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 …
Big Data – Activities
Define Big Data Strategy and Business Needs An organization’s Big Data strategy needs to be aligned with and support its overall business strategy and business requirements and be part of …
Big Data Strategy – Criteria
A Big Data strategy must include criteria to evaluate: What problems the organization is trying to solve. What it needs analytics for: While one advantage of Data Science is that …
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 …