Hadoop has become the preferred choice for big data analytics. It can handle both structured and unstructured data at very high volumes with an unprecedented price/performance ratio. Hadoop’s ecosystem advances now also make it suitable for real-time analytics.
February 2, 2015
Trends Section: SAP Announces Marketing Gap Analysis Tool That Sets the Foundation for Customer Engagement Success
January 27, 2015
Today’s customers have higher expectations for organizations than ever before. They engage with brands across multiple channels throughout their customer journey and demand personalized treatment, making marketers critically dependent on sophisticated technology as a result. Unfortunately, acquiring the best solutions for their organizational needs is not a simple task. If brands make the wrong choices and implement technology that does not meet their business needs, they miss critical opportunities to connect with target customers to drive growth and advocacy.
January 24, 2015
Every admin should scrutinize the CRM system to determine what can encourage better-quality data entry. This does not mean every field should be required, but make every required field matter.
January 12, 2015
This white paper highlights the differences between a relational database and a distributed document-oriented database, the implications for application development, and guidance that can ease the transition from relational to NoSQL database technology.
December 15, 2014
At this summer’s O’Reilly Open Source Convention (OSCON), Byron Ruth, a lead analyst/programmer with the Children’s Hospital of Philadelphia (CHoP), spoke about a topic that’s near and dear to the hearts of data management (DM) practitioners everywhere: ETL.
October 12, 2014
Ten years ago we were looking at data that was explicitly captured inside an enterprise as the transactions – as payments, as inventory info, resource management information, CRM systems and sales mgt info. These were in the realm of megabytes and gigabytes, and it was mostly transactions. Then we started to track interactions between companies and customers. Not just transactional data but sales records; CRM data; every phone call started getting recorded, transcribed and processed; the clickstream that we captured from our web interactions, web servers and online sales that became a part of the single view of the customer.
October 5, 2014
The development of Hadoop and the Hadoop Distributed File System has made it possible to load and process large files of data in a highly scalable, fault tolerant environment. The data loaded into the HDFS can be queried using a batch process provided by MapReduce and other cluster computing frameworks, which will parallelize jobs for developers by distributing processing to the data located on a pool of servers that can be easily scaled.