Data Stack Implementation

Expert guidance increases implementation success.

Staff augmentation is a vetted staffing service where our experts join your team for longer and larger initiatives.

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An Implementation Framework That Works

Power BI is an incredible tool, but it’s just the tip of the iceberg. To fully leverage enterprise data, every piece in your data stack must work and communicate seamlessly.

Collectiv has the technical knowledge of how these tools snap together so they actually solve your business problems. Whether you’ve already identified a need or you’re trying to pinpoint the problem, we implement a custom solution to increase efficiency and impact.

The Collectiv Approach to Data Stack Implementation

Most Power BI and data stack implementations fail due to a lack of expertise, experience, leadership, and technical skills. Collectiv understands how to build the right enterprise solution.

Assess

We learn about your goals and obstacles, then we conduct research to understand the specifics of the technologies and issues unique to your enterprise. If something hasn’t been built before, we’ll figure out a solution faster than anyone else.

Iterate

Tight iteration loops are the hallmark of high-quality, low-waste consulting because they allow us to refine the solution throughout the process. Using frequent and efficient development cycles, we collaborate with your team and continually validate the solution.

Handoff

Support

Some consulting firms take your request, go into a black box, and deliver something that doesn’t meet your expectations a few weeks or months later…that’s time and money lost. That is the opposite of what we do at Collectiv.

We work closely with our clients in tight iterative cycles. After understanding your organization’s challenges, we design an implementation plan and build a report structure that scales with your enterprise. While we conduct independent research and development, we check in with you daily or every other day to ensure that we’re on track.

Working with us on larger-scale projects is the most cost-effective way to leverage our breadth and depth of business, technical, and consulting expertise. Implementation success requires seamless execution of many technical details, including IT infrastructure, data architecture, integration, and cloud storage—we have the knowledge and experience to cover all the bases.

Our typical engagement starts at $15k because smaller-scale, piecemeal projects won’t be the best use of our clients’ budgets.

It depends on your data and reporting needs and where you are in your BI journey.

If you have a specific requirement, such as building a visualization from current data sources, we’ll get in and get it done. If you need help defining the problem, we work with your team to figure that out and then craft the best solution.

Oftentimes, Collectiv’s recommended solution involves Power BI but may also include the Microsoft Power Platform, data infrastructure, and/or a data warehouse.

No matter your challenges, we’ll dig deep and assess your needs to identify applications we can combine to build the most efficient solution. Then we’ll roll up our sleeves and build it—working closely with you to ensure that it meets your requirements and refine it over time to scale with your enterprise.

Our experts combine strong business acumen with industry-leading technical expertise across the entire Microsoft data stack, including Azure. Our experienced consultants have led Power BI implementations across a wide range of industries and use cases for analytics, planning, and predictive.

While there are plenty of Power BI developers out in the wild, what makes us different is that we are consultants. We listen, ask the right questions, and develop a deep understanding of your business needs to deliver high-quality outcomes.

Implementation FAQs

Implementing a data stack is a substantial undertaking. Here are some FAQs to help you understand the process. If you have additional questions or you’re ready to move forward, reach out to the Collectiv team.