10 Enterprise Analytics Trends to Watch in 2019

MicroStrategy

By 2025, IDC predicts the global datasphere will grow from 33 zettabytes currently to 175 zettabytes, with the majority of this data being managed and created by enterprise organizations. How will businesses make the most of all of this data? Watch this on-demand webcast to hear the trends that will drive both future success and disruption from today’s top thought leaders including: Ronald van Loon. Forrester’s Mike Gualtieri. Constellation Research’s Ray Wang and Doug Henschen.
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Spotlight

Federal data is growing at an astounding rate, expected to double every two years. However, data collected from a wide variety of sources such as blogs, emails, videos, social media, photos and other types of sensors often are unused. What makes their analysis difficult is their volume, the velocity with which they arrive, their variety, and the validity of their pedigree over the entire data life cycle. Xerox understands the challenges and the opportunities posed by the explosion in data, and inherent value data analytics brings to produce new insights. By using natural language processing, graph analytics, Hadoop, machine learning, and predictive analytics, agencies can realize the latent value potential sitting in large document stores and other operational datasets.

OTHER ON-DEMAND WEBINARS

Global Data Management in the Cloud

tdwi.org

Organizations that operate worldwide typically need to manage data both locally and globally. Local business units and subsidiaries must address region-specific data and accounting standards, regulations, customer requirements, and market drivers. At the same time, corporate headquarters must share data broadly and maintain a complete view of performance for the entire enterprise. For many global firms, data is the business. They need state-of-the-art data management just to remain innovative and competitive. Hence, multinational businesses face a long list of new business and technical requirements for modern data management.
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The Future of Healthcare and the Transition to Big Data

TechD

During this webinar you will: - Boost your Medicare Hospital Compare (MHC) and Accountable Care Organization (ACO) ratings Avoid fines and penalties from the Affordable Healthcare Act - Increase the quality of provided healthcare - Lower management, administrative and data center operational costs without compromising core business values - Deliver Products and Services per consumer needs, operating standards and regulations while minimizing cost and maximizing outcomes - Support real-time, event-driven service processes and decision management capabilities
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Rapid Response Analytics Accelerates Analytics ROI

Health Catalyst Inc

Rapid Response Analytics (RRA), an application suite that consists of two elements: curated, modular data kits called DOS™ Marts and Population Builder, a powerful self-service tool that lets any type of user, from physician executive to frontline nurses and population health teams explore their data and quickly build populations without needing to know how to write SQL and data science code. RRA increases an analytics team’s productivity by up to 10x and reduces its time to develop analytics by as much as 90 percent. Analysts can spend more time focusing on key strategic analysis and less time on repetitive tasks that can lead to inconsistent results and a backlog of requests. Learning Objectives: Discover how RRA is like a meal delivery kit that allows you to take components and customize them to quickly tailor and deliver meaningful insights.
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Data and AI: Accelerators of Banking CX

Sas

How important are data and analytics to a banker’s bottom-line objectives – growing deposits, loans and the customer base? In the latest Digital Banking Report, AI for Improved Customer Experience, almost 90 percent of respondents indicated that advanced analytics is extremely or very important to capabilities like cross-channel contextual communications, proactive advice and audience targeting.
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Spotlight

Federal data is growing at an astounding rate, expected to double every two years. However, data collected from a wide variety of sources such as blogs, emails, videos, social media, photos and other types of sensors often are unused. What makes their analysis difficult is their volume, the velocity with which they arrive, their variety, and the validity of their pedigree over the entire data life cycle. Xerox understands the challenges and the opportunities posed by the explosion in data, and inherent value data analytics brings to produce new insights. By using natural language processing, graph analytics, Hadoop, machine learning, and predictive analytics, agencies can realize the latent value potential sitting in large document stores and other operational datasets.

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