If you’re thinking about big data in the cloud, Apache Hadoop, or Apache Spark, start with the end in mind. How will you analyze all that data without creating more work for yourself, and provide secure, self-service access and visual analysis to everyone who needs it? Will your existing BI and analytics tools be able to scale and access new data formats?
Scale out, distributed data platforms call for distributed BI and visual analytics. With legacy BI tools, you need to extract and replicate data before you can analyze it. What if you want to analyze more dimensions or new data being ingested after you’ve already loaded a subset of data into your legacy BI tool? To solve these problems, organizations are turning to a web-based architecture for big data visualization that allows them to perform self-service analytics on large datasets directly from the browser, while taking advantage of in-Hadoop advanced analytic functions.
Join Arcadia Data in this webinar to hear how Procter & Gamble, Kaiser Permanente, and Royal Bank of Canada provide their employees with powerful visual analytics and data applications directly on modern data platforms. You’ll learn how you can use visual analytics to:
- Achieve faster and deeper insights with direct visualization of data in Hadoop, Apache Spark, Amazon S3, and other modern data platforms
- Provide self-service analytics for 100s of concurrent users on your data lake
- Secure your data without restricting authorized users
- Build data-centric applications for cyber security, trade surveillance, and marketing optimization
- Reduce costs, latency, and security risks