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Breaking the code: Why no-code platforms are gaining traction with IT and the business
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Machine learning is demonstrating its mettle across industries
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Learn how adopting a modern data strategy with cloud-based storage, database, analytics, and machine learning can open up new business opportunities, speed decision making, and improve efficiencies
Experts agree: A data-driven culture starts at the top
Leadership teams must be data evangelists – but the entire organization will need the right training and tools for putting the data to use iStock
No matter the analogy about data that it’s the lifeblood, fuel, engine, or new oil business leaders have little doubt about its importance to driving decision making and delivering business value.
The challenge for many leadership teams is that not everyone in the organization shares that vision of data’s power and possibilities. Often, they don’t embrace data for decision-making because they don’t have easy access to the right tools and license to explore data for ideas and opportunities.
VC and industry leaders say enterprise climate is promising for startups, but practitioner contact will be key
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Moore’s Law is dead, right? Think again.
Although the historical annual improvement of about 40% in central processing unit performance is slowing, the combination of CPUs packaged with alternative processors is improving at a rate of more than 100% per annum. These unprecedented and massive improvements in processing power combined with data and artificial intelligence will completely change the way we think about designing hardware, writing software and applying technology to businesses.
Every industry will be disrupted. You hear that all the time. Well, it’s absolutely true and we’re going to explain why and what it all means.
In this Breaking Analysis, we’re going to unveil some data that suggests we’re entering a new era of innovation where inexpensive processing capabilities will power an explosion of machine intelligence applications. We’ll also tell you what new bottlenecks will emerge and what this means for system architectures and industry transformations in