In this presentation, we talked about how to use machine learning for optimizing cloud server spend. This blog is a transcript of that presentation. The original video can be found here.
One of the most common limitations with business intelligence tools is that they don’t often enable you to predict what’s likely to happen in the future. Here’s how data science can help.
While the actual savings will depend on the number of servers employed and the efficiency at which they currently run, the cost benefits will be significant once the machine learning server optimization model is applied.
A common pitfall companies often fall into when pursuing data science initiatives is hiring data scientists without having a clear vision around their goals, business impact, and expected results. Here’s what you need to know before hiring a data scientist.
Why the Benefits of a Data Warehouse Outweigh the Financial Costs (and How You Can Reduce the Cost of Development)
Any organization that’s invested in an Analytics tool like Tableau, PowerBI, Looker, etc. knows that they’re only as good as the data you feed them. Challenges such as disparate sources,…
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