Production-quality data science requires a major team effort. The good news is our Expert Models platform takes care of a large number of jobs required to build successful data science projects and products.
Expert Models is our sophisticated, yet user-friendly data-science platform which enables you to collaborate, share data and create and deploy models online. We have the data science platform and technology expertise you need and we are here to help.
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The default Expert Models setup consists of an advanced file management system including data sharing (similar to Google Drive) but designed specifically for data science. File organisation is an essential workflow to get right for anyone working with data.
Secondly, Expert Models has a data editor . This can be thought of as a simplified version of Excel, but with features useful for working with the type of large datasets used by models. Data table types can defined to ensure data is correct at entry, rather than runtime.
The modeller: Most models are not online and do not live beyond contributing to a report. These models can offer great value if made available to other audiences. One of the reasons this has not happened already is that Modellers, while they may have advanced modelling skills, are not web programmers. Expert Models allows Modellers host their models within a web interface without having to learn web programming / system administration, or engage in a long expensive development project.
We work with Modellers to publish their models online in an interface we agree is appropriate. The Modeller can then open these models up to new audiences.
The Excel user: Excel still dominates the workflow of Data Analysts and Decision Makers alike. As well as Excel being used for its obvious function of working with data, Excel is also the primary go to software for creating mini-programs that perform some repeatable action. These programs can include models, data-cleaners, connectors and other variations. All these types of program are better implemented in Expert Models. Excel has major downsides that are increasingly becoming unacceptable in a configured world. A recent IBM report focused on just this issue:
“A number of studies have been made concerning the frequency of errors in spreadsheets. Based on these, it seems that 90 percent of all sheets contain at least one error.”
These errors can be avoided when a program is built within a workflow that includes data validation and programmatic error checking mechanisms. Building models in Python inside Expert Models will inherently clean up errors.
Scripting data import from your various data sources in these Python blocks, inside the platform, also has the double effect of allowing you to understand and audit the import process and remove this repetitive task.
Experience has told us that all customers will need some kind of support and sometimes customisation to their solution that goes beyond the default Expert Models setup. For this reason we not only provide a turn-key solution like CRM packages where the problems are already very well defined, we also provide a team of experts who will work with you to understand your problem, then we help you get your models and data into Expert Models before handing over logins.
Are you interested in trying a demo account? If so, please contact us.
You can read more about this in our articles: Data Science is a Team Sport – That’s Why We Created Expert Models and Expert Models Takes Care of 13 of 15 of Your Data Science Jobs – This is What That Means For You.