AI & Data
We will help you select the right data integration tools and techniques for your disparate data and determine where you should integrate your data, such as in a data lake, a persistent staging layer in a data warehouse, or a dimensional warehouse. We will also prioritize which data to integrate—and which to not—to control your costs associated with integrating, transforming, and storing data.
We design and implement data pipelines that utilize modern tools to automate workflows and testing, standardize and speed up data transformation, remove data engineering bottlenecks, and bring more people in different data roles to the pipeline development process so that your data is ultimately more useful for decision making.
Your data needs to be cleansed, combined with disparate data, and enhanced with derived business logic to create a trusted business-ready layer in your data warehouse. We help you transform raw data into actionable information using tried-and-true principles, technologies, and techniques to create robust analytics solutions for end user consumption.
We will help you establish realistic standards and thresholds for data quality, determine your best approach to data cleansing (sometimes human intervention makes more sense than expensive technology), optimize your existing cleansing tools, and get buy-in from your organization to support initiatives that promote data quality.
By combining our data engineering skills and our deep expertise with the modern data stack, we will make sure your data pipeline efficiently gets your data from all its sources to a state where game-changing analysis can happen.
AI as a tool for transformation
AI (Artificial Intelligence) can help make sense from vast amounts of data - faster, cheaper and more accurately. When combined with the right data integration, architecture and best practices - AI can unlock organizational transformation which is not possible otherwise.