Data Warehouse modernization is an inevitability. It will happen within your organization, either purposefully by design or organically in reaction to business needs.
The modern data warehouse is a modular, extensible architecture that allows for the expansion and adoption of new technologies to meet different information use cases. However, DW modernization is more than just a technology upgrade. The driver behind modernization should be a realignment of technology initiatives with specific, quantifiable business outcomes that are driven by the business’s core vision and strategies.
Modernization efforts should also include assessing your overall information management maturity. Extending the data warehouse will introduce new technologies, require new skillsets, create new integration points, change the flow of information, and challenge existing security and compliance policies. Such monumental investments can only be rationalized by aligning changes to specific business outcomes, allowing the organization to quantify the value and gain support through a unified strategy.
Here are a few practical tips for aligning data warehouse modernization with business outcomes in a unified organizational strategy:
Technology companies push warehouse modernization purely from a product/platform standpoint. While new, modern technology is ultimately needed to meet the speed, agility and scalability demands of the data-driven business, it’s important that modernization efforts start with a focus on understanding the business vision, priorities, and drivers that must be supported by the modern data warehouse. To determine your specific DW modernization roadmap, begin with a look at the business vision and the uses of data that the business intends to employ to achieve the vision. Only then can you begin to truly understand the functionality and associated capabilities that must be delivered from your technology investments.
By aligning your DW modernization efforts with specific business outcomes, you can then measure the value of your modernization effort. Modernization will also be recognized as a driver of business success rather than another IT cost center.
When creating your data warehouse modernization roadmap, develop a reference architecture that takes a modular approach to delivering capabilities to the business. Each component of your reference architecture should identify the capabilities and use cases satisfied by that component. This will allow you to focus on identifying the sequence of implementation by selecting the highest need/value business capabilities and prioritizing that component of the reference architecture first. This approach allows you to continue to architect your ideal modern data warehouse upfront but take a practical approach to implementation that carries demonstrable business value.
When modernizing your data warehouse, don’t forget to do some housekeeping on your information management processes. An effective data governance program will help you get the most value out of your modernization efforts.
Revisit the health and efficacy of your Data Governance (DG) program. The data governance program provides key input into your modernization efforts as data governance will define requirements around data access, security, retention, and metadata management. It will also help define the organizations response to providing access to information that originates outside of the traditional corporate-controlled IT systems which will guide your big data / Data Lake decisions.
Ensure you are collecting, organizing, and sharing metadata. Unnecessary data duplication is a key contributor to out of control growth in data volumes at many organizations. By sharing a catalog of data assets, you can elevate the business awareness of the data that is already available and reduce the unsustainable duplication of data.
How can you modernize your data models if you don’t have a way to collect, categorize, and expose them? How can you plan for data volume growth if you don’t have an information lifecycle management policy?
4. Think bi-modalBe sure that your modernization journey includes the “speed of business” uses cases that get information into the hands of business folks in meaningful ways to reduce the time to insights. The modern DW architecture should accommodate a variety of use cases from highly governed and controlled corporate data to data discovery and exploration use cases that lead to innovation. For many organizations, these “mode 2” use cases can be easily supported through small adaptations to your existing DW investments without requiring a massive overhaul and provide big dividends for a small investment.
Data Warehouse modernization is an exciting opportunity to shed years of accumulated technical debt and deliver new capabilities that empower business stakeholders and forge tighter business and IT partnerships. Take advantage of the opportunity to get people within your organization excited about data management using shiny objects like MPP, virtualization, Big Data, In-Memory and other technologies to empower users with fast access to data they may have never seen before, regardless of where it resides.
As we’ve discussed, modernization isn’t just about updating technology but improving all of your people, processes, and data along with tech advancements. Upgrade IT skillsets along with your technology to stay current with the industry and raise employee engagement within IT. Read tips for upgrading your processes along with modernization in this blog.
Data warehouse modernization isn’t your typical platform upgrade. It must be communicated effectively internally and collaborated on wholly by multiple business units which historically have not played a role in data management. The road to modernization can be long but on the other side lies a land full of opportunities to exploit the value of data in new and creative ways that can transform your culture, your business and your ability to compete in the digital marketplace.
