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Analytics Essentials
The integrity of any structure is only as strong as the foundation it rests on. That is especially true for data architecture in the era of AI. A well-built data foundation enables trusted, timely access to data across the business and is essential for scalable analytics powered by trusted AI.
Designing and building agile, high-performing analytics is the work we love. It’s a balance of business understanding and technical expertise, grounded in a strong data foundation and shaped by our Analytics Essentials. These form the critical first steps in the Senturus project methodology, ensuring your data is ready to support analytics, AI and what comes next.
Senturus project methodology
Applying the Essentials saves time and money
The Analytics Essentials of scoping, planning and defining allow us to align your business priorities with the best architecture to support them. During the process, we often uncover key opportunities – even in those organizations that believe they have fully defined their requirements.
Our goal: deliver a solution that provides the highest ROI with the least total cost of ownership.
- Ensures an architectural foundation to support short- and long-term needs.
- Delivers quick wins and agile development.
- Prioritizes business value and ROI.
- Ensures business requirements are fully identified and met; Avoids re-development and manual workarounds.
- Manages total cost of ownership.
- Delivers a working prototype that facilitates better design for the main project.
- Allows for detailed project planning and scoping.
How it works
Every organization is different. Our Analytics Essentials reflect that. Take advantage of any or all of these modules as they make sense for your organization.
Requirements
Interview key stakeholders to assess how business function and data use intersect. Identify gaps.
Architectural options
Identify architectural alternatives and corresponding pros and cons.
Priority matrix
Prioritize near-term, mid-term and long-term projects.
Data profiling and bus matrix
Develop a high-level matrix of common dimensions that can be used by all business processes.
Minimally viable dashboard
Deliver a viable dashboard with a subset of data to demonstrate technology components and business value.
Findings & recommendations
Itemize gaps (e.g. data quality, technology, accessibility, skillsets, culture, governance) in your current BI environment.
Proposed scope and estimate
Provide a detailed breakdown for all tasks related to the first phase.
Spotlight
Learn how – and why – a structured AI foundation helps leaders move from endless pilots to measurable impact and ROI.
Webinars, blogs, videos & whitepapers