Metadata is a broad term referring to information about data. Its purpose is to provide us with an easily understandable context for the information we use. It answers questions we’re likely to ask about any source of data, such as where it comes from, how it’s generated, and when it was created. In data analytics, metadata comes in three main types: Read more
When’s the last time you were talking data and analytics and someone stopped the conversation to ask what a term meant? If you’re wracking your brain now, you’re not alone. It’s a rare situation to run into.
Analytics professionals like being on top of things, which means sometimes when we hear something new in a conversation we just nod and make a mental note to look it up later. And then work gets busy and before we know it we’re resolving to just do our best to pick up said buzzword through context clues in other conversations. Read more
Ironside’s Crystal Meyers was featured in Vol. 19, No. 4 of TDWI’s Business Intelligence Journal. Her points are particularly relevant as business analytics begins a more pronounced shift toward a bimodal model in 2016.
Reprinted with permission of 1105 Media, Inc. As published in TDWI’s Business Intelligence Journal. Read more
On February 11th, Ironside hosted a webinar on Association Rules for Data Mining: Beyond Market Basket Analysis. Pamela Askar, Data Scientist at Ironside, presented on how to conduct association rules for data mining using SPSS Modeler. Read more
I belong to many Sales Operations and Sales Compensation social media groups. Recently, I read a post regarding what defines Sales Performance Management (SPM) that was very tool-based. It prompted me to think about all the systems and data utilized and captured in a mature sales data strategy and to ask myself the following question: What is the heart of SPM? Read more
Even though we’re already blazing full speed ahead into 2016, it’s always important to take a minute to look back at the past year and recognize the high points that made it special. In addition to being named a Boston Business Journal Pacesetter for the second time, making the Inc. 5000 list of fastest-growing companies for the third time, and receiving IBM’s 2015 Business Intelligence Partner of the Year award, we’ve produced several valuable and popular pieces of thought leadership to enrich the analytics community. Here are the top 5 articles 2015 saw us release. We hope you find them useful as you start your journey into the new year. Read more
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
On October 1st, Ironside hosted a webinar on Putting Data on the Map with Location Intelligence. You will get all the key facts on location intelligence and hear a Q&A panel of Ironside developers, Ironside data scientists, and location intelligence specialists from our partner Pitney Bowes. 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.