Your data and AI tools are important, and outcomes are critical, but with today’s data-driven world, businesses must accelerate outcomes while improving IT cost efficiency. But how do you achieve this?
First, Data and AI initiatives must have intelligent workflows where the data lifecycle can work
The numbers are alarming. In 2018, the World Health Organization, reported the United States had the sixth highest number of preterm births in the world.
In the United States today, 10 percent of children are born premature—three or more weeks before their due date. According to the 2019 March of
Imagine opening your mailbox and seeing a letter addressed to “current resident,” or having your financial institution’s AI powered digital assistant inform you that your replacement card is on its way to your old address.
Most people would take this impersonal letter, throw it in the trash, and go
During the IBM flagship Think conference in San Francisco today, businesses looking to accelerate their transformation with the IBM AI Watson were treated to news that they’ll be able to build, deploy and run AI models and applications across any cloud, giving them the freedom to apply Watson
A faster journey to AI for the enterprise? What’s the secret? In this interview with Dinesh Nirmal, IBM vice president of analytics development, he shares the highlights of his upcoming Think session: “Modernizing Your Data Estates for an AI and Multicloud World.” On Wednesday, 13 February, he and
Martec's law states, “Technology changes exponentially; organizations change logarithmically.” Translation? Technology will accelerate faster than companies can adapt to increasing data growth and adopt new business models.
Most businesses, independent of their business model, are concerned with compliance and profit. The business must comply with the law, regulations and conduct guidelines, and to be sustainable, the business must remain profitable.
To attain digital transformation maturity, organizations have to build a foundation of trusted customer and product data. This includes integrating policies which control how data is used within the enterprise and protecting sensitive information.
There’s a general need for next-gen executives to not only understand corporate regulations, but be able to adhere to and follow them using metadata solutions like data governance. As the business world’s top asset becomes data, data governance will ensure that data and information being handled is
The new Gartner Magic Quadrant (MQ) for Master Data Management has been published, and what you might not notice at first glance is that this year, IBM chose not to participate. Gartner still included IBM in the MQ. However, we did decline to engage in the process and provide detailed data for
Today’s most successful companies think differently about data governance. Recent Aberdeen research suggests that top-performing companies are those that create a more holistic approach to data governance, incorporating the right technologies, processes, skill sets and internal capabilities.
Some people think of master data management (MDM) purely as a platform for organizing and mobilizing enterprise information. While this is true, leading companies view MDM more as a philosophy or a set of best practices, not just a suite of software tools.