The use of artificial intelligence (AI) using machine learning (ML) will be the single most important trend in business software this decade because it can multiply the investment value of such applications and provide vendors an important source of differentiation to achieve a competitive advantage in what are today very mature software categories. I assert that by 2025, almost all Office of Finance software vendors will have incorporated some AI capabilities to reduce workloads and improve...
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Topics:
Office of Finance,
embedded analytics,
Data Management,
Business Planning,
Financial Performance Management,
ERP and Continuous Accounting,
digital finance,
AI and Machine Learning
As I stated when joining Ventana Research, the socioeconomic impacts of the pandemic and its aftereffects have highlighted more than ever the differences between organizations that can turn data into insights and are agile enough to act upon it and those that are incapable of seeing or responding to the need for change. Data-driven organizations stand to gain competitive advantage, responding faster to worker and customer demands for more innovative, data-rich applications and personalized...
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Topics:
Analytics,
Business Intelligence,
Data Integration,
Data,
data lakes,
data operations,
data platforms,
Streaming Data & Events,
AI and Machine Learning
I recently described how the data platforms landscape will remain divided between analytic and operational workloads for the foreseeable future. Analytic data platforms are designed to store, manage, process and analyze data, enabling organizations to maximize data to operate with greater efficiency, while operational data platforms are designed to store, manage and process data to support worker-, customer- and partner-facing operational applications. At the same time, however, we see...
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Topics:
embedded analytics,
Analytics,
Business Intelligence,
Data,
Digital Technology,
data platforms,
Analytics & Data,
Streaming Data & Events,
AI and Machine Learning
Organizations of all sizes are dealing with exponentially increasing data volume and data sources, which creates challenges such as siloed information, increased technical complexities across various systems and slow reporting of important business metrics. Migrating to the cloud does not solve the problems associated with performing analytics and business intelligence on data stored in disparate systems. Also, the computing power needed to process large volumes of data consists of clusters of...
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Topics:
Analytics,
Business Intelligence,
Data Integration,
Data,
data lakes,
data operations,
Streaming Analytics,
AI and Machine Learning
Ventana Research recently announced its 2022 Market Agenda for the Office of Finance, continuing the guidance we have offered since 2003 on the practical use of technology for the finance and accounting department. Our insights and best practices aim to enable organizations to operate with agility and resiliency, improving performance and delivering greater value as a strategic partner.
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Topics:
Office of Finance,
Business Intelligence,
Collaboration,
Business Planning,
Financial Performance Management,
ERP and Continuous Accounting,
Revenue,
blockchain,
robotic finance,
Predictive Planning,
lease and tax accounting,
profitability management,
AI and Machine Learning
Ventana Research recently announced its 2022 Market Agenda for the Office of Revenue, continuing the guidance we have offered for nearly two decades to help organizations realize optimal value from applying technology to improve business outcomes. Chief sales and revenue officers and their associated operations teams are experts in their respective fields but may not have the guidance needed to employ technology effectively. As we look to 2022, we are focusing on the entire selling and buying...
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Topics:
Sales,
Analytics,
Internet of Things,
Data,
Sales Performance Management,
Digital Technology,
Digital Commerce,
Conversational Computing,
mobile computing,
Subscription Management,
extended reality,
intelligent sales,
partner management,
Sales Engagement,
AI and Machine Learning
Organizations today have huge volumes of data across various cloud and on-premises systems which keep growing by the second. To derive value from this data, organizations must query the data regularly and share insights with relevant teams and departments. Automating this process using natural language processing (NLP) and artificial intelligence and machine learning (AI/ML) enables line-of-business personnel to query the data faster, generate reports themselves without depending on IT, and...
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Topics:
embedded analytics,
Analytics,
Business Intelligence,
Data Integration,
Data,
natural language processing,
data lakes,
data operations,
data platforms,
AI and Machine Learning
The internet is a rich source of information and is used by buyers to research new applications and offerings well before ever engaging a vendor and salesperson. Along with massive growth in offerings, this is a major reason why sales teams are facing increasing challenges to successfully sell and attain targets.
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Topics:
Sales,
Revenue Management,
Sales Engagement,
AI and Machine Learning
Data lakes have enormous potential as a source of business intelligence. However, many early adopters of data lakes have found that simply storing large amounts of data in a data lake environment is not enough to generate business intelligence from that data. Similarly, lakes and reservoirs have enormous potential as sources of energy. However, simply storing large amounts of water in a lake is not enough to generate energy from that water. A hydroelectric power station is required to harness...
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Topics:
Analytics,
Business Intelligence,
Cloud Computing,
Data Governance,
Data Integration,
Data,
Digital Technology,
data lakes,
data operations,
data platforms,
AI and Machine Learning
As I noted when joining Ventana Research, the range of options faced by organizations in relation to data processing and analytics can be bewildering. When it comes to data platforms, however, there is one fundamental consideration that comes before all others: Is the workload primarily operational or analytic? Although most database products can be used for operational or analytic workloads, the market has been segmented between products targeting operational workloads, and those targeting...
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Topics:
business intelligence,
Analytics,
Data,
data lakes,
data operations,
data platforms,
AI and Machine Learning