Analytics Engineering bridges the gap between data engineering and data analytics. Our analytics engineers provide business-ready data sets and analysis to clients in a more iterative, rapid, and low/no-code format that increases speed to insight without needing to rely on code-heavy IT platforms.
It’s not just data prep. In addition to wrangling even your messiest data, our analytics engineers can help enable spatial, prescriptive, and predictive analytics in a way that is simple for you to analyze and maintain.
IT and data management teams that want to enable self-service analytics and ML for business users.
Business teams that want to enable their own insights with simple, low/no-code, maintainable solutions for their analytics needs.
Product owners who want to meet users’ needs fast.
Citizen data scientists who need reliable access to data in all its forms.
Governance and security teams that want to ensure quality and secure data.
While no two customers are exactly alike, below we list examples of what is typically covered and not covered.
Our team has deep experience and expertise in Alteryx, KNIME, Tableau Prep, Power Platform, Matillion, Tableau CRM, DBT, Python, and R.
Data engineering is often concerned with large-scale infrastructure tasks, including data ingestion and warehousing. Analytics engineering is focused on business logic, requires knowledge in how the data is actually used, and is better oriented to understand the underlying business value of their work.
Because of the breadth of capabilities analytics engineering projects can enable, no two projects are alike. Pilots or POC projects can start as low as $20,000 – $30,000. That price will vary based on the complexity of the use case.
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