Thought Leadership

Many data modernization projects fail, but yours doesn’t have to

Nick Amabile


April 8, 2020
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So, you’ve decided to migrate your company’s data to AWS, Google Cloud Platform, Azure, or another leading cloud-based provider. Congrats!

That’s a fantastic decision with the potential to transform how your teams organize, store, retrieve, and analyze the information your business needs to scale new heights. 

But now there are a ton of factors to consider. What sort of timeframe will this data modernization project require? What resources, expertise, and people power will you need to expend? How much will the migration disrupt day-to-day operations? What are the best practices for continued reporting throughout the process? And ultimately: Is there any guarantee your project will be successful?

There’s no single answer to any of these questions except the last one—and that’s a hard no. The unfortunate reality is many data modernization projects fail, and for a wide range of reasons. Having led countless cloud migration projects, we know there’s a vast landscape between day one—when a company purchases the shiny new software or solution—to the end-game of successfully gleaning actionable, data-driven insights that will grow their business.

Between those two tent poles are a million uncertainties and opportunities for miscommunication between your business and IT teams. 

But there’s light at the end of the tunnel. With the right tools and guidance, you can ensure a successful data migration. You can overhaul your technological framework to improve data warehousing and analytics for huge results. We’ll get into the planning process, but first, let’s talk about the reasons so many projects fail outright at worst, or at best never reach their maximum potential.

Don’t let bad (or nonexistent) guidance derail your migration project

It’s a pretty obvious fact: Embarking on a modernization project without a solid plan in place is a recipe for failure. And it makes a lot of sense. Even if leadership has a fairly solid understanding of their data infrastructure, there are a thousand x-factors and what-ifs. Many times, these are simply outside the scope of understanding for anyone who hasn’t been intimately and repeatedly involved with the process of cloud migration. 

Further complicating matters, many companies in our industry bill themselves as consultants, but are in reality little more than glorified IT services firms. That’s why it’s important to be judicious and consider your range of options carefully before choosing a data partner. Ultimately, you want an expert like DAS42 whose consultants emphasize data analytics strategy and can show proven experience bringing complete, unique solutions to each project. At all costs, avoid being led down the wrong path by any so-called consultant who…

Fails to take the full data stack into consideration. Our experience has taught us that if a customer is looking at one piece of their data stack, the other pieces are probably candidates for improvement—or at least consideration. After all, business intelligence and data warehousing components only work optimally if both are firing on all cylinders. If you’re planning to go from an on-premises data platform to a cloud-based one, we believe there are a minimum of four or five different data technologies you will need in place. Whether you’re migrating to Looker, Snowflake, and Google Cloud Platform—or some other combination of technologies—it’s vital to keep the bigger picture in mind as you gear up for migration.

Is too platform agnostic. There are literally hundreds of tools in the marketplace to consider at each layer of the data stack. The last thing you need is a partner telling you, “They all have their pros and cons.” You already know that. What will be infinitely more helpful in your migration planning is a consultant with years of experience who can offer strong opinions about which tools and solutions will work best for your company’s specific challenges and goals.

Claims to be the end-all-be-all. While it’s true that authoritative advice based on expertise is essential in the planning process, it’s equally important for a data consultant to recognize and admit when they’re out of their depth. In general, a great data consulting partner would never claim to be familiar with dozens or hundreds of different technologies. They should claim to be expert advocates for only a handful of solutions. These are the ones they know will help their clients reach the next level of data analytics. 

To achieve great data outcomes, first evaluate your strategy

We’ve established that in order to be successful in your analytics modernization project, you need the right consultant with lots of experience in evaluation and planning. But what does that look like? And how should it influence your interactions throughout the migration process?  

It’s first and foremost about bridging the all-too-common gaps between business and technology. Unlike basic IT services firms, DAS42 starts each consulting engagement by connecting with both sides of the business on a practical level. We first take inventory of the vital, data-related questions you need to be asking of your business (i.e., data and KPIs), as well as the potential value that data could help you unlock. 

Our experts employ checklists, Q&A sessions, and past/potential scenario walk-throughs to evaluate the state of your current data strategy. This process is often marked by questions like:  

What are your sales team’s data-related goals? What about the marketing team’s? 

  • How comfortable are those teams in asking for what they need? Do they know the right questions to ask?
  • What barriers to success have business teams encountered in absence of the right data and KPIs?
  • How equipped are your IT experts to identify high-value use cases? Can they break down knowledge and communication barriers across the business? 

From there, we recommend working backward with your consultant to forge a migration strategy that addresses those challenges—both immediately and in the long term. The overarching goal should be building flexibility into the process, which requires understanding that there will be trade-offs. For example, your consultant can’t guarantee that all of your reports are going to run faster in the cloud, or that they can magically fix all your performance issues. But at the end of the day, they can work toward optimization by creating flexibility between business and IT users. 

It’s a whole different scene in the cloud

There are a number of ways to migrate analytics. So-called “lift and shift”—taking legacy strategies and applying them to the cloud—is one of the most commonly used approaches. But it’s important to remember that you’re upgrading for reasons that include cost savings, increasing flexibility, and decreasing time to value in gleaning insights from your data. Old, on-premises legacy systems are no match for the cloud. As a result, success on the new cutting edge will require updated processes and approaches. 

Furthermore, investing a lot of money to simply shift your current data to the cloud won’t produce the transformative results you or your team members are hoping for. That’s why it’s important to begin any modernization project by asking deep, probing questions about what types of data you need and what you hope to achieve once you have it. From that crucial starting place, you can build a comprehensive strategy with features that include:

  • Analyzing your cloud-migration portfolio
  • Designing a roadmap with clear milestones and opportunities to measure progress
  • Migrating, integrating, and validating your data
  • Continually optimizing user adoption and system performance over time

By internalizing this mindset shift, you can scale a successful migration project that leverages all the strengths and capabilities of the cloud, for both immediate and long-term benefits for your business.