A few years ago – somewhat tongue in cheek – I began using the term “data pantry” to describe a type of data store that’s part of a business application platform, created for a specific set of users and use cases. It’s a data pantry because, unlike a general-purpose data store such as a data warehouse, everything the user needs is readily available and easily accessible, with labels that are immediately recognized and understood.
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Topics:
Data Management,
Business Planning,
Financial Performance Management,
ERP and Continuous Accounting,
digital finance,
AI and Machine Learning
Organizations are continuously increasing the use of analytics and business intelligence to turn data into meaningful and actionable insights. Our Analytics and Data Benchmark Research shows some of the benefits of using analytics: Improved efficiency in business processes, improved communication and gaining a competitive edge in the market top the list. With a unified BI system, organizations can have a comprehensive view of all organizational data to better manage processes and identify...
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Topics:
business intelligence,
embedded analytics,
Data Governance,
Data Management,
natural language processing,
data operations,
Streaming Analytics,
operational data platforms,
AI and Machine Learning
I previously described the concept of hydroanalytic data platforms, which combine the structured data processing and analytics acceleration capabilities associated with data warehousing with the low-cost and multi-structured data storage advantages of the data lake. One of the key enablers of this approach is interactive SQL query engine functionality, which facilitates the use of existing business intelligence (BI) and data science tools to analyze data in data lakes. Interactive SQL query...
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Topics:
Analytics,
Business Intelligence,
Cloud Computing,
Data,
Digital Technology,
data lakes,
data operations,
data platforms,
Analytics & Data,
AI and Machine Learning
I’ve never been a fan of talking about semantic models because most of the workforce probably doesn’t understand what they are, or doesn’t recognize them by name. But the findings in our recent Analytics and Data Benchmark Research have changed my mind. The research shows how important a semantic model can be to the success of data and analytics processes. Organizations that have successfully implemented a semantic model are more than twice as likely to report satisfaction with analytics (77%)...
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Topics:
Business Intelligence,
Data Management,
data operations,
Analytics & Data,
semantic model,
AI and Machine Learning
Artificial intelligence using machine learning has passed through the bright, shiny object stage and software vendors are well into the process of making the concept a reality in their offerings. Ventana Research defines AI as the use of technology to process information in much the way humans do, including improving accuracy in recommendations, actions and conclusions as more data is received. I like the alternative term “augmented intelligence” because it emphasizes that these systems enhance...
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Topics:
Planning,
Machine Learning,
Budgeting,
Business Planning,
Financial Performance Management,
forecasting,
digital finance,
profitability management,
AI and Machine Learning
I previously explained how the data lakehouse is one of two primary approaches being adopted to deliver what I have called a hydroanalytic data platform. Hydroanalytics involves the combination of data warehouse and data lake functionality to enable and accelerate analysis of data in cloud storage services. The term data lakehouse has been rapidly adopted by several vendors in recent years to describe an environment in which data warehousing functionality is integrated into the data lake...
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Topics:
business intelligence,
Analytics,
Data,
data lakes,
data platforms
Compensation management is a key talent management process involving all workers and managers within an organization. Determining and providing the appropriate compensation for each person — whether it involves base pay, merit pay, or variable pay and incentives such as bonuses — is critical to being able to attract and retain productive members of the workforce, including full- and part-time employees, contingent workers and contractors. The complexities of compensation often prove to be a...
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Topics:
Human Capital Management,
Total Compensation Management
Organizations are constantly trying to streamline and optimize business data to solve complex problems and identify opportunities to increase revenue and accelerate business growth. The data is usually stored in multiple systems with various data governance rules, which makes it complicated to democratize data and analytics within an organization. The most pressing concerns cited by participants in our Analytics and Data Benchmark Research include difficulty integrating with business processes,...
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Topics:
Domo,
BI platform
As I recently described, it is anticipated that the majority of database workloads will continue to be served by specialist data platforms targeting operational and analytic workloads, albeit with growing demand for hybrid data processing use-cases and functionality. Specialist operational and analytic data platforms have historically been the since preferred option, but there have always been general-purpose databases that could be used for both analytic and operational workloads, with tuning...
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Topics:
Analytics,
Business Intelligence,
Cloud Computing,
Data,
Digital Technology,
data platforms,
Analytics & Data
Organizations are scaling business intelligence initiatives to gain a competitive advantage and increase revenue as more data is created. Lack of expertise, data governance and slow performance can impact these efforts. Our Analytics and Data Benchmark Research finds some of the most pressing complaints about analytics and BI include difficulty integrating with other business processes and flexibility issues. Kyvos is a BI acceleration platform that enables BI and analytics tools to analyze...
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Topics:
Business Intelligence,
Data Governance