The Ultimate MarTech Hiring Guide
In this guide, your friends at Vitamin T describe some common MarTech roles in today’s workplace, explain how to figure out what MarTech professionals you need to add to your team, and give you some tips on how to screen MarTech candidates for your company.
The Seven Steps to Modern Analytics Success
More than 60-percent of analytics projects are predicted to fail. One of the big reasons is they can take too long―and time to insight is a critical success factor. Old school sequential development and delivery, lack of business and IT collaboration, and unclear governance can all can throttle projects.
The complimentary Eckerson Group whitepaper “The New Analytics Lifecycle: Accelerating Insight to Drive Innovation,” provides a proven blueprint for organizations to reimagine their analytics delivery methodologies—so they’re more agile and responsive. You’ll learn:
– The 12 choke points to avoid that slow analytics initiatives
– How to create a 3-tier analytics strategy
– A proven 7 step methodology for rapid analytics success
Get the latest insights on how to upgrade your analytics delivery models based on Eckerson Group’s hands-on experience helping Fortune 2000 companies succeed with business intelligence, analytics, data management, data governance, performance management, and data science.
Achieving Self-Service for Enterprise Data Analysts
Analysts and analytic leaders at world-class enterprises are embracing the self-service data analytics shift to answer the demands for faster and deeper insights, and more importantly setting themselves apart from their less enabled peers.
This whitepaper features:
– Why enterprises are moving their processes to self-service models
– A comparison of analytics platforms and capabilities
– Case studies from Hyatt, JPMorgan Chase and Southwest Airlines
– Read this whitepaper and see why the shift toward self-service data analytics is empowering leading analysts and analytic teams to improve processes, eliminate repetitive tasks, build better relationships with IT, and deliver deeper insights faster.
Insurance In the Age of Analytics
A Snapshot of Analytics Maturity Within the Canadian Insurance Industry
From Data To Disruption: Innovation Through Digital Intelligence
With input from more than 600 business executives worldwide, we provide a lens into the value digital intelligence brings to your organization and help you understand what Digital Innovators are doing differently. As a CIO, you not only must think differently about the role data plays in your business strategy, but also must communicate the strategic priorities for the technology platforms and skills needed to enable the delivery of digital intelligence. To that end, this report showcases the key characteristics and approaches these Digital Innovators use to be successful.
Artificial Intelligence for Executives
Are you thinking about adding artificial intelligence to your organization? It’s certainly a hot topic and worth the attention.
This paper outlines the SAS approach to AI and explains key concepts. It also provides process and implementation tips if you are considering adding AI technologies to your business and analytical strategies.
The Evolution of Analytics
Analytics is now an expected part of the bottom line. The irony is that as more companies become adept at analytics, it becomes less of a competitive advantage. Businesses are now being forced to look deeper into their data to increase efficiency and competitiveness.
Enter machine learning. Recent advances have led to increased interest in adopting this technology as part of a larger, more comprehensive analytics strategy. But incorporating modern machine learning techniques into production data infrastructures is not easy.
Read this report to learn more about modern applications for machine learning, including recommendation systems, streaming analytics, deep learning and cognitive computing. And learn from the experiences of two companies that have successfully navigated both organizational and technological challenges to adopt machine learning and embark on their own analytics evolution.
How to Use Analytics for a Cognitive Business
As humans, we have the ability to think both analytically and creatively. The same should be true for your organization, with technology that helps you hypothesize by connecting fact to possibility. That is a defining trait of cognitive business: a new relationship with technology that empowers people by shifting technology’s role from enabler to advisor. Business technologies that automate and detect can now also advise and enhance human expertise, contributing to exponential increases in productivity and improved efficiencies across your organization.
IBM has developed a methodology that includes strategy, expertise and a game plan to accelerate your data and analytics success as a cognitive business. Download this guide to learn more.
How to Tackle the 7 Most Common Challenges with Big Data Integration
More organizations are realizing there is tremendous value locked away in their big data, and are seeking to tap into it to improve operations, boost revenues and gain a competitive edge. Companies that approach their big data strategically reap countless benefits.
However due to the many technical obstacles that can arise, a majority of big data projects fail. Are you making these big data mistakes? Complete the form to find out.
IBM: Your cognitive future
How next-gen computing changes the way we live and work
Organizations have just begun to scratch the surface of cognitive computing capabilities. From improving customer engagement to enhancing research capabilities that identify new life-saving medical treatments, the potential value is boundless. Through our research, we uncover multiple innovative opportunities across industries, creating chances for early adopters to achieve a substantial first-mover advantage.
WinterGreen Research estimates the global healthcare decision support market alone will increase to more than $200 billion by 2019 as a result of new cognitive computing technologies.
How Streaming Analytics Enables Real-Time Decisions
The idea of processing data from events as they are occurring is not new. Many platforms already have ways of generating alerts when certain thresholds are reached or when specific data is available.