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Chief Data Officers Face Major Challenges in Data Logistics and Management

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ET Bureau: What, according to you, is the requirement for building and refining data lakes in the cloud? Dave Murray: There's no doubt that the cloud has become the platform of choice for large data analytics projects, such as data lakes. The cloud uniquely provides a massive scale and elasticity needed to make these initiatives possible. The leading cloud providers have also brought together the necessary tools and expertise to help companies move much more rapidly toward their goals. To be successful, data analytics teams need to work closely with leaders across their companies to determine the major objectives for leveraging data.


Leverage machine learning, cloud to bolster decision-making - ITWeb Africa

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In a time when data has been labelled'the new oil', businesses are scrambling to implement effective forward-thinking data management strategies that can deliver real-time insights and business value to decision-makers to drive business strategy, increase revenue, and grow profits.


25 Data Management Vendors Worth Watching 7wData

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Digital businesses such as Uber and Airbnb are built to leverage data, and these frequently cited examples of modern digital business success are companies so many others want to emulate. But working with vast streams of messy data can be a challenge for enterprise organizations, and it's only getting tougher as more data is created and collected. Business users want to be able to use this data to get a clear picture of customers, products, and more, but in order to do so that data must be managed across multiple systems -- systems that aren't necessarily compatible. These systems don't look at data in the same way. That's why data management is so important to enterprise companies and to their IT organizations.


Council Post: Is Your Company Ready To Make Artificial Intelligence And Augmented Analytics Mainstream?

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Omri Kohl is the CEO and co-founder of Pyramid Analytics. He oversees the strategy and operations for the analytics leader's global team. Although enterprise companies have ramped up the adoption of AI and advanced analytics in recent years, many of those initiatives remain as pilots only. According to one report, as of November 2019, 76% of C-suite executives claimed they struggled to scale AI investments despite acknowledging they are critical to their growth initiatives. AI is critical to advanced analytics, but neither has been included in most mainstream operations.


AI-Powered Strategy Will Transform The C-Suite

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As former consultants, we appreciate the value of people-powered analytics. Indeed, we grew up using tools like Excel and PowerPoint to uncover and share insight. However, in a world where data doubles ever two years, which is as true for the corporation as it is for the person, the idea that a consultant can do the numbers crunching effectively seems laughable. Indeed, the concept of billing 2,200 hours a year, flying hundreds of thousands of miles to client locations to gather data and developing a hundred-page presentation to help drive corporate strategy seems less viable and valuable than it did 30 years ago. In a data-driven business world it's clear that machines are beginning to play, and will play, an ever-larger role in C-suite decision making.