AI/ML On Data
Translate Data Into Actionable Insights
Using recent advances in Machine Learning and Artificial Intelligence, let us help you initiate a Proof of Concept around ML/AI, organize your data and dashboards, find or train talent, and continue to transform your organization into a data-driven powerhouse by utilizing open-source software.
Decades of successfully working with clients, and providing them with talented developers, has shaped our approach to helping you optimize your business while building in-house talent for the future.
-
We perform affordable analysis of your situation and prepare an outline of recommendations for moving your business forward.
-
We work on the specific pieces you request to get your business data-driven.
-
While we work on your solution we find and grow talent that you can hire full-time. This can drastically improve less efficient recruiting and interview processes.
-
Bring your data together, not necessarily with a data-lake, but with a "virtual" data lake of metadata, essential attributes, governance requirements, and clear user-stories around the data (Data virtualization, data-fabric or data-catalog technologies).
-
Use notebooks and visualization (typically Jupyter and PyViz) tools to get a quick peek at your data while using scalable tools to transform your data to become "science-ready" or "model-ready" (Dask, xarray, pandas).
-
Initiate AI brainstorming by using interviews with your team to uncover what data features are most important, and then couple that with automated tools to look at what else the data might be able to tell you.
-
Establish a deployable and manageable pipeline to ensure the features you care about can be extracted, managed, and updated as things change.
-
Build and validate initial models.
-
Automate the previous 3 steps (and test a range of models).
-
Communicate and publish the model (dashboards, and visualization)
-
Setup processes and software to help you manage the model going forward.
The end result is a powerful data-driven business.
Steps To Transform Your Data
Focus Areas
-
Data Management Audit : Data-lakes are an optimization, but the real challenge is to organize the meta-data so that everyone has access to the same information, allowing you to iterate on how to use data effectively across your organization. You also want to ensure that it is not trapped in silos that do not allow the best algorithms to be used against it. By being focused around one framework, or one language, some data-management mechanisms actually restrict your use of the rapidly-growing set of algorithms freely available today in Scala, C/C++, Python, R, and other languages.
-
Visualization and DashBoarding : We help you build the best visualizations to make sense of your data as well as create flexible dashboards (from notebooks or scripts) that help you manage your business.
-
Feature Engineering Analysis : We can use unsupervised learning approaches to extract features from your raw data.
-
Building Predictive Models : We help you build predictive models by using a wide variety of techniques and the latest innovations, specific to your industry.
-
Automated Machine Learning : There are many steps in the data-science process that can be partially or fully automated, but this has to be done in a way that works for your data and your business. Some products are sold with the claim that they will automate away data science, but typically you end up spending far more resources re-architecting your business around their solution. Let us adapt existing open-source tools to automate your business needs individually.