse platforms help organizations focus on managing data rather than worrying about hardware upgrades, server capacity expansions and software upgrades. Clients can also enjoy ongoing feature updates, large-scale infrastructure enhancements and add-on services as and when needed.
• Agility and speed: The computing power of the cloud reduces the time to critical insight from days to minutes. Users can enrich data in the system, generate reports and respond quickly to new business opportunities. Cloud data warehouse vendors can leverage the global networks of hyperscalers to deliver a seamless analytics experience across geographies.
• Data accessibility and collaboration: Global footprint and robust data redundancy capabilities of hyperscalers allow you to replicate your data across regions to make it resistant to failure. A cloud data warehouse can support the business needs of various user personas by helping them to seamlessly access, visualize, query and exchange data through a web-based user interface.
• AI integration and advanced analytics: When integrated with a cloud data warehouse, AI leverages its cognitive computing capabilities to learn from different datasets, identify complex patterns, predict highly accurate outcomes and make actionable recommendations. AI in cloud data warehouses can offer the benefits of predictive analytics to help you make the most of business opportunities. It can predict future trends, alert you about potential risks and provide useful insight.
• Cost efficiency: On-premises data warehouse requires investment, maintenance and enhancements in physical servers, operating systems, CPU power, storage, licensing, energy for servers/data centers and emergency response. When data warehouse is moved to the cloud, these aspects are managed by cloud vendors who offer a pay-as-you-go service model.
• Security and compliance: In the case of traditional data warehouses, IT teams might take days to react to a cybersecurity breach. When moved to the cloud, dedicated cybersecurity teams of cloud vendors, offload a part of your responsibility of safeguarding data by managing patch installations and supporting regulatory compliance along with data sovereignty. Discuss the scope of such responsibilities with your cloud vendor.

Recommended approach for migrating to cloud data warehouse

1. Assess your current data estate: Undertake a thorough assessment of your warehouse architecture and analyze your current data estate based on multiple parameters like data type, source, schema, flow and size. At NTT DATA, we've built Cataloguer and Analyzer that can help you quickly analyze your existing data estate (including traditional monolithic data warehouses). It can also provide an estimate of the time and effort involved in migrating to any modern cloud data warehouse platform.

2. Identify the right cloud data warehouse platform: Evaluate the capabilities of different cloud data warehouse options to find the best fit for your organization’s needs. Assess their features, ability to support various data types (structured and semi-structured), performance benchmarks, costs involved and experiential factors. NTT DATA's 2023 Cloud Data Platform Benchmark & Analysis compares warehouse workload capabilities of leading cloud data platforms like Amazon Redshift, Azure Synapse Analytics, Databricks, Google BigQuery and Snowflake.

3. Determine the data sets to be migrated: Determine the data to be moved, archived or deleted. This will help you to streamline the migration process, avoid moving unnecessary data and optimize the migration costs. The Cataloguer and Analyzer accelerator can identify unused tables and datasets before migration to help you optimize migration costs.

4. Create a migration plan: Engage your business leaders, IT teams and data users by involving them in the planning and decision-making process from day one. Communicate the benefits and business impact of cloud migration to them. Doing this will enable your organization to drive cultural alignment in line with such changes. An accelerator, such as NTT DATA Migrator, can enable cloud migration of your data from a legacy data warehouse with minimal business downtime and impact.

5. Automate: Reduce human efforts by leveraging automation tools in the stages before, during and after migration. Make migration decisions by generating insights into the usage of data by various personas, frequency, storage, transmission and rejection. NTT DATA Validator can make sure the correctness and completeness of your migrated data.

6. Implement data security: Safeguard your data in the cloud by implementing strong data encryption, data access controls and other security measures. Work with your cloud vendor and potential IT solution provider to create a security plan that meets your organization's unique needs.

7. Change Management: A well-thought-out change management strategy for driving enterprise-wide adoption of cloud data warehouses is key for users to embrace this change and maximize return on such investments. Since the cloud platform involves a new consumption layer for users, change management shouldn’t be overlooked from a user satisfaction standpoint. Train your IT and Chief Data Office teams to use the cloud data warehouse and its features. It'll help them efficiently manage the data in the new platform and generate insights without any potential issues.

Real world impact

Cloud data warehouse offers a host of operational and commercial benefits to various industries. It removes data silos by running all workloads on the cloud at scale and securely shares data/applications across partners, suppliers and clients. It can govern your data with flexible policies and provide regulatory compliance while handling sensitive data.

To kickstart your migration journey from an on-premises data warehouse to the cloud, reach out to our Data Architecture & Integration experts.