Public cloud adoption is exploding and big data technologies are rapidly becoming an important driver of this growth. According to Wikibon, big data public cloud revenue will grow from 4.4% in 2016 to 24% of all big data spend by 2026. Digital transformation initiatives are now a priority for most organizations, with data and advanced analytics at the heart of enabling this change. This is key to driving competitive advantage in every industry.
For customers looking to establish a next-gen analytics platform, data lakes are a common approach. Industry analyst Tony Baer from Ovum Research will share his learnings on where to start and how to get the most from your data lake efforts based on his recent research.
The ability to enable all data to be analyzed, capture new data types (e.g., machine logs, social, and IoT), and obtain near-line storage for cold data are all reasons why data lakes are growing tremendously in adoption.
There is no better example of the important role that data plays in our lives than in matters of our health and our healthcare. There’s a growing wealth of health-related data out there, and it’s playing an increasing role in improving patient care, population health, and healthcare economics.
Join this webinar to hear how Baptist Health is using big data and advanced analytics to address a myriad of healthcare challenges—from patient to payer—through their consumer- centric approach.
Many organizations have invested in big data technologies such as Hadoop and Spark. But these investments only address how to gain deeper insights from more diverse data. They do not address how to create action from those insights.
Forrester has identified an emerging class of software—insight platforms—that combine data, analytics, and insight execution to drive action using a big data fabric.
Stream processing and analytics technologies provide opportunities for value creation including stream monitoring and alerting, operationalizing models in streams, and enriching stream data with other data to derive actionable insights in real-time. Join a lively panel of experts including representatives from MapR and SAP to discuss best practices for streaming analytics.
Join MapR and Dataguise webinar for best practices in achieving performance, reliability and protection of sensitive data in your big data deployments.
This session will cover:
- How to automatically detect sensitive data in your big data deployment Who has access to this sensitive data
- How can you securely share your big data for maximum leverage
- How you can monitor the effectiveness of your governance policies
How are leading enterprises deploying Hadoop with Spark in production? What key considerations should you consider to put your Spark-based innovative app to work faster?
In this webinar on October 8th at 10 am PT/1 pm ET, you'll hear real-life examples of companies turning data into action using Spark and Hadoop. Register now to learn:
Companies who harness and analyze data from transactional systems, social media, and other diverse sources to find valuable insights are more likely to outpace the competition. Yet leveraging big data assets, such as Hadoop, can be challenging. Modern data visualization solutions are helping companies overcome those challenges and present new opportunities for business optimization.
We hear it in the news more often than we should – data breaches are still occurring in spite of all the existing traditional security controls most companies have in place. How can you enhance – not replace – traditional security controls to enable your business to better protect sensitive or regulated data in a way that’s both efficient and cost-effective?
These days, businesses are facing three critical big data challenges: overflowing data warehouses, rapidly expanding data sources, and growing infrastructure expenditures. In order to combat these mounting pressures, businesses are turning to enterprise data hubs as a way to optimize their enterprise architectures.