Top 5 Worst Practices for Big Data Deployments and How to Avoid Them

Presented by

Matt Maccaux, Global Big Data Lead, Dell EMC; Anant Chintamaneni, Vice President, Products, BlueData

About this talk

Watch this on-demand webinar to learn how to deploy a scalable and elastic architecture for Big Data analytics. Hadoop and related technologies for Big Data analytics can deliver tremendous business value, and at a lower cost than traditional data management approaches. But early adopters have encountered challenges and learned lessons over the past few years. In this webinar, we discussed: -The five worst practices in early Hadoop deployments and how to avoid them -Best practices for the right architecture to meet the needs of the business -The case study and Big Data journey for a large global financial services organization -How to ensure highly scalable and elastic Big Data infrastructure Discover the most common mistakes for Hadoop deployments – and learn how to deliver an elastic Big Data solution.

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HPE Enterprise Software (formerly BlueData)
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Hewlett Packard Enterprise (HPE) – which recently acquired BlueData and MapR – is transforming how enterprises deploy AI / Machine Learning (ML) and Big Data analytics. HPE’s container-based software platform makes it easier, faster, and more cost-effective for enterprises to innovate with AI / ML and Big Data technologies – either on-premises, in the public cloud, or in a hybrid architecture. With HPE, our customers can spin up containerized environments within minutes, providing their data scientists with on-demand access to the applications, data, and infrastructure they need.