Forward-Thinking Data Strategies.
Transactional databases used for business applications are designed for day-to-day operations. Attempting to use these systems for reporting and analytics presents numerous challenges, including:
- Strain on source systems: As the demand for information grows, the load on systems grows with it. If a report takes five minutes to run, that puts five minutes of heavy load on the source systems, compromising any other users who are working at the time.
- A lack of historical data: Operational systems are built to handle daily business transactions. They are not intended to store historical data.
- Slow reporting: A transactional system is optimized for write operations, resulting in slow processing for reporting applications.
- Difficulty in creating business intelligence solutions: Modern business intelligence tools like Tableau, Power BI, and Qlik are not designed to read from transactional systems and require additional steps to integrate with the data.
- Confusing user experience: Most transactional systems are not built with user-friendly naming conventions, often resulting in misunderstandings when interacting with data.
- Inaccurate data: As data is entered into the original system, users may enter invalid or contradictory data.
- Inconsistent data: Disparate source systems function in isolation, resulting in conflicting information when combining data from multiple databases.
If any of the above sound familiar, you’re in the right place. At 2nd Watch, our consultants have more than 20 years of experience in architecting data warehousing solutions.
We have built data warehouses for companies across various industries during mergers, acquisitions, and periods of growth.
Based on our extensive industry background, 2nd Watch recommends a data warehouse as the foundation to a successful business intelligence platform.
2nd Watch can create a data warehouse for your organization that provides a fast, accurate, and consistent view of your data. Using best practices and well-established methodologies, 2nd Watch combines information from disparate source systems into a centralized repository, creating a single version of the truth.
The final design contains a user-friendly presentation layer that natively connects with both legacy and modern business intelligence tools. Because a data warehouse is optimized for performance and reporting, business users can easily create self-service reports on current and historical data.
Tool and technology selection for on-premise, hybrid, and cloud-based data warehouse systems.
Data modeling for dimensional and analytical/predictive systems.
Data warehouse modernization.
Deployment and training of end users.
Business-level big data strategy (data hubs/lakes).
Ongoing data warehouse support and maintenance.
Modern Data Platform Quickstart
Data-Driven Business in 6 Weeks
Data-driven decisions require the ability to quickly and reliably analyze all of your data. Building a modern data foundation for business intelligence and predictive analytics will ensure your organization can make better decisions now and in the future.