SAS Best Practices e-Book: Portrait of a CAO
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Access the latest thinking on topics you care about – analytics, big data, business intelligence, data management, fraud & security, marketing and risk management. We’ve assembled a variety of compelling content published by and curated from experts around the world. And it’s not all about the SAS point of view – our aim is to cover the issues that you, your peers and your competitors are faced with daily and how they’re being addressed.
Ideas and inspiration often come from looking at the world from different perspectives – through a different lens. So browse around. Read. Watch. Share. And come back for new insights as often as you like.
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Dell Digital Business Services
Whitepaper: Artificial Intelligence and Analytics
In this whitepaper, DBS Advanced Analytics analyst Shatanjoy Ray looks at how the birth of the data-driven economy at the turn of the century, new age computational tools and digital transformations have been embraced by a wide variety of industries. The paper looks at the implications of the Artificial Intelligence driven analytics in industries such as Healthcare, Manufacturing, Banking, Insurance, among others.
Organizations across industries are adopting digital at a fast rate. Thus an apt and adequate information management strategy is required to generate true business value from their data assets. Organizations often tend to explore new territories by creating innovative services or providing services of another industry. Thus in order to identify new business opportunities, companies need to develop a robust as well as innovative information management strategy that is instrumental for finding: new internal and external information sources, advancements in information processing techniques, architectures and technologies and use data as a differentiating asset. Read more in this point of view from Nitin Kapoor an information management practice leader at Dell Digital Business Services.
To help the Intel sales organization optimize its account management and increase estimated incremental revenue, Intel IT developed an advanced predictive analytics solution to identify and prioritize which resellers have the greatest potential for high-volume sales.
In a proof of concept applying natural language processing and statistical modeling to PC client event logs and IT Help Desk incident reports, Intel IT predicted 20 percent of the incidents that occurred in the following 28 days. Intel’s new ability to proactively, rather than reactively, identify and solve potential client issues before they become widespread promises to deliver significant cost avoidance to the enterprise.
Recognizing the value that big data can contribute to business intelligence, Intel began researching and developing a big data platform based on the Apache Hadoop open source software framework. After a paper analysis and technical evaluation of products from multiple vendors, Intel implemented a low-cost, fully realized big data platform in five weeks.
Intel IT is implementing a strategy for multiple business intelligence (BI) data warehouses to provide significantly more powerful analytics capabilities to business groups across Intel. By providing an array of BI platforms, Intel is helping to mine a broader range of data faster, deeper, and more cost-effectively.
Over the last five years, Intel IT has evolved its approach to BI solutions for Intel’s worldwide sales organization to enable rapid delivery of advanced
self-service business intelligence (BI) and data visualization capabilities. By moving to a user-centered model and establishing stronger working partnerships
with our sales groups, Intel now delivers reports and dashboards to production in just two to four weeks—85 percent faster than in 2007.