A Data Services Company
- Construction
- Infrastructure
- Equipment
- Facilities
Data Engineers
Building software to capture, transfer and clean data.
Analytic Engineers
Identify and design solutions to business problems using data.
Data Scientists
Create machine learning algorithms to predict or recommend.
A Different Approach to Data Projects
Data, AI and automation tools are developing so quickly that it is more important for data service companies to understand a client's business than it is for them to be an expert in a specific technology or system.
Past: Domain Generalists, Technology Experts.
Traditionally, data projects are scoped and delivered all at once. This is because technical experts on a specific technology implement that solution or analysis while learning your business. This works well for clearly scoped projects that are large and encompass many business units. This approach does not work well for data and knowledge projects.
Future: Domain Experts, Technology Generalists.
In the future, data products will constantly evolve. Knowing a technology won't be good enough to apply across industries. The use of AI and automation tools makes business understanding imperative for technical developers to be able apply different technologies precisely. Having a domain focused data partner will be critical to success in the data and knowledge projects of the future.
When We Can Help
Our goal is to be a service provider that explains data enabled processes and outcomes simply. We want to help you envision ways of using data better to enhance your business. Below are some common situations where we can help.
Data to insights is a frustrating process because of the prep work in pulling all the data you need from various internal and external sources. Even if the data is in one system, it is often not organized in a way that allows for easy analysis or is missing the reports you need.
We are experts in creating data models and designing data automation pipelines that are connected to a business activities and metrics. We believe choosing the tool and software for storing and analyzing data is important, but not the ultimate success factor. The difference between success and failure of a data warehouse project is ensuring the implementation strategy is driven by business outcomes, not technical best practices (vendors have very good docs for that).
There are many great products and solutions, but often they are only partially what you need or have way more functionality than you need and are prohibitively expensive. A common solution is to bring in an outside resource to conduct an analysis in Excel and deliver their findings. This is fine, but it's a one time answer to a question at a point in time given the data available at that time.
For similar cost, we want you to have a repeatable process you can provide new data to, adjust the parameters and get new findings. The best part is, we'll host it so you just log in, provide it with a refreshed data set and re-run it whenever you want. All in a few seconds.
We get it, its hard to understand what a product actually does behind all the marketing promises of wizardry and wish fulfillment. We get lost too.
Why is it so confusing? Nearly all products on the market are built for flexibility. They want everyone to use their products, but that means they have a hard time telling you exactly what they do.
We are experts at understanding AI and automation use cases. We will help you understand what data you need to ensure a product will deliver on all that wizardry. We will also look at your use cases identify how products can be applied to your business.
It is more critical than ever to ensure data flows properly throughout your business. Data is the fuel that runs the AI and automation engines. System implementation partners must ensure the system's data strategy will properly fuel those engines of the future.
Often times, technology projects are led by business analysts who are not technical, but lead a technical team. This is a hard job and often leads to a lot of frustration with outcomes. Why? If people implementing the solution don't understand the underlying business, there will be many small, but important decisions made by development teams that will not cause the product to fail, but will steer the project in a direction that doesn't meet your future needs.
We are technical implementers, but are experts at thinking through why systems are needed. We will either work with another implementation team or implement ourselves by assembling the right team to deliver the solution. We can serve as a general contractor for data projects. We may not do all the work, but we'll ensure any system you implement is developed so the data artifacts will enable your future efforts and business to be AI ready.
I started CN Dataworks because data projects are too often delivered like software projects. The approach of bringing in experts in a technology, having a couple full day workshops on how a business works and implementing configurations doesn't work when implementing data and knowledge solutions.
Algorithmic decision making and other flavors of AI will shape how businesses operate in the future. This change necessitates a different approach to partnerships between data service providers and clients. Service providers need to understand businesses, not specific technologies. With the proliferation of cloud and open source technology the power of corporations with large data teams is available to all businesses, but must be applied precisely. That precision comes from a deep domain understanding.
Developments in the data technology and AI space will not slow down and businesses that apply these tools with precision to their business will quickly recognize value. If your business is in the infrastructure, construction, equipment or facility domains, we'd love to help you in that journey.