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Showing 1 - 10 of 16 pages tagged with: Forrester Research
How Do You “Sur-thrive” Hyperadoption?
We are evolving from an information era to a customer-centric era. Enterprises must be innovative in delivering systems of insight to remain competitive. In this keynote session, our guest speaker, Forrester Vice President and Principal Analyst Brian Hopkins will discuss the importance of hyper-agility and the need to evolve from a lake to a fabric.In this session, Brian will discuss:
Data-Driven is Passé: Transform Into An Insights-Driven Enterprise
 After the dust of big data settles down, companies need to undertake the next transformational step: adopt systems of insight to shift the focus from data-to-insights to insights-to-action and transform from a data-driven to an insights-driven enterprise. Systems of insight delivers on what all the big data noise can't promise: tested insight at the point of action and continuous learning. However for it to be effective, systems of insight needs to be embedded within your company’s systems of engagement, record, and automation; and data virtualization is the glue that keeps all systems in...
Session 4: Business Agility Must Be Based on a New Flexible and Agile Data Approach
Gaining a deeper understanding of your customers’ needs, contextual marketing, and overall business intelligence and agility depend on accurate, timely, and relevant data. This data needs to be collected from a growing number of internal and external sources and then combined, refined, and fueled into a diverse portfolio of business intelligence and process applications.Join guest speaker Holger Kisker Ph.D. as he discusses what companies need today: a flexible data management architecture to cope with both traditional and emerging sources of data (in any structure), advanced data analytics...
Session 3: Build a Contextual Marketing Engine and Fuel It with Data
Traditional sources of competitive advantage have eroded as digitally-empowered customers have taken ownership of the relationships they have with companies and brands. These customers are out-running marketing campaigns and they expect high levels of personalization and relevance in their interactions. To succeed in this environment, marketers and business leaders must build what Forrester calls a contextual marketing engine, a brand-specific platform that exploits customer context to deliver utility and guide the customer into the next best interaction. Fueling this engine is data—about...
Session 2: Understanding the Customer Experience Ecosystem to Succeed in the Age of the Customer
In order to succeed in today’s business climate, every part of the organization must come together to consistently deliver a great customer experience.In this webinar, guest speaker Megan Burns, Vice President and Principal Analyst at Forrester Research Inc., will share her latest research on why this is the case and how companies can do this effectively. Viewers will learn how customer experience affects customer loyalty, which drivers of the experience impact loyalty the most, and best practices for establishing a disciplined system for customer understanding. This underscores the...
Session 1: CIOs Must Enable Business Agility via Modern Data Management in the Age of the Customer
In the last ten years, 75% of global 500 companies have fallen off the list. Why? They did not manage change well. For many, digital disruptors took their place with business models based on Internet connectivity, cloud-based applications, and mobile devices that connect everywhere. To help build the agile enterprise, CIOs must move beyond traditional technology agility, and become agile in ten dimensions of market, organization, and process. As data pervades in the age of the customer, modern data management principles including abstraction, data virtualization, logical data layer that...
[E-book] Data Virtualization: Advancements Driving Broad Adoption
By Noel Yuhanna, Forrester ResearchIn this ebook, Noel Yuhanna, Principal Analyst at Forrester Research and lead author of the recently published, The Forrester Wave™: Enterprise Data Virtualization, Q1 2015 report, explains the most up-to-date research on data virtualization – fresh trends, hot use cases and innovations and why it is essential for modern data architectures. This ebook also includes real-life examples from large and complex deployments of data virtualization.
Data Virtualization: Advancements Driving Broad Adoption
Traditional data integration approaches can no longer satisfy today’s new requirements - increasing data volumes, heterogeneous complexity, and extreme agility required to support new business initiatives. Data Virtualization's flexible architecture and expanding features are driving broad adoption and growth as enterprise architects use the technology to create a virtual data services layer to support requirements for secure, self-service access to real-time or batch data for a wide range of applications and processes.
Data Virtualization Enables Adoption of Key 2013 Technology Trends
Delivering New Insight, Faster Data Access, and Real-time Data Sharing.Key technology trends impacting enterprises in 2013 — Mobility, Big Data, Analytics and Cloud — require faster information access, seamless data integration, and real-time data from any type or source.These trends have led to increasing volume, complexity and usage of data which have created new data integration challenges and requirements facing enterprises today. Add to this the typical 50% — 100% annual growth in data volume for critical applications, and it is clear that traditional integration approaches are no longer...
Essential Guide to Using Data Virtualization for Big Data Analytics
Business is driving the need for better Analytics - historical, real-time, predictive, and cognitive - across a number of domains including customer, product, operations and more to become more competitive. Mirroring that, the data available to companies for such analytics is exploding in volume and complexity. Companies are adopting a myriad technologies from traditional data warehouses, OLAP tools, DW appliances, Big Data / Hadoop systems and streaming real-time analytics platforms to take advantage of these opportunities.