As you’ve seen in some of our previous articles about the financial services industry, there’s a lot that goes on behind the scenes to enable financial services firms to gain new customers and provide accurate investment advice.  What matters most, though, is that the technology powering all the fund transactions, client correspondence, market analytics, and sales strategies remains reliable and responsive on a daily basis. Read more

By now we all know that Hadoop is a central part of many big data projects, but how do we integrate this technology with some of the more traditional approaches to data handling? Is there a way to make sure our Hadoop cluster is interacting with and enriching the rest of our analytics environment? Luckily, there’s a whole suite of utilities that interact with Hadoop to address these questions, and it’s important to know what they are and how to take advantage of them. In this article, we’re going to take a quick look at five commonly used utilities in the Hadoop Ecosystem to help you understand how they can be used to integrate the Hadoop framework with more traditional relational databases and leverage the data for analytical purposes. Read more

The modern data landscape is so much more diverse than it was in the past, and the modern data warehouse needs to increase its flexibility to keep up. In the modern warehouse, it’s not enough to just source all the data; it’s equally important to source all data types as well. Data professionals need to derive insights from various systems of engagement (social media, mobile), systems of record (ERP systems, CRM systems, databases), and the Internet of Things, which means sourcing unstructured, semi-structured and structured data. These needs are driving a rapid evolution away from the familiar enterprise data warehouse (EDW) and toward a new, more flexible solution: the logical data warehouse (LDW). Read more