5 Tips for a Successful Machine Learning Deployment
Corporate educator TDWI has published an eBook on five engineering requirements for machine learning
Corporate educator TDWI has published an eBook on five engineering requirements for machine learning
First, identify the data and brainstorm a use case. Then make sure everything's in place to make it
There's gold to find in the big data forest, but most companies have no map and no
Data and source-agnostic platforms will beat out siloed systems; Spark and machine learning continue to
A data lake needs to be fed and governed properly before analytics can discover kernels of
Opportunities abound to sell customer data related to transactions and product usage, but companies must be sure that data is
AI technologies have clear value paths in marketing, including sales and enhancing customer
Data governance and metadata synchronization can prevent Hadoop data from going dark.
A rock-solid business use case and data integration are pressing
Big data visualizations are now easy, but not all visuals have