You already know using data well can make big impacts on your business. Datateer offers Data Crews–an expert ”data team” permanently assigned to your account. You’ll always get the same Lead Data Engineer and the same Data Product Owner for all your needs.
Rather than hiring, managing, and paying for an internal team, you can scale your business intelligence team up and down as your needs change. We will help plan your data strategy, manage your data roadmap with you, and break down your strategic goals into achievable service requests.
Through the Datateer Portal, you’ll always have visibility and control over your spending, priorities, and velocity. Your Data Crew is a complete set of experts, on-demand as you need them.
Unlock the Power of Your Data with the Right Strategy
Navigating the data landscape can be overwhelming, but not when you have the right companions. Our Data Crews, a data-as-a-service team, offer more than just solutions; they are a scalable, fractional data team that’s permanently assigned to you.
This team, committed to understanding your business, becomes an integral part of your journey. As you chart your course in business intelligence, they’ll bring invaluable insights and proven best practices. You will always move forward with clarity and confidence.
Expert Collaboration: Flexible, Adaptable, and Always Ready
In the ever-evolving landscape of business, your data needs can change and expand. Our data consulting services, embodied by the Data Crew, understand this dynamic nature. As your business intelligence team grows and pivots, the Data Crew, which can be seen as your data platform team, is right there with you, creating and refining Data Assets that reflect the latest developments in your journey.
Whether you have specific queries that require ad hoc analyses or you're aiming to set up self-serve data analytics team structure pipelines, our business intelligence consulting approach ensures solutions that fit like a glove.
Need to scale up? The Data Crew expands effortlessly, just like a flexible data engineering consulting service would.
Need to slow down? Only pay for what you need.
It’s like having an in-house data engineering team, ready to adjust and redefine as you chart new territories. Dive into growth, confident that your Data Crew, essentially your database team, is synced perfectly with every twist and turn.
Understanding the Data Crew (Data Team): A Seamless Business Intelligence Team Experience
When pinpointing your needs, the Data Crew seamlessly transforms them into service requests, followed by a clear quote. This business intelligence consultant approach ensures transparency—you're always informed about costs upfront, eliminating hourly tracking concerns.
The Datateer Client Portal offers you a central hub to manage your requests and monitor progress. Always be in the loop, always in control. What's more, your Data Crew is just a chat away, accessible via tools like Slack and the Portal's live chat feature. This data services team allows you to dictate the pace of work, ensuring flexibility in both speed and budget management. For those with continuous requirements, we even offer discounted Reserved Time.
Bear in mind, data analytics often pull from "upstream" systems—complex entities that, over time, may require adjustments or face obstacles. Rest assured, your data team as a service stands ready, proactively addressing any challenges that emerge.
Staying connected matters to us. Regular touchpoints include detailed status checks, strategy reviews, and specialized workshops.
Elevate Your Business Intelligence Team & Increase Profitability
In today's complex data landscape, a robust data team is crucial. Our Data Crews offer tailored business intelligence consulting services, serving as an integral fractional data team for your business.
This dedicated team, blending the roles of a business intelligence team, data engineering team, and data platform team, ensures you navigate the intricacies of data with clarity and confidence.
Harness the combined power of data consulting services and business intelligence consultant expertise, and stay always updated, flexible, and ready for growth.
"We created 100 different metrics very relevant to our customers. We have seen significant growth in our key accounts."
Paul Harty - Chief Strategy Officer @ Motion Recruitment
"We were data rich but information poor. When you are moving at the speed we are, you can't just throw people at that problem. Datateer gives us a full picture and saves us a ton of time.”
Kelsey Waters - Senior Director of Operations @ Equinix
"Datateer understood our data and consolidated all that information in a way that dramatically improved the speed and quality of client conversations."
Devin Mulhern - Managing Director @ Denver South EDP
FAQ (Frequently Asked Questions)
A data or business intelligence team is responsible for making data valuable to an organization. Although it is often said, “data is an asset,” in reality, data is often raw, inconsistent, and unusable.
A data or business intelligence team is responsible for the end-to-end process of making that raw data into insights, answers, and information.
A data team’s purpose and process can vary across different businesses. Ultimately, businesses want to extract value from data: answering questions, making decisions, and being informed.
Typically, a business intelligence team is responsible for shaping and presenting data to business stakeholders. This often comes in the form of reports and dashboards.
A data team may have broader responsibilities, including:
- Data engineering - organizing the data and optimizing for performance and maintenance
- Analytics engineering - transforming raw data from business systems into metrics and insights
- Business intelligence - writing reports, creating visualizations, and delivering analytics to the end consumers
- Data analysis - deep-diving into data to answer specific questions
Businesses that become data-driven in their decision-making grow at an average of 30%, compared to all businesses at 3% (Forrester). Small businesses can often get by with reporting available from their applications, manual reporting, or no reporting at all.
As businesses grow, they need more timely information and consistent metrics and reporting. You need a data team when you know you have more valuable information hiding in your data, but it is difficult to make use of it. This can manifest in many ways such as:
Reports requiring a specialized process that takes days or weeks
Data from different systems or sources does not reconcile
Your customers or employees do not have access to the data that you know is available
The prevailing best practice to structure a data team is along the following responsibilities:
- A central data engineering team that brings data all into one place
- An analytics team that combines and transforms data from multiple sources into a single, unified, consistent reporting model
- Data analysts embedded in functional departments to further tailor the reporting model to answer department-specific questions
- Business intelligence experts (either centrally or embedded in departments) to create reports, dashboards, scheduled notifications, or other means of getting information to the right audiences
- A central data operations team (sometimes called “DataOps”) to provide support, monitor technical health, and manage data quality
The success of data teams is notoriously hard to measure because typically they enable other initiatives or departments to succeed. And they are typically cross-cutting, meaning they serve many different areas of the business.
One approach is to identify strategic initiatives made possible by the efforts of the data team and to attribute a portion of that success to the data team.
For example, a company that launches a new data product to its customers may measure success by looking at new revenue or new leads generated. This product required efforts from several areas of the business, including the data team.
A project-by-project approach can be appropriate for internal initiatives. For example, the marketing team may be able to optimize ad spend if metrics are clear and available to ad buyers. The data team that provides these data assets could be attributed for positive effects such as reducing ad spend, increasing ad effectiveness, or reducing customer acquisition costs.
Imagine you are building a LEGO city:
The data engineer is like the person who gathers and organizes all the pieces, ensuring they are available to the builders.
The data analyst is like the person who determines what buildings, parks, and roads need to be built and creates them.
Another way to look at it is that a data engineer is like a librarian, gathering and organizing books. The data analyst pulls only the books needed for a specific research project and performs the research.