In today’s “Big Data” era, a lot of data, in volume and variety, is being continuously generated across various channels within an enterprise and in the Cloud. To drive exploratory analysis and make accurate predictions, we need to connect, collate, and consume all of this data to make clean, consistent data easily and quickly available to analysts and data scientists.
Read moreGathering data is an essential step before performing analysis in Power BI Desktop. The tool allows users to connect with many different data sources, such as traditional or cloud databases, text files, big data, and live streams. Among these sources are SQL Server Analysis Services (SSAS) Tabular models, which are widely leveraged for enterprise solutions. Why? Let’s dive into Tabular Modeling to learn more.
Read moreIn the first installment of this series, we discussed the origins of Mode 2 Analytics, and in the second installment we focused on how to enable this capability in your organization using Cognos. Now that we’ve learned all about how Mode 2 works, let’s walk through a sample use case that highlights the Bimodal Analytics Lifecycle as well as the technical capabilities of Cognos Analytics and how they fit together.
In this example, you are the manager of a Healthcare Call Center system that is comprised of seven (7) regional centers across the country. Each call center handles contact (phone calls and online chats) from the customers that are located within the states that make up those regions.
Read moreWhen you think about the different ways that data gets used in your company, what comes to mind?
You surely have some executive dashboards, and some quarterly reports. There might be a reporting portal containing everything that IT created for anyone within the past decade.
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 this within our own company. Meet Tom Clancy – hear about his journey and what he has learned along the way.
Read moreWhen 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.
Read moreLast 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 time the phrase ‘Big Data’ is mentioned today, we will all take a shot during happy hour.”
(Tip: Don’t try that for this article.)
Read moreIn 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 being incorporated into Cognos Analytics 11.1 Data Modules.
Read moreCustomer 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 segment, it allows companies to identify the right customers for targeted and relevant offers. Those who successfully define and maintain customer segmentation can derive a competitive advantage from the implementation by improving customer experience.
Read moreMetadata 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 leading vendors in the analytics space address this core capability in a bimodal analytics world.
Susan Ma and Suresh Edara are both long-time Ironside consultants with deep expertise in top BI toolsets: Microsoft and Cognos.
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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.