While COVID-19 continues to cause devastating disruption to the global economy more than two years into the pandemic, it is also continuing to force remarkable innovation across different industries. Companies have found new ways to sell, service and operate during the crisis. For me, there is one common theme for these innovative companies, including Qlik, and it is “Jobs to be Done.”
Since I’m now migrating NodeGraph’s processes to Qlik, I thought it may be a good time to talk about migrating data during a merger or acquisition. There are many aspects to consider. Here are some of my thoughts on why companies merge or migrate data landscapes, common M&A migration pitfalls and how to avoid them, the time and cost involved migrating data during a merger or acquisition, and other topics.
Over the course of my next two blog posts, I would like to share my thoughts around a debate raging in data architecture circles. The bone of contention? That the 21st century needs a new data management paradigm for modern analytics. First up, I’ll frame the argument and explain the two prominent approaches of data hub and data fabric. Then, I’ll cover data mesh and compare all three architectures. As always, I’d love to get your input, feedback, queries and comments!
One of the key cornerstones of the emerging field of ethical, explainable AI is recognizing and avoiding bias. As AI takes on a greater role in organizations with sometimes opaque calculations, there is an increased urgency in many businesses to get ahead of these challenges, and companies, such as IBM, Salesforce and Microsoft, have already added roles specifically with the aim of ensuring that ethics are a key consideration of AI.
In today’s tech-forward companies, CFOs are tasked with managing and overseeing an increasingly expansive domain of systems and technologies to thrive. The rise of regulatory considerations, novel market drivers and a globally connected business environment is creating an entirely new set of pressures on both the structure of the department and on leadership.
Hello, I’m Imogen Heap – musician and tech founder. Now, I know what you might be thinking. Why is a musician and composer talking to me about data? Well, for any of you that follow my work, you will know that I am a bit of a data nerd, and that’s why I loved speaking to Joe DosSantos on the latest Data Brilliant podcast. A lot of my music is powered by data. In fact, Joe and I discussed my love for how technology and data inspires me to be more creative. Want to know how?
The business world is rapidly pivoting all the time. Strategic shifts, reprioritization and being first all require being smart while moving fast. The value of agility has never stood out more due to the need to react to new realties in everything from public health, remote and in-office business policies and workflows, to broader economic concerns like supply chain as we move into recovery and revitalization.
There is an explosion of data from a myriad of sources and an insatiable demand to consume it. Traditional manual ETL methods are too brittle to keep up. Leaving many a BI team struggling to provide meaningful business insights quickly.
