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AI-Powered Data Unification for Successful Data-Driven Initiatives Better Trust in Data for Better Use of Data The current economic climate has highlighted more than ever the differences between enterprises that can turn data into actionable insights and those that are incapable of seeing or responding to the need for change. Data-driven enterprises stand to gain a competitive advantage by... Read More

Topics: Analytics and Data


Unlock Business Value with Speed, Scale and Simplicity The Importance of Data In today’s competitive business environment, enterprises must effectively harness and maximize the power of data and artificial intelligence (AI) to be successful. To do so, companies need a powerful data stack that takes data from a state of chaos and turns it into a strategic advantage. The opportunity to capitalize... Read More

Topics: Analytics and Data


Accelerate Enterprise Data Science in the Hybrid Cloud with MLOps Overcome the Challenges of Operationalizing AI/ML Data is an extremely valuable asset for every organization, but it is meaningless until it is used to make actionable decisions. Given the volume of data generated and collected today, using artificial intelligence with machine learning (AI/ML) is the most efficient way for... Read More

Topics: Data


Harnessing CX Automation for Elevated Experiences Executive Summary Contact centers typically operate at the extreme edge of capacity, balancing customer expectations against the imperative to control costs. Bridging this capacity gap has historically proven elusive for operations teams, often forcing compromises in either service quality or agent performance, until artificial intelligence (AI)... Read More

Topics: Customer Experience


Data Integration Considerations for ISVs and Data Providers Real-Time Data and AI Drive Businesses Today Data is an extremely valuable asset to almost every organization, and it informs nearly every decision an enterprise makes. It can be used to make better decisions at almost every level of the enterprise—and to make them more quickly. But to take full advantage of the data and to do so quickly... Read More

Topics: Analytics and Data


Harness Better Tools Powered by AI to Quickly Maximize Recurring Revenue The Impact of Failed Customer Payments and Passive Churn Failed customer payments for recurring subscriptions are often seen as a cost of doing business when using subscription revenue models. Payment failure rates approaching 25% of recurring transactions are not uncommon. And these failures can happen for a variety of... Read More

Topics: Office of Revenue


Closing the Loop on Data Generation and Business Decisions Accelerating Business Insight The current economic climate has highlighted more than ever the differences between organizations that can turn data into actionable insights and those that are incapable of seeing or responding to the need for change. Data-driven organizations stand to gain a competitive advantage when they increase the... Read More

Topics: Digital Technology


Achieve Platform Independence and FedRAMP Compliance Modern Data Security Means Authentication Today's information security and privacy requirements are not just compliance exercises; they are an integral part of a comprehensive, strategic and continuous risk-based governance program. Cybersecurity threats are more prevalent and dangerous than ever, and breaches can have huge financial and... Read More

Topics: Digital Technology


Balance Costs and Performance Between MPP Databases and Apache Spark Different Designs for Different Functions Apache Spark and massively parallel processing (MPP) analytical databases are designed for different things. The first generation of “big data” architectures relied upon the distributed Hadoop and MapReduce framework for analytical processing. This framework provided a breakthrough in... Read More

Topics: Analytics


Think Differently to Avoid Silos The Analytics Continuum In practical reality, “analytics” comprises many types of analysis, including reporting, visualization, planning, real-time processes, artificial intelligence and machine learning (AI/ML), and natural language processing. The analytics continuum must not only support these analyses, but it must also include the appropriate data management,... Read More

Topics: Analytics