Data is everywhere — veritable treasure troves of it. But with the constant evolution of businesses and customers, that data grows exponentially day by day. New sources come online constantly, and without the right architecture and pipeline, it’s difficult to extract value from that data. Many organizations simply don’t have the engineers or architects to manage it all.
The lack of talented data scientists, the presence of fragmented data and a plethora of tools, practices and frameworks to select from in tandem with stringent IT standards for training and deployment make it difficult to operationalize ML models. It’s also tough to operationalize ML models with unclear accuracy and unaudited predictions.
At DMI, we’ve built our business around data management, AI and ML, and we can help you get the most from your data. We can design and engineer the proper systems and pipelines to make sure your data is accessible, manageable, understandable and — most of all — valuable.
Simplify the Process of Turning Data Into Insights
At DMI, we have a variety of tools, expert engineers and experienced architects to help you build a data pipeline that extracts value. We can deploy the necessary talent to engineer lakeshore capabilities from various sources, including ETL. We’ll help you build your data architecture so your operations team has self-service capabilities while reducing time to market. All with strong governance practices that ensure workloads don’t spin out of control and duplicate reports won’t generate unnecessary costs or clutter.
DMI’s data science integration enables you to operationalize data science models on any cloud while establishing trust in AI outcomes. Furthermore, with ModelOps, you’ll be able to manage and govern the AI lifecycle, optimize business judgments with prescriptive analytics and speed up time-to-value with visual modeling tools.