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Some dread it; some delight in it; either way, the construction of a data infrastructure requires perfect understanding of data and its resulting use cases.

The world is becoming ever more aware of AI’s potential. There is real momentum, evidenced by the race for global leadership in artificial intelligence.

It’s no secret that data marketing is huge.

With the cloud, users are offered abstract Infrastructure as a Service (IaaS*) rather than finite resources they can buy, known as on-premise infrastructure. The cloud can also offer an application (PaaS*: Platform as a Service) or a function (FaaS*: Function As A Service).

Creating quality content on Amazon is critical to a brand’s success and will influence two aspects of your activity.

This is especially true when it comes to knowing which data is most important in order to understand consumers. It is less about WHO they are, WHAT they did, and much more about HOW they behaved. The way consumers behave on an online platform will tell you more about their propensity to spend than other factors. Brands need to capture this data, and many do not.

Needless to say, China’s internet ecosystem is now dominated by 3 giants: Baidu, Alibaba, and Tencent, or what we call the “BAT” – i.e. the “GAF (Google / Amazon / Facebook)” of the Middle Kingdom. These 3 giants collect billions of consumer data on a daily basis and they are all trying to monetize the data within their own independent ecosystems.

Launching a media campaign on Amazon is a must if you want to raise awareness and increase activity, but it’s also a complex step which requires perfect understanding of this ecosystem.

“Will machines replace humans?” The year was 1940, and Franklin D. Roosevelt, in a debate with the president of MIT, was worrying about the impact of machines on  the unemployment rate. Sixteen years later, at the Dartmouth conference, Artificial Intelligence (AI) officially enters the pantheon of scientific disciplines.

With the advance of automation, the field of digital marketing is changing in profound ways. While advertisers used to outsource their campaigns to external partners in the past, many are now increasingly shifting to carrying them out in-house due to the increasing accessibility of technological resources. Although this may seem simple at first glance, it proves to be much more complicated when faced with the harsh reality of onboarding a variety of tools. Advertisers need consulting, which presents itself as an opportunity for a growing number of IT consultancies on the market. Will they eventually eliminate established media agencies?

In 2016, e-commerce accounted for 8.5% of total global sales. From now until 2021, this figure is set to double, reaching almost 18%. It has become crucial for a brand to include this channel within their strategy and get to grips with how it works.

In an ideal world, businesses would know exactly how much they can sell, when and where. But building an effective demand prediction model is easier said than done, especially when the retail sector is getting increasingly fragmented.

Artefact has adapted Lean Manufacturing methodologies in order to remedy the seven sources of waste traditionally encountered in artificial intelligence projects.

It’s a Wrap! It has been an inspiring and exhilarating last three days at CogX 2019. We’ve thoroughly enjoyed being at the global epicenter of AI and Data, speaking to future and current industry titans at our stand and taking in an immense depth of knowledge on both highly exciting prospects and deeply pressing issues that are associated with our collective future.

Data deluge Day two of CogEx (or #SogEx as some wag has christened the event on Twitter in the aftermath of yesterday’s downpours), thankfully the skies have remained clear and positivity has shone through. This was apparent in today’s opening session on the main stage, ‘Transformation in the age of machines’ from Salim Ismail of OpenEXO.