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
Tag Archive for: Big Data
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
Business intelligence has been around for a long time. From decision support systems in the 1960s through Ralph Kimball’s books on dimensional modeling in the 1980s, the core concepts of the discipline are decades old. As these concepts and the products built around them mature, more advanced techniques and technologies come to light that evolve and redefine what we thought we knew about the business intelligence space and business intelligence’s future. For instance, developments like the cloud, data visualization tools, and predictive analytics are changing the way businesses evaluate and make decisions from their data. Read more
By now, we’ve all heard the V3 definition for Big Data maybe a million times: Volume (Size of Data), Variety (Type of Data) and Velocity (Frequency of Data) with Veracity (Accuracy of Derived Insights) thrown in as an extra sometimes. The issue is that this all-too-common definition has caused some confusion in organizations around who qualifies as having big data or a big data problem. Read more
Today, our world is filled with data. It has quietly become part of our daily life, and we’ve changed our routines to accommodate it. Beyond the impact it’s had on us, data itself has dramatically changed over the past two decades due to continual advances in internet and storage technology. Almost everything we interact with now is digital: web browsers, smart phones, tablets, social media accounts, and much more. Read more
ELT is a term heard increasingly in today’s analytic environments. Understanding what it means, and how you can make use of it, requires understanding the traditional nature of how data warehouses are loaded and how data movement tools work. That’s why we’ve pulled this article together: to break down the ETL vs. ELT divide and show you where the similarities and differences are. Read more
Planning an information management infrastructure is a fun and exciting activity for everyone, whether they work with information systems or not. What? It isn’t? Then why are so many people building information management infrastructure solutions in Access and Excel? That’s not IM you say? Well in a way it is, though we can agree that it is neither sufficient nor sustainable for just about any organization. So why do it? Read more
Thomas Friedman’s book “The World Is Flat” describes how outsourcing, technology, and other factors helped level the business playing field around the globe. What if traditional barriers to entry for using big data and business analytics were removed? Would small to mid-sized businesses be able to compete more effectively with larger organizations? IBM has made it possible to answer these questions and many more for its customers who leverage IBM Analytic Answers. Read more
Ironside is a data, analytics, and AI consulting and technology implementation company. We work with clients to understand their business objectives and day-to-day challenges, then employ our deep expertise in data strategy, architecture and engineering, integration, business intelligence, AI, and generative AI. We create technical solutions and practical approaches designed to drive smarter, data-driven decisions across a company and help it move further and faster toward its business goals.