Customer Case Studies of Self-Service Big Data Analytics
In the new world of big data, analysts are challenged to ask questions that were never possible before. Self-service tools empowers business users to rapidly gather, analyze and visualize data from board, diverse data sources. Analyzing these sources provides new answers and new business opportuni
In the new world of big data, analysts are challenged to ask questions that were never possible before. Self-service tools empowers business users to rapidly gather, analyze and visualize data from board, diverse data sources. Analyzing these sources provides new answers and new business opportunities for those smart enough to answer the new questions. Free-up your IT staff so they no longer have the need to response to routine report requests. Business users can now rely on the rapid delivery of advanced self-service BI and data visualization capabilities to solve complex problems and capitalize on new opportunities.
In this session you will learn:
-Customer examples and return on investment from self-service big data analytics
-How business analysts can take advantage of Machine Learning
-Best practices in self-service big data analytics
RecordedFeb 19 2014
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* Brian Boroff, Head of Customer Success and User Operations, Asana
* Jon Ferrara, CEO/ Founder Nimble
* Stewart Rogers, Director Marketing Technology, VentureBeat
Customer experience is a tough one -- we all have seen those businesses who think they're building a great scalable customer experience, but have customers who might not have the same opinion. And it's not enough to build a great product -- we define ourselves in the marketplace through each and every interaction we have with the customer.
You might understand that the reason you're doing something is for a very valid business reason, but the customer may interpret that action entirely differently. And your world class customer service can sometimes start to falter as your startup organization adds more resources and more layers -- good for your growth but sometimes risking the very people who made your company successful. Ouch.
Customer engagement doesn't take costly tools and high priced business analysts -- but it's also not always intuitive. We're going to show you some no-nonsense ways to keep customers loyal and driving growth while also building amazing customer experience that scales along with your business. Our panel of experts will share tactics and strategies that will help you kick start and refine your approach to delivering service -- and helps your company grow even faster.
In this webinar you'll:
* Understand what your customer wants and needs throughout the product lifecycle.
* Learn strategies for rethinking the role of customer service within the organization
* Create a new process for empowering employees to retain a top tier customer experience
* Identify potential obstacles that may be causing customer attrition
If you need guidance with performance, capacity, and sizing using Red Hat® Ceph Storage on Supermicro servers, then this webinar is for you. Red Hat and Supermicro have performed extensive lab testing to characterize Red Hat Ceph Storage performance on a range of Supermicro storage servers.
Join this webinar to:
•See benchmarking results that led to Ceph-optimized Supermicro server SKUs.
•Learn how to best architect various sizes of Red Hat Ceph Storage clusters for throughput and cost/capacity optimized workloads deployed on Supermicro servers
Why choose between your datacenter and the cloud? A hybrid cloud solution gives you both.
You have already invested in server products that are on premises. You believe that Cloud is the future and the power of the Cloud can open up countless opportunities for people to do more and achieve more. But how can you leverage the Cloud given your current infrastructure?
Join this webcast to learn Hybrid Cloud options as well as how to extract value from your existing investments by:
- Expanding your options without adding complexity
- Easily moving workloads from your datacenter
- Building hybrid applications that leverage both on-premises and cloud resources
- Taking advantage of storage, backup, and recovery options with increased efficiency and reduced cost.
What can we do with massive amounts of diverse data coming from everywhere at a breakneck pace? Machine learning, an automated data analysis approach, delivers coveted business insights with iterative learning from data to uncover critical trends, patterns and relationships.
Join our webinar to learn about:
•Machine learning basics, market adoption and business impact
•How machine learning can be leveraged in business applications
Today’s technology leaders need to tackle the big trends—cloud, big data, the Internet of Things, mobility, social media—while lowering IT spend year over year. That’s a tall order. Storage cost projections are becoming unsustainable, and organizations need new, more cost-effective ways of delivering storage. Nexenta provides a software-only storage solution that includes a rich feature set across all block, file, and object storage needs. This enables you to deliver software- defined infrastructure for legacy and next-generation enterprise applications, virtual workloads, file service applications, and more—all while maintaining the freedom to choose which platform to run on.
In this session you will learn more about the main kinds of software-defined storage technology landscape you’ll likely deploy:
Each solution is easy to support with Nexenta software and commercial off-the-shelf Intel-based hardware.
In recent years, some users have harbored concerns about clouds in general, as well as their use in data warehousing. As the number of user organizations practicing elastic data warehousing on clouds has increased, the track record of success has helped other users get past perceptual barriers and other myths concerning security, multi-tenancy, and interfacing with clouds.
We all know that data warehouses and users’ best practices for them are changing dramatically today. As users build new data warehouses and modernize established ones, they are turning to cloud-based elastic data warehousing, because the automation of elasticity yields agility, ease of use, scalability, and performance, while reducing maintenance, tuning, capital investments, and other costs.
This webinar will:
- Demystify elastic data warehousing by debunking myths about it
- Define elastic data warehousing and its goals in terms that data management professionals and business users can relate to
- Show how cloud-based data-driven tools and platforms have proved themselves, such that users are now more comfortable adopting them
- Discuss the real-world benefits of data warehousing, data management, and analytics on elastic clouds
- Explain how data warehousing solutions built to leverage the full capabilities of an elastic cloud can satisfy new requirements for analytics, big data, data streams, and multi-structured data
Les entreprises entrent de plein pieds dans le monde Big Data. Avec Microsoft Azure et Hortonworks vous pourrez monter un cluster Hadoop aussi simplement que d'aller acheter une baguette.
Rejoignez-nous pour un webinar pendant lequel nous vous montrerons comment débuter avec votre HDP sur Microsoft Azure.
Nous aborderons les sujet suivants:
- La Marketplace Microsoft Azure
- Les produits Hortonworks pour le Big Data: HDP et HDF
- Les atouts d'une architecture Cloud pour Hadoop
- Démo de création et d'utilisation d’un cluster Hortonworks sur Azure à travers le Marketplace
Neil Raden, Hired Brains and Andrew Brust, Datameer
The BI landscape has evolved from one led by IT into one now led by the business user. This means, data architectures are now built on the fly as potentially interesting data is sourced and models are driven from the data. As a result of the new roles, implications need to be understood by all parties prior to investing in a big data solution.
Join us for this webinar, 10 Questions to Align Your Big Data Project with Business Requirements, as Neil Raden, CEO and Principal Analyst at Hired Brains and Andrew Brust, Datameer's Senior Director of Market Strategy and Intelligence, discuss the top 10 questions to consider such as:
- Why alignment with the business matters?
- What will you do with the analytic results?
- How do you measure success?
Hadoop is changing. Despite being Big Data’s poster child for the last several years, changes to Hadoop's architecture mean it can now work for small data too. Data volumes aside, Hadoop is becoming defined more by ecosystem tools that are compatible with its file system and less by its own processing and management capabilities.
Datameer makes big data analytics simple. Datameer gives users a unified, self-service environment to integrate, prepare, analyze, visualize, and operationalize big data analytics. Hundreds of customers, including CIOs, CMOs, CTOs, doctors, scientists, law enforcement officials, and even Olympic athletes all rely on Datameer to help them get from raw data to insight faster than ever. Datameer combines Hadoop’s unlimited storage and compute power with a common spreadsheet interface and powerful functionality, quickly transforming businesses into agile, data-driven organizations.