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 go wrong when rolling out data democratization projects. The purpose of this article is to identify potential issues and provide guidance on how to avoid them in the democratization process.
Read moreWhen asked “What’s your data strategy?” do you reply “We’re getting Hadoop…” or “We just hired a data scientist…” or “If we only had a data lake, all our problems would be solved…”? Plotting a good data strategy requires more than buying a tool, hiring a resource, or adding a component to your architecture. You need something to describe:
- the goals you are trying to achieve,
- the stakeholders you are trying to serve, and
- the internal capabilities required to satisfy those stakeholders and achieve those goals
In the first installment of our series on bimodal analytics, we talked about the origins of Mode 2 analytics. We looked at some of the challenges around implementing true bimodal analytics within IBM Cognos Analytics 11 and touched on some of the vendors who were born as Mode 2 platforms. This second installment will focus specifically on how to enable Mode 2 analytics within the organization using Cognos.
Read moreEarlier today the AWS team unveiled two new capabilities for QuickSight, Amazon’s signature Business Intelligence tool. Speaking live from the AWS re:Invent conference at the Venetian in Las Vegas, the four hosts announced the ability for users to easily embed QuickSight dashboards in applications and previewed new native Machine Learning capabilities. Read more
You’ve undoubtedly heard the term “Self-Service Analytics” thrown around, but what does self-service analytics actually look like in practice? What does a self-service user look like? And what prep work is needed to enable these people to serve themselves?
I spoke with Crystal Meyers, our resident Tableau guru and self-service analytics advocate to learn more. The following is a conversation with Crystal, where she explained some of the nuances of self-service analytics. Read more
Last week at Analytics University, IBM formally announced the release of the next major version of Cognos Analytics, v11.1.
IBM has hinted at the inclusion of “smarts” for “augmented analytics” and improvements in the usability of this new version over the past year. Our expectation was that these improvements would continue to “modernize” Cognos and help address some of the competitive pressures that organizations with legacy investments have been encountering in recent years. Read more
At least weekly, I am granted the opportunity to meet and work alongside experienced professionals who serve in a corporate business intelligence (BI) leadership function. When they describe their role upon introduction, there is a common thread to the scope of influence and control which usually intersects one or more of these domains: Read more
Well in advance of the IBM acquisition of Cognos, the Cognos name was synonymous with powerful, trusted enterprise business intelligence and managed reporting. Between its ability to scale to meet the needs of the largest enterprises, its robust, governed metadata layer that made it possible to report against a vast array of different data sources, powerful reporting capabilities churning out highly complex managed BI reporting solutions, and ad-hoc reporting and analysis against those governed data sources, IBM Cognos was the answer for almost all enterprise reporting needs. Until it wasn’t.
Read moreWe’re often asked how “our methodology” helps drive better user adoption. The key to user adoption is satisfying users’ needs, within the context of their environment. This sounds obvious, but it’s surprisingly easy to miss the mark. And all too often, projects are doomed from the beginning…with the requirements. Read more
The last several years have represented an interesting journey for organizations and teams leveraging Cognos for analytics. During that time, visual data discovery tools have made a significant impact. However, as of late, we have seen the pendulum swing back to concepts introduced by enterprise BI tools long ago.¹ What’s old is new again.
When these new tools arrived, they challenged both the status quo and what many of us saw as an ideal solution to the localized, ungoverned, manually-intensive, and often error-prone data manipulation (i.e. “shadow analytics”) processes of the past. If we think back to the dawn of the modern business intelligence age in the mid 1990’s, we realize that these challenges are what tools like Cognos were developed to solve. 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.