Predictive analytics blends data from both descriptive and diagnostic analytics to detect exceptions and patterns that can help predict trends.
It is a key discipline in the broad field of data analytics, which uses quantitative methods and data expertise to answer important questions about businesses, scientific endeavors, and other data-driven fields of inquiry.
Many organizations employ predictive analytics to optimize marketing and operations, improve performance and increase customer acquisition, retention and revenue. Predictive models help companies attract, retain and nurture customers.
It is a form of advanced analytics that relies on a mix of retrospective and current data to forecast future behavior and activity. Statistical analysis and ML are deployed to build predictive models that can score the likelihood of certain events happening within pre-determined time periods.
Snowflake and Predictive Analytics
Snowflake’s Data Cloud allows companies to collect a mix of unstructured, semi-structured, and structured data to build the predictive modeling needed to drive predictive insights. In addition, Snowflake’s deep partner ecosystem provides a wide range of platforms and tools to expand all data analytics capabilities in the cloud.