Is Datateer a Product or Consulting Company?
One of the main reasons we started Datateer is to get you out of this either-or question.
Product companies give you consistency and continual improvement of their platform. But they have an incentive to minimize support costs, which means customers end up with a one-size-fits-all product.
Consulting companies can produce something exactly fit for your needs. But it will be a one-off solution that you must support, and consultants have an incentive to maximize billable hours.
What if we could maximize the consistency and continual improvement of a product and bring the customization you need? This is Datateer’s operating model. 75% of your data platform’s features can be automated into product features. Datateer automates, supports, and continually improves these features. The other 25% of your needs are specific to your business. We help you grow your data capability over time, as your needs require and resources allow.
Every company has more data than they ever had before. Our customers have a vision for what they could do with their data, if they could get a good handle on it. This is the journey that we go on with our customers. Together we scope and phase a crawl-walk-run approach based on available budget, timing, and ROI expectations.
After the initial onboarding, we flip between Project Mode and Operational Mode.
Project Mode is often a capital expenditure, where we implement major enhancements like new data providers or new forms of analytics.
Operational Mode is lower cost, billed as a single, bundled, predictable subscription fee that includes the Datateer platform license, managed services fees, and any vendor license costs.
Sometimes customers have staff or specialists they want to plug into our process. We welcome and encourage this kind of collaboration!
- Identify audience(s)
- Select delivery method(s)
- Articulate questions that need answered
- Define metrics
- Define dimensions
- Inventory data providers and sources
- Analyze source data
- Get data flowing from providers to data lake
- Create the analytical data model
- Implement metrics
- Design the delivery methods: dashboards, emails, reports, visualizations, etc.
- Create the analytical data model
- Implement the delivery methods
- Service desk requests
- Monthly security audit
- Monthly Business Review
- Minor enhancements
- Hosting and monitoring
- Monitoring and break-fix
- Platform enhancement rollouts
One thing we have learned from years spent evaluating tools, technologies, and techniques–there is no shortage of options to create a cloud-based data management platform. In fact, the challenge is in the end-to-end solution, tying everything together with the right specialized tools and processes.
It’s not like you need anything magical to create a solution like this–it’s just that there is a LOT to do! Kimball identified 34 subsystems in the ETL process alone. This is a complex specialty.
We simplify and standardize and automate as much as possible, continually upgrade our practices and architecture, and roll all that into features of the platform–so that you and we can focus on your business and your unique data.
- Scalable data lake and data warehouse
- Full data isolation and security
- Automated data quality control
- Scheduled and on-demand data pipelines
- Proactive issue monitoring and resolution
- Always-on service desk and SLAs
- Private slack channel
- Auto-generated data dictionary
- GDPR compliance
- Infrastructure automation
- Regular security audits
- Data pipeline automation
- Notifications and logging
- Auto-generated data lineage
- Missing data checks
- Cost monitoring & minimization