Welcome to our blog.

From BI to Data Science: An Interview with Tom Clancy

At Ironside, we believe that data science is a team sport, and should be accessible to and enable as many players as possible. We work with clients on a regular basis to make data science accessible within their organization. But we also do…

Business Analytics

Defining Factors for a Successful Modern Analytics Strategy

When defining or assessing a Data & Analytics Strategy, Ironside leverages a proven framework of understanding the current state and comparing it to a desirable future state with a focus on six key areas, or pillars. In a previous…

Technology Spotlight

Ironside Tech Tip: Cognos Data Sets - An Alternative Approach to Data-Driven Prompts

What is the most common, most vital need of any business? Speed. Speed to adapt, to respond, to evolve. It is important, not just at the big picture level, but on a daily basis as well. If you're constantly waiting for information, then…

FP&A

How "Work" is Hindering Your Finance Team

I was recently discussing with a colleague what differentiates our various clients. While each of them is undergoing improvement in some form, it is clear that some Offices of Finance perform significantly better than others. The basic difference…

Business Analytics

Is "Self-Service" Analytics the New "Big" Data?

Last spring, I had the opportunity to attend a local analytics conference with Dr. Claudia Imhoff as the keynote speaker. As she got on stage to begin her presentation, she started out by making a statement along the lines of “For every…

Business Analytics, Technology Spotlight

New Features of Cognos Analytics v11.1: Data Module Enhancements

In previous releases of Cognos Analytics, we have seen a trend of integrating many of the features of metadata modeling in Framework Manager into the Cognos Analytics interface. This trend is continuing with new or improved modeling capabilities…

Business Analytics, Data Management

Challenges of Customer Segmentation

Customer segmentation is defined as “the process of dividing customers into groups based on common characteristics so companies can market to each group effectively and appropriately.” By using the correct attributes to define the customer…

Data Management, Technology Spotlight

Snowflake: A Modern Cloud-Based SQL Data Warehouse

With the maturing and ever increasing acceptance of the cloud across multiple industries and the data gravity gradually moving to the cloud, i.e. more data being generated in the cloud, we are seeing some interesting cloud-based data and analytics…

Business Analytics, Technology Spotlight

Metadata Comparison - Microsoft vs. Cognos

Metadata has long been an essential part of every successful organization’s analytics strategy. In this article, I sat down with two of Ironside’s foremost experts on the topic to discuss its origin and value and how two of the industry’s…

Business Analytics, Data Management

What to Consider When Building Your Data Democratization Strategy

Data democratization is the ability of an organization to provide information to end users in an easy and effective way. The goal is to provide self-service of information to end users with minimal IT support. There are many things that can…

Data Science

Five Traits of Highly Effective Data Science Teams

2019 is the year that data science, machine learning and artificial intelligence for business will become ubiquitous. Most organizations large and small, across all industries, have recognized the benefits and competitive advantage that these…

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Welcome to our blog.

From BI to Data Science: An Interview with Tom Clancy

Defining Factors for a Successful Modern Analytics Strategy

Ironside Tech Tip: Cognos Data Sets - An Alternative Approach to Data-Driven Prompts

How "Work" is Hindering Your Finance Team

Is "Self-Service" Analytics the New "Big" Data?

New Features of Cognos Analytics v11.1: Data Module Enhancements

Challenges of Customer Segmentation

Snowflake: A Modern Cloud-Based SQL Data Warehouse

Metadata Comparison - Microsoft vs. Cognos

What to Consider When Building Your Data Democratization Strategy

Five Traits of Highly Effective Data Science Teams

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