DATA SCIENCE & MACHINE LEARNING
Augment legacy data by combining streaming data like Facebook or Twitter with existing database and analytics information to produce real insight (and foresight) into how the people who use your products and services are actually behaving.
Use this new combined data and combine it with 'deseasonalized data' to predict which tactics are most likely to succeed given specific parameters.
How do they prefer to shop?
Why did they leave us for a competitor?
Which factors lead to positive social media posts?
What are they likely to buy next?
Use data-driven capabilities to determine what data should be used for analyzing effectiveness of a marketing campaign. Is certain data better stored in Hadoop or is it more appropriate for Cassandra? Or, what is statistical process control telling us about how a client's spending patterns are changing over time?
Standardize, cleanse and combine data from multiple sources into holistic, unified information which can actually help make better decisions.
Blend data from internal sources with data sourced from LinkedIn, Twitter or Facebook, etc. to create a complete, unified view of Business Information and concepts (i.e. Customer, Product, Places and Internet of Things IoT)
Classify and organize both structured and unstructured data by its behavior when used in making business decisions.
Illustrate hidden relationships between data in statistics, to assess consumer sentiment or detect fraud, etc.
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