Modernizing Your Data Warehouse: Key Drivers, Benefits, and Standard Methods

In today’s increasingly digitized world, data warehouse modernization is crucial to driving data-driven business decisions and insights. Organizations can benefit from improved agility, scalability, and cost efficiency with the right modernization strategy. A data modernization strategy helps you create data management and governance practices that optimize intelligence tools while enhancing data privacy and security across all cloud, multi-cloud, and hybrid IT environments.

Modern data architectures, like cloud data warehouses and data lakes, empower employees to leverage analytics for insights more efficiently. With the right data governance strategy and data democratization measures, more people can self-serve curated, trusted data, fostering data-driven business decision-making.

In this blog post, we will explore the key drivers for modernization, standard methods, benefits and challenges of the journey, and how Hexaware can help you effectively achieve your modernization needs.

Key drivers for data warehouse modernization

As with most modern digital enterprises, data warehouse modernization is driven by two primary levers – business and technology. Data warehouse modernization helps organizations become data-first enterprises where data-driven decisions and insights can be effectively monetized. The way they are intertwined can substantially impact the outcome and the ROI.

Business Drivers

• High speed meets high performance: Business expansion is almost impossible unless supported by data aligned with its goals. When it comes to a pure data warehouse, the data often gets outdated, and its ability to support newer business initiatives becomes limited. This is where data warehouse modernization comes into the picture, helping enterprises get the right, updated data for insights that truly matter.
• Collaboration becomes more close-knit and seamless: Multifunctional teams must, in reality, collaborate more efficiently. However, this is not always the case. Technical snags, analytics reporting delays, etc., often hinder seamless collaboration, which is often exacerbated when business and IT teams coexist and work toward misaligned goals. A modern data warehouse bridges this gap, if not eliminates it, by making it easier for IT teams to interact with the data warehouse.
• Serves as a big boost for self-service BI and analytics: Today’s businesses rely on generating up-to-date reports to gain timely and actionable insights to make decisions both large and small. With advanced Business Intelligence (BI) and analytics applications, you can obtain the required information as and when needed. However, it can be rendered useless by a legacy data warehouse.
• Significantly reduces the costs: Typically, capex spends are much lower, thanks to the cloud. Similarly, a well-designed modern data warehouse reduces the cost of BI infrastructure by eradicating the need to purchase multiple data integration tools to eliminate data silos. Modern data warehouses with user-friendly accessibility at their core can make your data function in several ways without requiring additional resources.

Technology Drivers

• Designed for the present and the future: Technology is an excellent enabler and accelerator for pursuing growth and innovation. This requires staying ahead of the curve and making every process efficient and reliable. Consider the current advantages of zero-code ETL tools, self-service BI, and DW automation platforms and the pace of their evolution. These cutting-edge platforms and systems enable you to confidently meet new business requirements at speed and scale.
• Data integration becomes more stringent: As enterprises assimilate data from increasingly diverse sources (including applications like SaaS tools, ERP systems, web applications, cloud databases, social media, etc.), consolidation becomes essential for making sense of it all. In terms of consolidation, data warehouse modernization once again outperforms legacy data warehouses.
• Keeping up with the times necessitates agility and elasticity: Businesses are experimenting with various data modeling approaches for sustained growth. Because there is no one-size-fits-all solution, Cloud computing once again demonstrates its mettle by being able to scale on demand and adapt to changing requirements. With automatic scaling or de-scaling of servers, storage, and network bandwidth to handle large volumes with unparalleled efficiency, data warehouse modernization provides enterprises with an infrastructure that suits the purpose as and when required without integration or optimization issues.

Standard methods of data warehouse modernization

Now that you are aware of the key drivers of data warehouse modernization, let us explore the methods that will help you get there. Does it involve rebuilding everything from scratch? Or is it possible to update your current data warehouse? Well, the answer is that you can do either. Here are three effective methods for modernizing data warehouses:

Method #1: Migrate on-premises systems to the cloud

Moving legacy systems to a cloud-based data warehouse is the first step in modernizing data warehouses. This approach entails re-platforming, i.e., optimizing existing infrastructure for optimal cloud performance. This method has numerous advantages, including the following:

• Pay-as-you-go, only for the storage and computing power utilized
• Higher elasticity with the ability to scale with data growth
• Zero maintenance and support costs
• Easy and quick integration with other cloud-based services and applications

Method #2: Greenfield development

Greenfield development, a significantly more intensive and time-consuming method, entails using tools, platforms, and practices to launch a new data warehouse initiative from scratch. Enterprises can create a data lake, domain, or model to store data through this. This method has advantages that may appeal to numerous businesses.

• Right architecture design becomes simple as you begin from the scratch
• Common and upcoming standards are simpler to implement
• Hyper-customizable to precisely meet the needs of today and tomorrow
• Cloud-based scalability

Method #3: Extending an existing data warehouse

Enterprises may sometimes retain their on-premises legacy systems to ensure compliance and security. These challenges, however, can no longer hinder an enterprise’s digital transformation journey. Extending an existing data warehouse is the best option in situations like these. Legacy sources are integrated with modern tools and cloud platforms to improve the scalability and agility of your data warehouse. This strategy preserves selected old components while modernizing others with new functionalities. The advantages of the extension method are as follows:

• Increased processing power and storage capacity, improving scalability, and lowering hardware upgrade costs.
• Command of a more regulated environment for experimenting, with modern platforms and legacy components coexisting.
• Automation manifests as a modern extension, complete with tools that can help minimize the time, cost, and risk of data warehousing projects while broadening the use cases for advanced analytics.

Benefits of Data warehouse modernization

Data warehouse modernization transforms an inefficient data storage and processing system into a modern, agile architecture. Almost every modern enterprise relying on a robust IT ecosystem would gravitate toward this advantage. Maximizing the use of new or open data sources, deploying Cloud BI, and managing data are the current trends for executives. However, the list of advantages is much longer. In actuality, it consists of numerous elements, including those mentioned previously. Here is a summary of the key drivers of data warehouse modernization:

• It enables users to rapidly access critical data from multiple sources in a single location, thereby saving time and accelerating decision-making for daily operations and future forecasts.
• It provides consistent information on cross-functional activities and supports ad-hoc reporting and queries.
• It facilitates the integration of numerous data sources, thereby reducing the time required for analysis and reporting.
• It enhances data catalogs, data hubs, microservices, and APIs to make data management more accessible and flexible.
• It provides a reliable, multi-channel environment with uninterrupted backup.
• It boosts user experience by providing user-friendly interfaces with simple multi-touch, drag-and-drop functionalities with multi-dimensional visualizations.

The challenges in the journey

Before embarking on the data warehouse modernization journey, it would be prudent to pose a few questions regarding potential scenarios.

• What is the complexity of the current data and analytics ecosystem?
• How can an organization avoid business disruption during migration?
• Even though an automated migration accelerates the transformation, will there be obstacles during migrating complex scripts?
• What is the ideal target cloud platform, and what technologies can add value to the organization?
• How will the organization ensure compliance with geographically specific, stringent data governance and regulatory requirements?
• What would the road map look like, how much savings can the organization anticipate, and when can it expect a return on investment?
• What are the current landscape’s usage patterns, and how can the cloud infrastructure be optimized?
• How can an organization optimize cloud execution by gaining visibility into workload execution patterns?

CIOs would do well to take into account all the scenarios above from both a business continuity and financial standpoint. At Hexaware, we are fully aware of these challenges and how to resolve them comprehensively.

Why modernize your data warehouse with Hexaware?

Are you seeking an ideal technology partner for your data warehouse modernization journey? Do you want to ensure all the challenges that might crop up are well anticipated and planned? Look no further than someone with proven industry expertise! At Hexaware, we empower enterprises to leverage next-gen automation for modernizing data warehouses and analytics ecosystems – thanks to Amaze^® – our proprietary Data & AI platform.

Amaze^® is a purpose-built, complete data management platform for modernizing data from on-premises to a cloud environment that considers every enterprise situation, cloud platform, and migration process. Additionally, it integrates data discovery, quality, transformation, reconciliation, lineage, and security into a single platform, thereby enhancing IT and business team collaboration. Moreover, our cloud engineering team ensures that the entire journey is agile, seamless, and secure, with zero or minimal possible downtime.

To learn more about how Hexaware can accelerate and enhance the results of your data warehouse modernization, visit: https://hexaware.com/services/business-intelligence-and-analytics/amaze-for-data-ai/data-warehouse-modernization/