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The Key Factors Driving Data Warehousing Modernization

The Key Factors Driving Data Warehousing Modernization
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by Sanjeev Kapoor 09 Jun 2022

If you have been following the IT field and developments, especially on infrastructure management and server processes, you no doubt have heard about data warehousing. Simply put, Data Warehousing is the process of storing large volumes of data across the enterprise. In recent years, Data warehousing modernization has made it possible for companies to store their information and analyze it in-house instead of just purchasing services from cloud service providers. This modernization is driven by recent advances in data warehousing technology.

In the last two decades, Data Warehousing (DW) has grown substantially to become a unique component of the modern enterprise architecture. It builds on the concept of ETL (extract-transform-load) that combines data from multiple sources into a centralized repository for analysis and reporting. As enterprises have evolved to embrace new business models, thrive in the digital economy, and establish greater organizational agility, data warehousing has grown in importance to support multidimensional decision-making across the enterprise.

Data warehousing is changing rapidly, with the advent of big data, cloud computing and business intelligence (bi). For example, many companies have opted not to build their own warehouse management system and have switched to using cloud-based systems to store all their data. However, there are still some organizations who prefer to manage their data on-premises rather than in the cloud. Moreover, big data are changing the future of data warehousing, while novel bi tools enable more sophisticated processing of very large amounts of structured, unstructured and semi-structured data. Also, with the advent of modern data warehousing techniques and advanced analytics that serve as a perfect blend of historical and real-time information, enterprises gain timely support in their decision making. Overall, new age data warehousing is being driven by the new era of digital technologies, which enable the development and deployment of advanced data mining and data analytics functionalities.

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Data Warehouse Modernization Technologies

With the ever-increasing compute and storage needs of today’s organizations, the challenge faced by businesses is the spiraling cost of managing data storage. Hence, the modern data warehouse must be equipped with scalable and high-performance tools that make it easy to store, analyze and visualize data. Scalability, performance, and quality of service in modern data warehouses is mainly driven by the following cutting edge digital technologies:

  • Cloud Computing: Cloud based data warehouses are scalable and cost-effective infrastructures which ultimately provide increased agility compared to on-premise solutions. Using data warehouses in a multi-cloud environment enables organizations to modernize their data architecture and to provide a better user experience to users of data driven applications and services.
  • Big Data Analytics: Modern data warehouses come with powerful tools for analyzing data. This allows for the extraction of unique insights and hidden patterns of business intelligence. The ability to extract specific and valuable insights from historical data is a major factor contributing to the demand for modern data warehouse solutions. In many cases big data solutions are powered by advanced machine learning and artificial intelligence techniques, which boost automation and facilitate the extraction of non-obvious insights and correlations.
  • Business Intelligence Dashboards and Reporting Tools: Modern data warehousing is a permanent and multi-faceted structure consisting of many subsystems such as relational databases, and ETLs for transforming data. State of the art data warehouses come with advanced reporting tools, including ergonomic and user-friendly dashboards. The latter facilitate users in understanding analytics and how to operationalize them in specific business processes. Moreover, they enable them to implement no code functionalities, which obviates the need for programming novel bi solutions.

As data warehouses revolutionize business intelligence and analytics, new trends are emerging by virtue of the latest advancements in data warehousing. Modern data warehouses have ergonomic and easy to use business intelligence tools, offer real-time analytics functionalities, and can be deployed within clouds to benefit from the capacity, scalability, and quality of service of cloud computing.


Data Warehousing Benefits

Modern enterprises invest in data warehousing infrastructure to enhance their ability to manage large amounts of data from diverse sources. With a state-of-the-art data warehousing infrastructure in place, companies can enjoy the following benefits:

  • Flexibility of Choice: Enterprises now have more choices than ever when it comes to how they build, manage, and use their data warehouses. For many enterprises, the traditional single-vendor-provider for data warehouse services is no longer the only option available. Today’s business landscape has fostered a growing number of alternative-providers who are building their own technology stacks that incorporate the flexibility and scalability required to meet today’s most pressing business challenges. Hence, the adoption of modern cloud-based data warehousing services provides enterprises with many different options about how to best manage their data.
  • User Experience: Modern data warehouse solutions emphasize on user experience. They come with user friendly interfaces, which leverage popular user-facing functionalities such as multi-touch objects, drag-and-drop operations, and multi-dimensional visualizations.
  • Reliable Multi-Channel Data Management: With data flowing in from various channels, a reliable data warehouse is more important than ever. Now that people generate huge amounts of data every day, it has become much more essential to collect and analyze it. The goals of a business are met with modern data warehouses. The latter have their own central systems providing them with uninterrupted backup; this also makes them easier to use since there is always access to data and no loss of information can occur.
  • Advanced Analytics: Modern data warehouse infrastructures consolidate information from a wide variety of data sources, including structured and unstructured sources, data in motion and data at rest. Moreover, they offer analytical tools over these data sources despite their diversity. This leads to unique knowledge extraction and advanced analytics functionalities, which broaden the spectrum of insights that can be provided to enterprise decision makers.


In recent years many organizations understand the value of data warehouses in terms of offering a centralized location for managing project data and operations. Nevertheless, many companies struggle with how to best leverage their resources to meet the demands of ever-changing environments. It is not uncommon for many businesses to feel overwhelmed by the idea of implementing data warehousing due to its perceived complexity, especially when it involves merging disparate sources and putting the new information into a warehouse structure. Therefore, CIO (Chief Information Officers) must strive to raise awareness about the complexity and the multi-facet benefits of modern data warehouse software solutions.

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