In predictive analytics, machine learning involves training a computer to evaluate data sets and create prediction models from trends it finds in the data. Machine learning builds off traditional statistics and creates larger and more advanced models faster than a person ever could.
This article demonstrates processing a web-based data source in the IRI Voracity data management platform. Static and streaming data defined in URLs — including flat files in formats like CSV or through FTP/S, HTTP/S, HDFS, Kafka, MQTT, and MongoDB — are supported by the default data processing engine in Voracity, CoSort Version 10.
Power BI is a business analytics and data visualization package from Microsoft that can provide custom-designed dashboards and reports ready for web or mobile display. Like other BI and analytic tools, Power BI can also perform simple data wrangling jobs like sorting and aggregation before and after the data are displayed.
“Have you stopped speeding?” You could probably object to a leading question like this in court, but what happens when an important question with only a yes or no answer is solicited on a mandatory form, and the response becomes part of an actionable database record?
Note: This article covers the third available IRI customer method for statically masking or encrypting PII in structured MongoDB collections through the IRI FieldShield product or IRI Voracity platform (both powered by IRI CoSort v10 and its support of the native MongoDB driver).
Users of PII masking tools like FieldShield, DarkShield, and CellShield EE in the IRI Data Protector Suite or Voracity platform can catalog and search their data — and apply data transformation and protection functions as rules — using built-in data classification infrastructure in their common front-end IDE, IRI Workbench, built on Eclipse™.