DataFramed

Arianna Huffington, co-founder of The Huffington Post, woke up in a pool of blood nursing a broken cheekbone after collapsing at her desk in 2007. Various stresses and pressures in her life had manifested themself into an episode of extreme mental exhaustion. This event was the catalyst for her to write a book on well-being as well as start the behavioral-change company Thrive Global. Many of us h...

2023 was a huge year for data and AI. Everyone who didn't live under a rock started using generative AI, and much was teased by companies like OpenAI, Microsoft, Google and Meta. We saw the millions of different use cases generative AI could be applied to, as well as the iterations we could expect from the AI space, such as connected multi-modal models, LLMs in mobile devices and formal legislatio...

In January 2024, six activists were identified by British Police in London, suspected of planning to disrupt the London Stock Exchange through a lock-in. In an attempt to prevent the building from opening for trading. Despite the foiled attempt, the strategy for this protest was inherently flawed. Trading no longer requires a busy exchange with raucous shouting and phone calls to facilitate the fl...

Cookies were invented to help online shoppers, simply as an identifier so that online carts weren’t lost to the ether. Marketers quickly saw the power of using cookies for more than just maintaining session states, and moved to use them as part of their targeted advertising. Before we knew it, our online habits were being tracked, without our clear consent. The unregulated cookie-boom lasted until...

We’ve never been more aware of the word ‘hallucinate’ in a professional setting. Generative AI has taught us that we need to work in tandem with personal AI tools when we want accurate and reliable information. We’ve also seen the impacts of bias in AI systems, and why trusting outputs at face value can be a dangerous game, even for the largest tech organizations in the world. It seems we could be...

Your data project doesn't end once you have results. In order to have impact, you need to communicate those results to others. Presentations filled with endless tables and technical jargon can easily become tedious, leading your audience to lose interest or misunderstand your point. Data storytelling provides a solution to this: by creating a narrative around your results you can increase engageme...

Data used to be the exhaust of our work activities, until we started seeing the value it can provide. Today, data is a strategic asset, used to gain a competitive advantage and well guarded from those that might use it to harm others. With this change in attitude, how we access and safeguard our data has improved massively. However, data breaches are not a thing of the past, and with the advent of...

We learned so much about generative AI and its impact for people and organizations in 2023, we must anticipate many more innovations in the data and AI space 2024. One of the best places to look for this information is through the wisdom of those that spend their time with the Fortune 1000 leaders that are helping shape data and AI practices. Wavestone’s annual Data and AI Executive Leadership Sur...

Regardless of profession, the work we do leaves behind a trace of actions that help us achieve our goals. This is especially true for those that work with data. For large enterprises where there are seemingly countless processes happening at any one time, keeping track of these processes is crucial. Given the scale of these processes, one small efficiency gain can leads to a staggering amount of t...

There are a few caveats to using generative AI tools, those caveats have led to a few tips that have quickly become second nature to those that use LLMs like ChatGPT. The main one being: have the domain knowledge to validate the output in order to avoid hallucinations. Hallucinations are one of the weak spots for LLMs due to the nature of the way they are built, as they are trained to correlate da...

Over the past year, we’ve seen a full hype cycle of hysteria and discourse surrounding generative AI. It almost seems difficult to think back to a time when no one had used ChatGPT. We are in the midst of the fourth industrial revolution, and technology is moving rapidly. Better performing and more capable models are being released at a stunning rate, and with the growing presence of multimodal AI...

Effective data management has become a cornerstone of success in our digital era. It involves not just collecting and storing information but also organizing, securing, and leveraging data to drive progress and innovation. Many organizations turn to tools like Snowflake for advanced data warehousing capabilities. However, while Snowflake enhances data storage and access, it's not a complete soluti...

There's often a debate in technology ethics on whether technology is neutral or not. On one hand, critics have rightfully pointed out examples of technology exacerbating the climate crisis, amplifying bias as we've seen in our recent episode with Dr. Joy Buolamwini, or contributing to the spread of misinformation and disinformation. Conversely, we cannot deny the many wonderful things technology h...

The consequences of data not being easily accessible within an organization are profound. Good decision-making often relies on good information, and with crucial insights locked behind closed doors, decision-makers may have to rely on incomplete information, stifling their ability to innovate through a lack of comprehensive data access or an inability to leverage data to its full potential. The ra...

We are all guilty of getting excited about shiny new toys in whatever guise they present themselves to us. For many of us, lots of the recent shiny new toys have been ways of utilizing AI to update and iterate on the ways that we work. Leadership teams have been looking for ways that their organizations can incorporate AI solutions into their products, regardless of whether they might be the most...

Poor data engineering is like building a shaky foundation for a house—it leads to unreliable information, wasted time and money, and even legal problems, making everything less dependable and more troublesome in our digital world. In the retail industry specifically, data engineering is particularly important for managing and analyzing large volumes of sales, inventory, and customer data, enabling...

In 2015 an MIT Researcher set out to build a mirror that would augment their face to look like those of their idols. The execution of this went well, until it came to testing. When the researcher came to use the mirror, no face was detected. The researcher was not detected in the mirror, until that is, she put on a white mask, at which point, the mirror worked as expected.  Three years later,...

I think it's safe to say that we are in the peak of the hype cycle with generative AI. Almost every week now, we see new startups with exciting new GenAI use-cases and products. However, exciting doesn't necessarily translate to useful. And now more than ever, it's important for leaders, whether at incumbents or startups, to adapt and drive value with generative AI and focus on useful use-cases. S...

Throughout the past year, we've seen AI go from a nice-to-have, to a must-have in almost every large organization’s boardroom. There’s been more and more focus deploy AI  by leadership teams, and as a result, there's never been more pressure on the data team to deliver with AI. However, as the pressure to deliver with AI grows, the need to build safe and trustworthy experiences has also never...

In today's AI landscape, organizations are actively exploring how to seamlessly embed AI into their products, systems, processes, and workflows. The success of ChatGPT stands as a testament to this. Its success is not solely due to the performance of the underlying model; a significant part of its appeal lies in its human-centered user experience, particularly its chat interface. Beyond the founda...

It's been almost a year since ChatGPT was released, mainstreaming AI into the collective consciousness in the process. Since that moment, we've seen a really spirited debate emerge within the data & AI communities, and really public discourse at large. The focal point of this debate is whether AI is or will lead to existential risk for the human species at large. We've seen thinkers such as El...

From the dawn of humanity, decisions, both big and small, have shaped our trajectory. Decisions have built civilizations, forged alliances, and even charted the course of our very evolution. And now, as data & AI become more widespread, the potential upside for better decision making is massive. Yet, like any technology, the true value of data & AI is realized by how we wield it.  We'...

In data science, the push for unbiased machine learning models is evident. So much effort is made into ensuring the products we create are done thoughtfully and correctly, but are we investing the same effort in ensuring our teams, the very architects of these models, are diverse and inclusive? Bias in data can lead to skewed results, and similarly, a lack of diversity in teams can result in narro...

It's been a year since ChatGPT burst onto the scene. It has given many of us a sense of the power and potential that LLMs hold in revolutionizing the global economy. But the power that generative AI brings also comes with inherent risks that need to be mitigated.  For those working in AI, the task at hand is monumental: to chart a safe and ethical course for the deployment and use of artifici...

For the past few years, we've seen the importance of data literacy and why organizations must invest in a data-driven culture, mindset, and skillset. However, as generative AI tools like ChatGPT have risen to prominence in the past year, AI literacy has never been more important. But how do we begin to approach AI literacy? Is it an extension of data literacy, a complement, or a new paradigm altog...