In an age of rapid technological transformation, governments are playing regulatory catch-up as they try to keep pace with technological developments and the increasing amount of personal identifiable information (“PII”) generated by our every-day lives. Privacy laws regulating the use of PII continue to strengthen (Gartner estimates that while 10% of the world’s population was covered by comprehensive privacy laws in 2020, by year-end 2024 it will be 75%).

In this blog series, I am exploring the “sliding doors”, or divergent paths, for creating value with data across different use cases, practices, and strategies. In this post, I want to discuss how to generate value with Data Products. As I reviewed in my last blog, grabbing the door to the better path for managing your data isn’t just about solving your particular use case: it’s ultimately about delivering value for your business.

Data engineers and architects are being asked to do more with their enterprise data than ever before. Yet, the knowledge gap between what businesses want to do with data and how they can accomplish it is growing daily—especially considering today's AI hype cycle. With all that noise in the market, it's easy to see how organizations struggle to keep pace with innovation.

It's summer of 1997, and I’m seven years old. I’ve just finished typing up my last homework assignment of the year, and a few loud keyboard taps later, it’s saved to a floppy disk, ready for printing at the school library. I grab my headphones and press play on my Walkman: Fleetwood Mac – Rumors.

In my first post of this new blog series, I introduced the concept of “sliding doors” for creating value with data: the divergent paths that organizations can take which can lead to great - or not so great - outcomes. In this post, I want to explore this for what has become a new data imperative for organizations today: effectively reporting their environmental, social and governance (ESG) data to meet new regulations.

In the popular 90’s film “Sliding Doors”, the life of the lead character, played by Gwyneth Paltrow, takes two divergent paths based on whether she catches or misses a train. Spoiler alert if you have not watched it: one path ultimately (and surprisingly) leads to a better outcome than the other.

Today, we are excited to share insights into the strategic vision, product highlights, and the roadmap that will shape the future of data integration, analytics, AI, and machine learning. Click here to check out the webinar on-demand.

January 28th is Data Privacy Day, an international effort to empower individuals and encourage businesses to respect privacy, safeguard personal data and enable trust. In fact, it so important that the National Cybersecurity Alliance has a focused program for a full week. Data privacy is not just a legal concern, it concerns everyone.

Generative AI was undoubtedly the most important data moment of 2023, and created a level of excitement for our industry that will certainly continue to be felt in 2024. As we welcome the new year, I am thrilled to share that Qlik is hitting the ground running on that front: today we are announcing the acquisition of groundbreaking technology from Kyndi, an innovator in natural language processing, search, and generative AI.

Today, at Qlik, we continue our exciting journey by revealing a completely new brand and website. This transformation goes beyond aesthetics, symbolizing our dynamic evolution at the forefront of data integration, analytics, and AI. Our new identity encapsulates innovation, clarity, and agility. In the current landscape, CEOs face the challenge of harnessing AI effectively—a realm where Qlik's unique agility and independence provide unparalleled advantage.