Data Analytics

Showing 41 - 46 of 46 pages tagged with: Data Analytics

Myth Busters II: BI Tools and Data Virtualization are Interchangeable

Reporting tools, while important and necessary, focus on the visualization of data and it’s presentation to the business user. Data virtualization is a governed data access layer designed to connect to and provide transparency of all enterprise data. Yet the myth suggests that these technologies are interchangeable. So we’re going to take it on!Watch this webinar as we compare and contrast BI tools and data virtualization to draw a final conclusion.

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Denodo and RXP Joint Webinar: 'Use of Aggregated Healthcare Data to Enhance and Improve Patient Treatment'

More than anything else, the COVID-19 crisis has accelerated the focus on the use of enhanced data in our health system. There are a range of enhanced data sets and analytical tools that can be used to emerge stronger on the other side.Join this session to learn:How to aggregate health data from multiple data sets, across data sources for fast, powerful insights.How to use data and analytics to monitor supply chain and make data-driven decisions for maximum efficiency.How to use analytics tools to monitor patterns in data access to deliver early-warnings of misuse, fraud and improve cyber...

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Accelerate Self-Service Analytics with Virtualization and Visualisation (Thai)

ติดสปีดการวิเคราะห์ข้อมูลด้วยตัวเองแบบรวดเร็วแม่นยำด้วย Data Virtualization และ Data Visualisationองค์กรชั้นนำกำลังขยับตัวไปสู่การวิเคราะห์ข้อมูลทางธุรกิจด้วยตัวเอง เพราะผู้ใช้งานต้องการการเข้าถึงข้อมูลแบบทันทีเพื่อเห็นภาพแบบองค์รวมและหลากหลายมิติโดยไม่ต้องคำนึงถึง ตำแหน่งและ แหล่งที่มา หรือชนิดของข้อมูลสำหรับการตัดสินใจครั้งสำคัญData Virtualization (การทำให้เห็นข้อมูลแบบเสมือนจริง) และ Data Visualisation (การทำให้เห็นข้อมูลเป็นภาพ)ทำงานด้วยกันผ่านชั้นข้อมูลเชิงความหมายที่เป็นรูปแบบสากล Webinar...

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Simplifying Cloud Architectures with Data Virtualization

Moving applications and data to the Cloud is a priority for many organizations. The benefits - in terms of flexibility, agility, and cost savings - are driving Cloud adoption. However, the journey to the Cloud is not as easy as many people think. The process of moving application and data to the Cloud is challenging and can entail widespread disruption across the organization if not carefully managed. Even when systems are migrated to the Cloud, the resultant hybrid or multi-Cloud architecture is more complex for users to navigate, making it harder for them to get the data that they need to...

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Myth Busters I: Can data virtualization uphold performance with complex queries?

In the first webinar of the series, we bust the 'performance' myth.“What about performance?” is usually the first question that we get when talking to people about data virtualization. After all, the data virtualization layer sits between you and your data, so how does this affect the performance of your queries? Sometimes the myth is perpetuated by people with alternative solutions… the ‘Put all your data in our Cloud and everything will be fine. Data virtualization? Nah, you don’t need that! It can't handle big queries anyway,’ type of thing.Watch this webinar to look at the basis of the '...

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How Data Virtualization Adds Value to Your Data Science Stack (APAC)

For their machine learning and data science projects to be successful, data scientists need access to all of the enterprise data delivered through their myriad of data models. However, gaining access to all data, integrated into a central repository has been a challenge. Often 80% of the project time is spent on these tasks. But, a virtual layer can help the data scientist speed up some of the most tedious tasks, like data exploration and analysis. At the same time, it also integrates well with the data science ecosystem. There is no need to change tools and learn new languages. The data...

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