Social Analytics Framework for Marketing and Sales Effectiveness
Analytics Model
Differences in use case for Column and Row-Oriented Databases.
Column-Oriented Databases are best used for analytics against large data volumes. Row-oriented Databases are best suited for transaction processing with low-complexity, high-volume datasets. NoSQL databases are best suited for high-complexity, high-volume datasets.
Source: The emerging database landscape
Potential Use Cases for Big Data Analytics
Business Intelligence Maturity
Data & Information 2.0
Site Extension: Big Data in Practice
the concept of site extension is to identify a custom network of sites whose visitor populations are very similar. If a campaign is successful on one site in the network, that performance can then be extended across the other similar sites. The solution requires two key ingredients - a massive data warehouse containing information on billions of monthly impressions and a flexible analytics platform that enables event-level reporting.
Career of the Future: Data Scientist
The Emerging Big Data Stack
The competitive axes and representative technologies on the Big Data stack are illustrated here. At the bottom tier of data, free tools are shown in red (MySQL, Postgres, Hadoop), and we see how their commercial adaptations (InfoBright, Greenplum, MapR) compete principally along the axis of speed; offering faster processing and query times. Several of these players are pushing up towards the second tier of the data stack, analytics. At this layer, the primary competitive axis is scale: few offerings can address terabyte-scale data sets, and those that do are typically proprietary. Finally, at the top layer of the big data stack lies the services that touch consumers and businesses. Here, focus within a specific sector, combined with depth that reaches downward into the analytics tier, is the defining competitive advantage.
