Time To Call Your Data Doctor

Getting To The Bottom Of It: Are You Solving The Underlying Problem Or Just Treating The Symptoms?

Chances are at least one person reading this is guilty of having run their symptoms through WebMD (or perhaps nowadays, Chat GPT) when experiencing a new ache or struggling with a particularly bothersome cold. The trouble with symptoms is they can be tricky to interpret. Independent or linked, they can point to alarming problems or be indicative of issues hiding in plain sight.

Companies don’t commonly meet up with us and say “I need to rethink and redesign my data platform from scratch”. Instead, they might have specific issues along the lines of “Our Data Warehouse is not working as expected” or “We are having difficulties making all of our data available”

And sometimes a cold… is just a cold. Some issues are exactly what they seem, and both their symptoms and solutions are straight-forward and conclusive. Sometimes this is the correct approach, applying a quick fix to specific issues that must be addressed promptly due to the disruption they cause to important processes.

However, most problems are symptoms or indicators of a deeper issue, not the root cause. Quick fixes, like painkillers for a toothache, may provide temporary relief, but a real cure requires addressing the underlying cause, such as an infection, with specific treatment. Without diagnosing the root problem and implementing a long-term solution, the problem may resurface.

How Discovery Shapes The Outcome

No one knows more about their industry and business than our clients. This is why, during our initial discovery assessment, we pay close attention to our clients’ expertise and strive to gather all the knowledge and details they have to offer. This is what our Discovery process is all about.

As part of our process we gain a thorough understanding of our client’s industry, business model, and strategy before offering our expert advice on their systems, models and technical capabilities. The goal is to be as informed as possible to guide our clients strategically towards a data-driven approach that can drive their product’s success.

We assess the company’s technical maturity using established and proven criteria and data engineering questions to understand their current data infrastructure, architecture, staffing, processes and practices. This approach provides an impartial evaluation of their current state, enabling us to identify where they stand and the gap that needs to be closed in order to reach their desired position.

Often, our assessment uncovers technical debt (the cost of maintaining existing systems and capabilities from past shortcuts or inadequate design). Lack of attention to these issues can result in a significant portion, up to 40%, of a client’s time and resources being wasted as overhead.

As data experts, we’ve learned to ask the right questions like:

• What are our clients' needs and priorities?
• Where is the business going?
• What does their current data infrastructure look like?
• How about their typical data use cases?
• What tools are they using?
• What’s the extension of their data teams’ capabilities??

Evaluating the details not only showcases the gap between the current state and the desired state, allowing for a better roadmap, but also guarantees we are not solving the “wrong issue” or focusing on a temporary fix that doesn’t address underlying issues.

At the end of the process, we deliver a collection of in-depth discovery documents with our findings. This includes exhaustive research into the current state of data management within the organization and a clear roadmap describing our proposed solution to close the gap between the current state of affairs and the desired context. The best part? We tell the client exactly what we need from their side to make the process and the project at hand a success.

We consider the technical criteria that best align with the organization's business objectives. Some of the output documents we tend to include (which may vary depending on the client's needs) are:

• Data Platform recommendations
• Deep Dive on specific strategic resources the client has consulted us about.
• Our proposed Machine Learning & Data Engineering Best Practices
• Exploratory Data Analysis on particular systems
• ADRs (Architectural Decision Records): Our recommendations on specific tools to use.
• Machine Learning Canvas
• Roadmap with a clear set of goals and milestones to achieve the desired result.

Strict About The Outcome. Flexible About The Process.

AI implementations are challenging and commonly failure prone, even when successful they require large amounts of time and money. This is why we recommend consulting with autonomous experts who can proactively propose solutions. We've climbed the AI mountain many times - we know what to look out for, we are experts in planning, organizing, developing and nurturing all the necessary AI and data capabilities for the climb. We free resources for your company and implement cost-friendly solutions so that you can leapfrog your ascent and focus your time and energy on reaching the next growth summit.

As your on-demand data team Mutt Data can help you crystallize your data strategy through the design and implementation of technical capabilities and best practices. We study your company’s business goals to understand what has to change so we can help you accomplish it through a robust technical strategy with a clear roadmap and set of milestones. Talk to one of our sales reps at hi@muttdata.ai or check out our sales booklet and blog.

See It, To Believe It

We’re active on Clutch! Read our reviews here. Or check out our success stories:

• Supply Chain & Delivery: Habitat Logistics
• Fintech: Ank
• Health: Sirum
• E-Commerce: Mercado Libre
• Education: ClassDojo
• Amazon Web Services Published Success Stories: ClassDojo & Ank