EMC positions the Greenplum HD Data Computing Appliance as a key component in its new Hadoop-centric analytics push.
How to get to the root of ETL and data integration issues.
We explore the benefits and drawbacks of integrating data from social media with your existing BI investment.
TDWI Research's Philip Russom offers commonsense rules for handling the next generation of data integration.
Using analytic software to greatly accelerate the process, Swedish police analyzed years of crime reports and found links that helped them arrest a serial shooting suspect who was terrorizing the area.
Seven tips to help your data analyst give you the best insights from your data.
Amid all the hype, three core principles will help ensure your success with a data warehouse.
TDWI's recent World Conference made the case that change is inherent in BI and DW. BI pros are going to have to accommodate event processing. It's all part of the ongoing transition to Hyper business intelligence.
Why the impact of cloud BI is unavoidable.
The path to data governance starts with small steps.
What’s ahead for BI? We offer five trends happening now that are irreversible and have substantial implications for BI.
Microsoft sees a bifurcated data warehousing market, with Fast Track SQL Server on the low end and SQL Server Parallel Data Warehouse at the top.
An overwhelming majority of organizations believe mobile BI will play an important -- perhaps even critical -- role in their information futures.
BI projects are expensive, time-consuming, and risky. Advanced prototyping can bring IT and business users together.
Enterprises finally seem serious about grappling with what makes for good data governance.
Business intelligence vendors still seem to run on a test track while users just want to get on the road with data.
How data integration developers can include parallelism into data integration models.
In 2010 we learned that big data doesn’t mean big insights. What will we learn this year?
To react quickly to a changing regulatory environment, BI projects need a flexible and robust -- and agile -- underlying architecture.
Instead of just reporting on data, shops should be exploring their data. This is particularly true in government, where very large data sets can benefit from cutting-edge visual data exploration technologies.