The Office of Finance can be compared to a numbers factory where the main raw material, data, is transformed into financial statements, management accounting, analyses, forecasts, budgets, regulatory filings, tax returns and all kinds of reports. Data is the strategic raw material of the finance and accounting department. It is the key ingredient in every sale and purchase as well as every transaction of any description. Quality control is essential to achieving high standards of output in any...
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Topics:
Office of Finance,
embedded analytics,
Analytics,
Business Intelligence,
Data Management,
Business Planning,
ERP and Continuous Accounting,
data operations,
digital finance,
operational data platforms,
Analytic Data Platforms,
Revenue, Lease and Tax Accounting,
Purchasing/Sourcing/Payments,
Consolidate/Close/Report,
AI and Machine Learning
The data and analytics sector rightly places great importance on data quality: Almost two-thirds (64%) of participants in Ventana Research’s Analytics and Data Benchmark Research cite reviewing data for quality and consistency issues as the most time-consuming task in analyzing data. Data and analytics vendors would not recommend that customers use tools known to have data quality problems. It is somewhat surprising, therefore, that data and analytics vendors are rushing to encourage customers...
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Topics:
Analytics,
Data Governance,
Data Management,
Data,
Digital Technology,
natural language processing,
Analytics & Data,
AI and Machine Learning
MicroStrategy is a long-standing business intelligence and analytics vendor that operates worldwide. Founded in 1989, this publicly traded company with hundreds of millions of dollars in revenue recently held its first in-person conference since prior to the pandemic. Similar to previous in-person events, the event was well attended by about 2,000 attendees and exhibitors. The theme, “MicroStrategy ONE,” is a way to explain the breadth of capabilities the company offers. The breadth of the...
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Topics:
embedded analytics,
Analytics,
Business Intelligence,
Digital Technology,
natural language processing,
Analytics & Data
Artificial intelligence (AI) has evolved from a highly specialized niche technology to a worldwide phenomenon. Nearly 9 in 10 organizations use or plan to adopt AI technology. Several factors have contributed to this evolution. First, the amount of data they can collect and store has increased dramatically while the cost of analyzing these large amounts of data has decreased dramatically. Data-driven organizations need to process data in real time which requires AI. In addition, analytics...
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Topics:
Analytics,
Digital Technology,
natural language processing,
Analytics & Data,
AI and Machine Learning
The data platforms market has traditionally been divided between products specifically designed to support operational or analytic workloads, with other market segments having emerged in recent years for data platforms targeted specifically at data science and machine learning (ML), as well as real-time analytics. More recently, we have seen vendor strategies evolving to provide a more consolidated approach, with data platforms designed to address a combination of analytics and data science, as...
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Topics:
Analytics,
Business Intelligence,
Cloud Computing,
Data,
Digital Technology,
Analytics & Data,
operational data platforms,
Analytic Data Platforms,
AI and Machine Learning
Generative AI is a class of artificial intelligence used to generate new, seemingly real content. Broadly speaking, AI has traditionally been used to identify patterns in data and apply those patterns to categorize and predict behaviors. For instance, it can organize customers into groups (or clusters) with similar characteristics, or predict which customers are most likely to respond to certain offers.
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Topics:
Analytics,
Digital Technology,
AI and Machine Learning
The recent publication of our Value Index research highlights the impact of intelligent applications on the operational data platforms sector. While we continue to believe that, for most use cases, there is a clear, functional requirement for either analytic or operational data platforms, recent growth in the development of intelligent applications infused with the results of analytic processes, such as personalization and artificial intelligence (AI)-driven recommendations, has increasing...
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Topics:
Analytics,
Business Intelligence,
Cloud Computing,
Data,
Digital Technology,
Analytics & Data,
operational data platforms,
Analytic Data Platforms
In my perspective on decision intelligence, I lamented the fact that business intelligence technologies have left the rest of the exercise to the reader for too long. Making a decision is a process that involves many steps and many people. Decision-making is so complicated and divorced from day-to-day business processes that organizations have had to create entirely separate teams to focus on the analytics and data to support it. One aspect of the decision-making process that can be enhanced by...
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Topics:
business intelligence,
Analytics,
Digital Technology,
Analytics & Data,
Collaborative & Conversational Computing
Organizations are becoming increasingly aware of the potential value that can be gained by processing big data. As data sources grow, it becomes important to have tools and methods to effectively process, analyze and visualize this information from disparate systems and warehouses.
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Topics:
business intelligence,
embedded analytics,
Analytics,
Streaming Analytics
People analytics is the application of data and statistical methods to better understand and optimize the human capital within an organization. It has become a crucial aspect of business strategy as organizations seek to make data-driven decisions about the workforce. In the past decade, the people analytics market has experienced substantial growth, as businesses look for ways to gain insight into the effectiveness and efficiency of human capital investments. Most HCM technology platforms...
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Topics:
Human Capital Management,
Analytics,
HR Analytics,
People Analytics,
HCM Analytics