Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! With more and more of our lives spent online, it's no wonder today's headlines are rife with stories that sound like science fiction plot lines blurring the lines between human and computer. Earlier this year, a Google engineer voiced concerns that its chatbot model LaMDA had become sentient. Shortly after, the head of global affairs for Meta published a lengthy article about the impactful experiences that immersive technology makes possible, which featured an image of a man playing chess with a humanoid hologram -- implying technology can generate and replace that kind of human-to-human experience.

No one needs reminding that the life of the third-party cookie is increasingly finite, with only just over a year left before they are obsolete. At the same time, privacy regulation is tightening and consumers are getting more and more data-savvy, with 90% wanting more data privacy built into their devices. The loss of a lot of data that marketers have, to date, taken for granted – meaning that more decisions will have to be made with less data. Despite alternatives to the third-party cookie progressing hugely over the past two years, the way ahead is still daunting for many marketers. Targeting and measurement are the areas where the lack of third-party data will be felt most strongly.

For more than 50 years, Davos, the annual meeting of the World Economic Forum, has been an important barometer of economic, political, social, and environmental issues affecting the future of the world. So, what topics are driving the agenda for Davos 2022? The global supply chain crisis has taken on a new meaning. As the pandemic spread rapidly in 2020 and lingered in 2021, the general consensus was that disruptions to the global supply chain would be temporary albeit costly. But in 2022, it is clear that fragile supply chain may exist in a perpetual state of disruption for quite some time. In fact, the global supply chain was always in a fragile state; the pandemic laid bare just how vulnerable it was all along.

Customer data platforms (CDPs) and data management platforms (DMPs) are regularly confused. The mix-up stems from the fact that marketers use both CDPs and DMPs to collect data and to create audiences. A customer data platform allows you to collect data from relevant touchpoints where customers interact with your business. A CDP will organize this data and relay it to your other martech tools. Armed with such data, you can better target your audience with messages honed in line with your brand communication strategy.

Tendü Yoğurtçu, CTO, Precisely, directs the company's technology strategy and innovation, leading research and development programs. There's no doubt that artificial intelligence (AI) and machine learning (ML) are increasingly important to organizations seeking competitive advantage through digital transformation. More than 75% of enterprises are prioritizing AI and ML over other IT initiatives, and they are hiring data scientists in droves to make those initiatives happen. However, most of those efforts are siloed within individual business functions rather than addressing digital transformation across the enterprise. Traditional analytics cannot handle the volume and complexity of data available to organizations today.

ISLAMABAD: A meeting on broadening of tax base was informed that the Federal Board of Revenue (FBR) has provided 14 million records of financial transactions of citizens to the National Database and Registration Authority (NADRA) to compute indicative income and tax liability of non-filers by use of artificial intelligence. The meeting was presided over by Adviser to the Prime Minister on Finance Shaukat Tarin on Monday. The FBR chairman and his team gave a detailed presentation on the progress on readiness for potential taxpayer outreach initiative to boost the revenue growth and resource mobilisation. The FBR chairman apprised the adviser that steps have been initiated for compilation of data, with the support of the NADRA, which would be available to potential and current taxpayers in a presentable and comprehensible manner through a web portal. According to Business Recorder, the 14 million financial records included property transactions, vehicle purchases, registration of cars with provincial excise departments, buying/selling of movable and immovable properties, utility bills, foreign travels, and other heavy expenditures.

The arguments here often focus on the negative, the loss of third-party cookie data that enables advertisers to identify their most desirable targets across a vast network. But this doesn't mean that it's time for marketers to panic or tear their hair out in frustration. Yes, walled gardens of data will undoubtedly grow but now is the time to look beyond what we'll lose in third-party data terms towards the possibilities and opportunities. Paramount among these is the growing role of AI-driven predictive analytics in helping organizations to enrich their audience data. By using predictive analysis, publishers can deliver enrichment that's transparent and cost-effective, leading to a far higher quality of data than is delivered by the black box third-party solution that brands have used previously to target audiences.

A new study commissioned by Trifacta is shining the light on the costs of poor data quality, particularly for organizations implementing AI initiatives. The study found that dirty and disorganized data are linked to AI projects that take longer, are more expensive, and do not deliver the anticipated results. As more firms ramp up AI initiatives, the consequences of poor data quality are expected to grow. The relatively sorry state of data quality is not a new phenomenon. Ever since humans started recording events, we've had to deal with errors.

There are two Kirana stores in my neighborhood market. Their square footage is almost the same and they both offer similar products. The only differentiating factor between the two is the customer experience they both offer; one is really lousy at it, whereas the other excels at it. Guess which of these stores gets my business? It's obviously the one where I – the customer – feels valued and gets a personalized experience.

Qualified data providers include category-leading brands such as Reuters, who curate data from over 2.2 million unique news stories per year in multiple languages; Change Healthcare, who process and anonymize more than 14 billion healthcare transactions and $1 trillion in claims annually; Dun & Bradstreet, who maintain a database of more than 330 million global business records; and Foursquare, whose location data is derived from 220 million unique consumers and includes more than 60 million global commercial venues. For qualified data providers, AWS Data Exchange makes it easy to reach the millions of AWS customers migrating to the cloud by removing the need to build and maintain infrastructure for data storage, delivery, billing, and entitling. Enterprises, scientific researchers, and academic institutions have been using third-party data for decades to conduct research, power applications and analytics, train machine-learning models, and make data-driven decisions. But, as these customers subscribe to more third-party data, they often have to wait weeks to receive shipped physical media, manage sensitive credentials for multiple File Transfer Protocol (FTP) hosts and periodically check for updates, or code to several disparate application programming interfaces (APIs). These methods are inconsistent with the modern architectures customers are developing in the cloud.