Digital transformation has changed. The monolithic, top-down approach to transformation is dead. And it’s leaving thousands of failed projects in its wake.
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More often than not, big-bang data migration amounted to… well, migration: shuffling the same data silos to the cloud.
It’s led to still-disconnected systems (cloud-hosted as they may be), missed opportunities, culture-tech mismatch, and essentially, people doing the same old thing.
It’s no wonder all-at-once transformation has such a high failure rate. (Somewhere between 70% and 95%, depending on who you ask).
Projects run over budget, under expectations and often leave people wondering what was so special about the cloud in the first place.
Curious as to why most cloud
transformations fail?
One based on data meshes, event-driven architecture, and microservices. And it’s changing how companies change.
It’s now understood that data sitting in the cloud has no inherent value.
The real value emerges when data is put to work—when it’s fulfilling specific tasks like informing decisions, solving problems, or enabling actions.
By focusing on the “jobs” that data needs to perform, organizations can align their data strategy with their business strategy, unlocking practical value almost immediately.
And by applying that one-job-at-a-time practical perspective to the wave of modern data architectures, you get a newly-effective approach to digital transformation that fulfills the promise of the cloud.
A new wave of transformation architecture
Data mesh
An approach to data management that builds decentralized, self-serve data systems. Data mesh enables your teams to access data and act on it. Use it to create a flexible data infrastructure that can help your business keep up with change.
Event-driven architecture
A design pattern where events drive the flow of data and actions within an application or a system. Each component responds to specific events, enabling you to build agile systems that quickly respond to changing business and customer needs.
Microservices
A software architecture pattern that builds applications as independent, modular services instead of a monolith. Microservices enable your business to develop, deploy, and manage applications more freely and can improve operational speed and innovation.
These concepts give companies the tools and frameworks to digitally transform using flexible, scalable, and agile systems.
Data Jobs To Be Done is a modular, practitioner-led approach to digital transformation where data-optimized business outcomes are embedded in every step. It breaks transformation down into key components so you can go faster, deliver more automated solutions, manage change with less risk, and transform your business one project at a time.
It’s…
Pragmatic
Tooling and tech is in service of the work to be done, not the other way round.
Flexible
Built using a modular approach to enable domain-driven data products that are fundamentally scalable.
Future-proof
Leverages future-friendly architecture that means you won’t have to build and rebuild.
Culture-accelerative
Facilitates true cross-departmental collaboration via modular cloud adoption across the organization.
And it’s based on three major data jobs that lead to operational data nirvana.
Data-driven applications
Data visualizations & dashboards
Insights & AI/ML
Architecture on Steroids
It starts with blueprints that enable us to spin up these modern architectures fast.
Now, we know everyone claims “deep expertise”.
But our team has been using architectures like Kafka, Kubernetes, and data meshes long since before they were cool.
That means we can deliver near-turnkey solutions. Before our first meeting, we’re 70% of the way there, then we tailor the rest of the task to the complexities of your business by a deep-dive approach to discovery that aligns with your business goals.
This means:
- Faster turnaround
- Less need for experimentation (as we know our way around these architectures)
- Less risk
It all results in data architecture that aligns with your business strategy, allowing data to be accessible, accurate, and complete.
Use Case
Take, for example, a healthcare platform company that wants to provide real-time data insights to its customers, along with modern systems like EHR and patient portals. With our Data Jobs to be Done framework, you'll get ready-to-implement decisions on managed services vs. self-hosting, cost analysis, and more. We'll help you set up a repeatable, scalable, and secure Cloud Foundation on AWS, Azure, and Google Cloud, with Infrastructure as Code modules, a hub-spoke cloud networking model, and a serverless CI/CD automation process.
01 Data-Driven Applications
One of the great promises of the cloud is being able to automate core business processes.
But you can only automate as much as your data is readily-accessible. And without a strong thread of actionable data, you can’t connect your teams to make cross-departmental automation possible.
This Data Job is all about bringing the right data at the right time to your operational systems, connecting them so you can execute tasks at speed and at scale. It allows for decentralized domain data powered by event-driven architecture.When done right, this makes your data as practically accessible as possible, allowing you to automate business processes and letting your line of business teams unlock the real potential of their data.
This is how we’ve helped companies build seamless, fast self-service tools at scale. It’s how retail grocers have been able to bring their 24-hour delivery window down to a 2-hour window - effectively offering a whole new tier of service to their customers.
02 Data Insights & AI/ML
This Data Job involves architecting multiple layers of data so that you’re able to ask and answer more complex questions than ever before.
This means your teams can find deeply nuanced patterns and derive multifactorial insights from data sources that would have been previously impossible to reconcile — so they can take decisive action instead of relying on best-guesswork.
Having this kind of multi-domain trove of knowledge also allows for more collaborative understanding and action across the business.
03 Data Viz & Dashboards
All dashboards aren’t created equally.
Some are marginally better than a spreadsheet — and others can revolutionize how users consult data in their day-to-day.
The kind of dashboards that enable high-volume data discovery at real-time speeds (and at scale) requires a very specific engine to be whirring under the hood. And building the frameworks that power these dashboards are what this Data Job is all about.
So your team can finally start asking the day-to-day questions they want to ask — the ones that help them do their jobs better.
They can get nearly-instant answers to queries like “How many orders have we processed in the last hour? Or 24 hours? Or last month? Which products have been requested most?” and have that data visualized in actionable, report-friendly formats.
Now what?
It’s clear that the road to becoming a data-powered organization is best walked one step at a time, not bounded in a colossal leap. Data Jobs To Be Done allows companies to transform on demand, in the way that serves their business goals first. Jobs can be done — or not done — in nearly any order (though architectural blueprints are invariably the first step). Curious to see how a modular approach to transformation can grow your business?