Metrics are vital to any management process; they not only quantify activity, but can define the variation between what is observed and what is desired. Technical Usage MetricsMany of the …
Big Data – Readiness and Risk Assessment
As with any development project, implementation of a Big Data or Data Science initiative should align with real business needs. Assess organizational readiness in relation to critical success factors: Business …
Big Data – Visualization Tools
Traditional tools in data visualization have both a data and a graphical component. Advanced visualization and discovery tools use in-memory architecture to allow users to interact with the data. Patterns …
Big Data – Cloud Solutions and Statistical Computing
Big Data – Cloud Solutions: There are vendors who provide cloud storage and integration for Big Data, including analytic capabilities. Based on defined standards, customers load their data a cloud …
Big Data – Distributed File-Based Databases
Distributed file-based solutions technologies, such as the open source Hadoop, are an inexpensive way to store large amounts of data in different formats. Hadoop stores files of any type – …
Big Data – MPP Shared-nothing Technologies and Architecture
MPP has evolved because traditional computing paradigms (indexes, distributed data sets, etc.) did not provide acceptable response times on massive tables. Massively Parallel Processing (MPP) Shared-nothing Database technologies have become …
Predictive Analytics Vs. Prescriptive Analytics
Predictive Analytics Predictive Analytics is the sub-field of Supervised Learning where users attempt to model data elements and predict future outcomes through evaluation of probability estimates. Rooted deeply in mathematics …