Introducing Cloudera Data Science Workbench for HDP

Data scientists require on-demand access to data, powerful processing infrastructure, and multiple tools and libraries for development and experimentation. Meanwhile, IT has a difficult time keeping up with these changing needs while ensuring operational efficiency and compliance. Sound familiar? CDSW was designed precisely to r
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Spotlight

Imagine that it’s 2007. You’re a top executive at major search engine company, and Steve Jobs has just unveiled the iPhone.For some, real-time big data analytics (RTBDA) is a ticket to improved sales, higher profits and lower marketing costs. To others, it signals the dawn of a new era in which machines begin to think and respond more like humans.

OTHER ON-DEMAND WEBINARS

Delivering Trusted AI with DataRobot and Microsoft

datarobot.com

In order to maximize the value of your data and democratize AI across the organization, citizen data scientists are emerging and implementing machine learning models into business analytics applications such as Microsofts Excel, Power Apps, Power BI, Reporting Services and more. In this webinar, attendees will learn more about how their organizations can add AI to BI, making more predictive decisions along the way.
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Financial Analytics Fundamentals Use Data Science And Analytics In BFSI

analyticsindiamag

For a data analyst, financial analytics is one of the most useful skill sets to inculcate given the rapid growth of roles in this booming sector. A specialisation in this field will be a value-add given the rapid rise of fintech in India’s digital ecosystem. Financial analytics helps companies uncover deeper insights into the company’s finances and can help in finding pain points and new streams of revenue. Financial Analysts work in investment firms, banks, insurance sector and digital payments companies.
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Data Privacy During Economic Downturn: How to Make It Work With Limited Resources?

The global spread of the novel coronavirus (COVID-19) and the economic impact that followed has prompted many businesses to furlough the workforce or migrate from the traditional office to remote-working environments. The volatile landscape has created incremental risks, especially for organizations heavily relying on IT Sec/Ops teams to monitor security and privacy and enforce regulatory compliance.
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The Rise of Data Mesh and Data Fabric Architectures

As businesses strive to advance digital transformation efforts, legacy architectures can be a significant obstacle to enabling the agility required to succeed in today's ever-changing data landscape. Many enterprises struggle with scaling the delivery of data and analytics to accommodate the growing array of data domains, users, and use cases. As a result, data mesh and data fabric architectures are on the rise with the aim of abstracting data management complexity, increasing data availability, and fostering greater collaboration.
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Spotlight

Imagine that it’s 2007. You’re a top executive at major search engine company, and Steve Jobs has just unveiled the iPhone.For some, real-time big data analytics (RTBDA) is a ticket to improved sales, higher profits and lower marketing costs. To others, it signals the dawn of a new era in which machines begin to think and respond more like humans.

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