Over the past decade, how organizations manage processes and record data related to transactional events captured by an enterprise resource planning system has undergone a significant evolution. Some of the more recent changes have been the result of a steady migration to the cloud, since these systems are typically updated frequently, require less maintenance, have better performance and are more readily available than those operating on-premises.
Evolving ERP Systems Redefining Office of Finance Operations
Posted by
Robert Kugel on Dec 3, 2021 3:00:00 AM
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Topics: Office of Finance, Business Planning, ERP and Continuous Accounting, digital finance
Cockroach Labs Brings Developers and Serverless Database Together
Posted by
Matt Aslett on Dec 2, 2021 3:00:00 AM
Breaking into the database market as a new vendor is easier said than done given the dominance of the sector by established database and data management giants, as well as the cloud computing providers. We recently described the emergence of a new breed of distributed SQL database providers with products designed to address hybrid and multi-cloud data processing. These databases are architecturally and functionally differentiated from both the traditional relational incumbents (in terms of global scalability) and the NoSQL providers (in terms of the relational model and transactional consistency). Having differentiated functionality is the bare minimum a new database vendor needs to make itself known in a such a crowded market, however.
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Topics: Cloud Computing, Data, Digital Technology, Digital transformation, Digital Business, data platforms, Analytics and Data
Why Revenue Planning Should be Continuous and Year Round
Posted by
Stephen Hurrell on Dec 2, 2021 3:00:00 AM
With the emergence of multiple selling channels and the rise of the subscription model, the need for a unified approach to revenue planning and execution should be a priority for every organization. As I have written about in my analyst perspective Revenue Management: The Opportunity for Innovation and Optimization, this need to unify the approach and focus on alignment across all revenue supporting teams in furtherance of an organization’s objectives and targets is of key importance to ensure that teams handle different aspects of a customer’s journey and experience. And, as I will further discuss, this alignment between groups is rarely a happy accident but rather the result of forward-looking, continuous planning.
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Topics: Sales, Customer Experience, Sales Performance Management, AI and Machine Learning, subscription management, Revenue Management, Sales Engagement
Automating Workflows for a Better Customer Experience
Posted by
Keith Dawson on Dec 1, 2021 3:00:00 AM
Any organization that relies heavily on a large labor force looks to automation to reduce costs, and contact centers are no exception. They handle interactions at such large scale that almost any effort to automate some part of the process can deliver measurable efficiencies. Two factors have ratcheted up attention on automating customer experience workflows: the dramatic expansion of digital interaction channels, and the development of artificial intelligence and machine learning tools to facilitate workflow deployment.
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Topics: Customer Experience, Voice of the Customer, Analytics, Data Integration, Contact Center, Data, AI and Machine Learning, agent management, data operations, Digital Business, Experience Management, Customer Experience Management, Field Service
TIBCO Broadens Portfolio for Improved Analytics Efficiency
Posted by
David Menninger on Nov 30, 2021 3:00:00 AM
TIBCO is a large, independent cloud-computing and data analytics software company that offers integration, analytics, business intelligence and events processing software. It enables organizations to analyze streaming data in real time and provides the capability to automate analytics processes. It offers more than 200 connectors, more than 200 enterprise cloud computing and application adapters, and more than 30 non-relational structured query language databases, relational database management systems and data warehouses.
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Topics: embedded analytics, Analytics, Collaboration, Data Governance, Information Management, Data, Digital Technology, data lakes, AI and Machine Learning
