Data is growing exponentially. In 2020 alone 64 Zettabytes of data was created! At the same time, many IT organizations are struggling with flat IT budgets—driving the need for flexible data storage consumption. As businesses grow, their ability to consume capacity in a flexible manner becomes even more critical. Tom Christensen, Hitachi Vantara Global Technology Advisor, discusses on-prem, public cloud and private cloud options and the advantages of private cloud, consumption based services.

The growth in IoT data collection and processing underscores the need for comprehensive data management strategies. The average enterprise today has deployed – and collects data from – nearly 4,000 IoT endpoints. And these organizations expect a 65% increase in the number of connected IoT endpoints over the next two years. Hear from 451 Research (part of S&P Global Market Intelligence) and Hitachi Vantara to assess the business impact of edge computing and IIoT on data management.

Tim Stammers of 451 Research discusses key technologies and trends for midsize enterprises and the cloud

Are you ready to harvest the massive real-time data that your organization generates? You need to master streaming data to  gain an edge in business, in every industry. But, most businesses still rely on batch and incremental processing. If that’s you, don’t despair. Join this session to understand key concepts, common technologies and best practices you need to succeed with streaming  data. You will  also learn about the Hitachi Vantara streaming data stack and how we can help you meet your goals.

One of the toughest challenges for data professionals today is migrating data from on-premises environments to the cloud. Many companies still lack the tools and infrastructure to ingest and process complex datasets to achieve critical business outcomes. Tune in for a joint-session with Snowflake and Hitachi Vantara as we discuss best practices to address common edge-to-multicloud issues and how our joint offering can dramatically simplify data preparation, migration and analytics tasks to help deliver analytics-ready data in the cloud.

The growing waves of data that you’re pulling in include sensitive, personal or confidential data. This can become a compliance nightmare, especially with rules around PII, GDPR and CCPA, and it takes too much time to manually decide what should be protected. In this session, we will show how AI-driven data catalogs can identify sensitive data and share  that identification with your data security platforms to automate its discovery, identification and security.  You'll see how this dramatically reduces your time to onboard data and makes it safely available  to your business  communities.

Struggling to extract insights and actionable intelligence from your data? With more data science and analytic solutions available today, do the handoffs among data scientists, IT and the business continue to disrupt your analytics value chain or are they becoming even more difficult? We’ve seen this cause “data despair” and decelerate investments in analytics and machine learning projects. In fact, only a quarter of organizations believe that they are actually building the “data culture” that fosters success.